Mineral Revenues
MMS Could Do More to Improve the Accuracy of Key Data Used to Collect and Verify Oil and Gas Royalties Gao ID: GAO-09-549 July 15, 2009In fiscal year 2008, the Department of Interior's Minerals Management Service (MMS) collected over $12 billion in royalties from oil and gas production from federal lands and waters. Companies that produce this oil and gas self-report to MMS data on the amount of oil and gas they produced and sold, the value of this production, and the amount of royalties owed. Since 2004, GAO has noted systemic problems with these data and recommended improvements. GAO is providing: (1) a descriptive update on MMS's key efforts to improve the accuracy of oil and gas royalty data; (2) our assessment of the completeness and reasonableness of fiscal years 2006 and 2007 oil and gas royalty data--the latest data available; and (3) factors identified by oil and gas companies that affect their ability to accurately report royalties owed to the federal government.
MMS has several key efforts underway to improve the accuracy of the payor-reported data used to collect and verify royalties, but it is too soon to evaluate their effectiveness. MMS is in the process of implementing (1) GAO's past recommendations to help identify missing royalty reports and monitor payors' changes to royalty data; (2) recommendations from the Royalty Policy Committee--a group empanelled by the Secretary of the Interior to provide advice on managing federal and Indian leases and revenues--to improve edit checks, monitor the quality of natural gas, revise gas valuation regulations, and improve coordination with BLM; and (3) other efforts on adding specific edits for sales prices and identifying discrepancies in volumes between operators and payors. While much of the royalty data we examined from fiscal years 2006 and 2007 are reasonable, we found significant instances where data were missing or appeared erroneous. For example, we examined gas leases in the Gulf of Mexico and found that, about 5.5 percent of the time, lease operators reported production, but royalty payors did not submit the corresponding royalty reports, potentially resulting in $117 million in uncollected royalties. We also found that a small percentage of royalty payors reported negative royalty values, which cannot happen, potentially costing $41 million in uncollected royalties. In addition, payors claimed processing allowances 2.3 percent of the time for unprocessed gas, potentially resulting in $2 million in uncollected royalties. Furthermore, we found significant instances where payor-provided data on royalties paid and the volume and/or the value of the oil and gas produced appeared erroneous because they were outside of expected ranges. Oil and gas company representatives reported that several factors affect their ability to accurately report royalties, including complex land ownership, administratively combining leases into units, ambiguity in federal regulations that establish gas prices, short time frames for filing royalty reports, and inaccuracies in MMS's internal databases.
RecommendationsOur recommendations from this work are listed below with a Contact for more information. Status will change from "In process" to "Open," "Closed - implemented," or "Closed - not implemented" based on our follow up work.
Director: Team: Phone:GAO-09-549, Mineral Revenues: MMS Could Do More to Improve the Accuracy of Key Data Used to Collect and Verify Oil and Gas Royalties
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Report to Congressional Requesters:
United States Government Accountability Office:
GAO:
July 2009:
Mineral Revenues:
MMS Could Do More to Improve the Accuracy of Key Data Used to Collect
and Verify Oil and Gas Royalties:
GAO-09-549:
GAO Highlights:
Highlights of GAO-09-549, a report to congressional requesters.
Why GAO Did This Study:
In fiscal year 2008, the Department of Interior‘s Minerals Management
Service (MMS) collected over $12 billion in royalties from oil and gas
production from federal lands and waters. Companies that produce this
oil and gas self-report to MMS data on the amount of oil and gas they
produced and sold, the value of this production, and the amount of
royalties owed. Since 2004, GAO has noted systemic problems with these
data and recommended improvements. GAO is providing: (1) a descriptive
update on MMS‘s key efforts to improve the accuracy of oil and gas
royalty data; (2) our assessment of the completeness and reasonableness
of fiscal years 2006 and 2007 oil and gas royalty data”the latest data
available; and (3) factors identified by oil and gas companies that
affect their ability to accurately report royalties owed to the federal
government.
What GAO Found:
MMS has several key efforts underway to improve the accuracy of the
payor-reported data used to collect and verify royalties, but it is too
soon to evaluate their effectiveness. MMS is in the process of
implementing (1) GAO‘s past recommendations to help identify missing
royalty reports and monitor payors‘ changes to royalty data; (2)
recommendations from the Royalty Policy Committee––a group empaneled by
the Secretary of the Interior to provide advice on managing federal and
Indian leases and revenues––to improve edit checks, monitor the quality
of natural gas, revise gas valuation regulations, and improve
coordination with BLM; and (3) other efforts on adding specific edits
for sales prices and identifying discrepancies in volumes between
operators and payors.
While much of the royalty data we examined from fiscal years 2006 and
2007 are reasonable, we found significant instances where data were
missing or appeared erroneous. For example, we examined gas leases in
the Gulf of Mexico and found that, about 5.5 percent of the time, lease
operators reported production, but royalty payors did not submit the
corresponding royalty reports, potentially resulting in $117 million in
uncollected royalties. We also found that a small percentage of royalty
payors reported negative royalty values, which cannot happen,
potentially costing $41 million in uncollected royalties. In addition,
payors claimed processing allowances 2.3 percent of the time for
unprocessed gas, potentially resulting in $2 million in uncollected
royalties. Furthermore, we found significant instances where payor-
provided data on royalties paid and the volume and/or the value of the
oil and gas produced appeared erroneous because they were outside of
expected ranges.
Oil and gas company representatives reported that several factors
affect their ability to accurately report royalties, including complex
land ownership, administratively combining leases into units, ambiguity
in federal regulations that establish gas prices, short time frames for
filing royalty reports, and inaccuracies in MMS‘s internal databases.
Figure: Production Facilities on a Federal Lease in Colorado:
[REfer to PDF for image: photograph]
Source: GAO.
[End of figure]
What GAO Recommends:
To prevent erroneous data from being entered into MMS databases and to
check the quality of data already entered, GAO recommends that MMS
design (1) an edit check to prevent payors from submitting a claim for
processing allowances on gas that is not processed and (2) new edit
checks to examine the net effect of adjustments to certain key royalty
variables. To simplify auditing, GAO recommends that MMS royalty payors
submit data on unit agreements and reasons for changes to original data
submissions. In commenting on a draft of this report, Interior
generally agreed with our findings and recommendations.
View [hyperlink, http://www.gao.gov/products/GAO-09-549] or key
components. For more information, contact Frank Rusco, (202) 512-3841,
ruscof@gao.gov.
[End of section]
Contents:
Letter:
Background:
MMS Has Ongoing Efforts to Improve the Accuracy of Payor-Reported
Royalty Data, but It Is Too Early to Assess the Effectiveness of These
Efforts:
In Several Instances, Data Used to Collect and Verify Royalties Are
Either Missing or Appear to Be Erroneous:
Multiple Factors Affect Oil and Gas Companies' Abilities to Accurately
Report Royalties Owed to the Federal Government:
Conclusions:
Recommendations for Executive Action:
Agency Comments and Our Evaluation:
Appendix I: Scope and Methodology:
Appendix II: Comments from the Department of the Interior:
Appendix III: GAO Contact and Staff Acknowledgments:
Tables:
Table 1: GAO Analysis of Key Royalty Variables, MMS's Oil and Gas
Royalty Data Exclusive of Royalty-in-Kind Transactions, Fiscal Years
2006 and 2007:
Table 2: Royalty Rate Calculations Outside of Expected Ranges for
Federal Oil and Gas Leases, Fiscal Years 2006 and 2007:
Figures:
Figure 1: MMS's Processes for Submitting, Checking, and Accepting
Royalty Data:
Figure 2: Percentage of Gas Production Reports without Corresponding
Royalty Reports in the Offshore Gulf of Mexico for Fiscal Years 2006
and 2007:
Figure 3: Range of Reasonable Oil Prices in the Offshore Gulf of Mexico
Based on Highest and Lowest Daily Spot Prices for Each Month:
Figure 4: Sales Prices for Oil from Federal Leases in the Offshore Gulf
of Mexico That Appear Erroneous, Fiscal Years 2006 and 2007:
Figure 5: Range of Reasonable Gas Prices in the Gulf of Mexico Based on
Highest and Lowest Daily Spot Prices for Each Month and the First of
the Month Price at the Henry Hub:
Figure 6: Sales Prices for Gas from Federal Leases in the Offshore Gulf
of Mexico That Appear Erroneous, Fiscal Years 2006 and 2007:
Figure 7: Block Diagram Illustrating the Hypothetical Creation of a
Federal Unit:
Figure 8: Block Diagram Illustrating a Hypothetical Complex
Relationship between Unit Agreements and Potential Impacts on
Oversight:
Figure 9: Numbers of Oil and Gas Royalty Records and Leases Reported
per Month for Fiscal Years 2006 and 2007:
Abbreviations:
API: American Petroleum Institute:
BLM: Bureau of Land Management:
Btu: British Thermal Unit:
CPT: Compliance Program Tool:
EDI: Electronic Data Interchange:
FERC: Federal Energy Regulatory Commission:
IG: Inspector General:
IPAMS: Independent Petroleum Association of Mountain States:
IRS: Internal Revenue Service:
LLS: Light Louisiana Sweet:
MMBtu: millions of British Thermal Units:
MMS: Minerals Management Service:
OGOR: Oil and Gas Operations Report:
PCC: Production Coordination Committee:
RIK: Royalty In Kind:
RPC: Royalty Policy Committee:
TIMS: Technical Information Management System:
[End of section]
United States Government Accountability Office:
Washington, DC 20548:
July 15, 2009:
The Honorable Jeff Bingaman:
Chairman:
Committee on Energy and Natural Resources:
United States Senate:
The Honorable Nick J. Rahall, II:
Chairman:
Committee on Natural Resources:
House of Representatives:
The Honorable Darrell Issa:
Ranking Member:
Committee on Oversight and Government Reform:
House of Representatives:
The Honorable Carolyn Maloney:
House of Representatives:
Royalties for oil and natural gas produced from federal lands and
waters are one of the country's largest non-tax sources of revenue,
accounting for over $12 billion in collections during fiscal year 2008.
The Department of the Interior's Minerals Management Service (MMS) is
responsible for collecting royalties from companies that produce oil
and gas from almost 29,000 federal and Indian leases. Each month, these
oil and gas companies self-report to MMS data on the amount of oil and
gas they produced and sold, the value of this production, and the
amount of royalties owed the federal government. Over the past 5 years,
GAO has found problems with these data. These problems include missing
data, errors in the self-reported amounts of oil and gas produced, self-
reported oil and gas sales value data that, given the reported volumes
of oil and gas sold, appear at odds with prevailing market prices for
oil and gas, and a lack of controls over changes to the data that
companies report. Although data accuracy was not the focus of our
previous work, we recommended that MMS correct some of these data.
Building on our prior work examining MMS's royalty data, we are
providing (1) a descriptive update of MMS's ongoing efforts to improve
the accuracy of oil and gas royalty data, (2) our assessment of the
completeness and reasonableness of fiscal years 2006 and 2007 oil and
gas royalty data, and (3) factors identified by oil and gas companies
that affect the ability of these oil and gas companies to accurately
report royalties owed to the federal government. We are addressing only
cash royalty payments; we have a separate engagement underway
addressing issues related to MMS's Royalty-in-Kind Program--an option
whereby MMS takes a share of oil and gas produced on federal lands and
waters in lieu of cash royalty payments.
To describe MMS's efforts to improve the accuracy of royalty data, we
reviewed and discussed with MMS officials their action plans to
implement recommendations made by GAO and Interior's Royalty Policy
Committee, reviewed a demonstration of MMS's Compliance Program Tool
(CPT)--an automated system that analyzes royalty payments--and
discussed with MMS officials their implementation of the CPT to
systemically identify misreported volumes and missing royalty reports.
We made no attempt to evaluate the effectiveness of MMS's ongoing
efforts to improve the accuracy of royalty data because these efforts
are not fully implemented.
To assess the completeness and reasonableness of fiscal years 2006 and
2007 oil and gas royalty data, we first analyzed MMS's existing edit
checks and plans for modifying or adding new edit checks. In our
subsequent analyses, we replicated several of MMS's edit checks but
used a different method. While MMS evaluates each royalty record
individually, we combined all royalty records submitted by a given
payor for each month, product type, and lease, thereby examining the
cumulative effect of changes to original royalty data. We then used our
methodology to evaluate 4.1 million royalty records for fiscal years
2006 and 2007 based on extensive data reliability work conducted on two
previous assignments. In doing so, we developed a risk-based approach
to identify and review key aspects of data collection, processing, and
reporting, and reviewed the extent to which MMS's royalty collection
system fills those needs. We also reviewed reports and testimonies on
oil and gas royalties to understand the historical problems associated
with the royalty collection process, and we interviewed key MMS staff
and state and tribal auditors that work on federal oil and gas leases
to identify any continuing concerns with MMS's royalty reporting
process.
To examine factors that oil and gas companies identified as limiting
their ability to accurately report royalties owed to the federal
government, we interviewed a non-random sample of oil and gas company
representatives from the 15 companies that report to MMS the highest
amount of royalty data and from the two largest national oil and gas
industry associations. The 10 companies that responded to our request
for information represent the major companies, large independent
companies, mid-size independent companies, and small independent
companies. We chose to interview a non-random sample because we lack
the authority to compel private companies to participate in such
interviews and because we deemed the cost of trying to convince a large
enough sample to participate to make the results statistically relevant
to be greater than the benefits of being able to make inferences from
the sample interviews. As a result, our results for this objective
should not be viewed as a comprehensive list of reporting difficulties
or an evaluative assessment of the validity of all the elements of the
list. A detailed description of our scope and methodology appears in
appendix I.
We conducted this work from July 2008 to April 2009 in accordance with
generally accepted government auditing standards. Those standards
require that we plan and perform the audit to obtain sufficient,
appropriate evidence to provide a reasonable basis for our findings and
conclusions based on our audit objectives. We believe that the evidence
obtained provides a reasonable basis for our findings and conclusions
based on our audit objectives.
Background:
Companies that develop and produce oil and gas resources do so under
leases obtained from and administered by the Department of the
Interior. Interior's Bureau of Land Management (BLM) manages onshore
leases, and Interior's MMS manages offshore leases. MMS is responsible
for collecting the royalties on all federal and many Indian oil and gas
leases. Royalties on producing leases are a percentage of the value of
the production sold less deductions known as allowances.[Footnote 1]
Together, BLM and MMS are responsible for ensuring that oil and gas
companies comply with applicable laws, regulations, and policies for
more than 29,000 producing federal and Indian leases, which account for
about 23 percent of domestically produced gas and 26 percent of
domestically produced oil.
In some cases, several companies form partnerships to explore and
develop oil and gas leases, thereby sharing the risk, the costs, and
the benefits. These companies often elect from among themselves a
single company, called the operator, to manage the physical drilling of
wells and the installation of production equipment. Operators report
monthly to MMS on the Oil and Gas Operations Report (OGOR) the amount
of oil and gas produced from each well on each lease. In addition, all
the companies that share the proceeds from the sale of oil and gas from
federal lands and waters are required each month to report to MMS on
the Form MMS-2014 data about the oil and gas they sold. MMS refers to
these companies, including the operator, as royalty payors. The data on
each Form MMS-2014 are then stored in MMS's system as a number of
records, each of which consists of many variables, such as the name of
the payor, the lease number, the amount of oil and gas sold (sales
volume), the value of this oil and gas (sales value), allowable
deductions for transportation and processing, and the amount of
royalties owed (royalty value). Payors can legally adjust these data
they report for up to 6 years if, for example, they learn that the data
they submitted were incorrect.[Footnote 2] Almost all payors submit
these data electronically.
Within its 5-year business plan for fiscal years 2008 to 2012, MMS has
set an objective of ensuring timely and more accurate mineral revenue
reporting and payment.[Footnote 3] According to Interior's 2009 Budget
Justification, MMS set goals in fiscal years 2008 and 2009 of ensuring
that companies report 98 percent of their data accurately the first
time, up from actual percentages of 97.4 in fiscal year 2006 and 97.3
in fiscal year 2007, and compared to an actual percentage of 98.3 as
reported by MMS for fiscal year 2008. While we could not find a
business entity that performed identical services to those of MMS for
comparing its accuracy of electronic transactions, we chose the
Internal Revenue Service (IRS) for comparison because of the potential
difficulty in interpreting complex tax regulations, determining
allowable deductions, and calculating taxes owed. To this end, IRS
reported in January 2008 that its electronic tax filers have a 99
percent accuracy rate--only slightly higher than the rates reported by
MMS. To help improve data accuracy, MMS subjects payor-reported royalty
data to over 140 edit checks. Specifically, MMS has incorporated
certain up-front edit-checks in its data acceptance tools that help
detect and reject erroneous payor-reported royalty data before MMS's
data systems will accept them. MMS also incorporates a second level of
edit checks that review payor-reported data for additional errors after
data are accepted. Edit checks must comply with GAO standards for
internal controls in the federal government as required by 31 U.S.C. §
3512(c) and (d), commonly referred to as the Federal Managers'
Financial Integrity Act of 1982. These standards identify and address
major performance challenges and areas at greatest risk for fraud,
waste, abuse, and mismanagement. Furthermore, the standards state that
automated edits and checks should help control the accuracy and
completion of transaction processing.
Given the large amount of royalty revenues at stake and problems with
royalty management identified by past GAO, Interior Inspector General,
and other reports, MMS's processes for ensuring the accurate collection
of royalties have been the subject of continuing scrutiny. For example,
in 2003 while examining MMS's Royalty-in-Kind program, we found that
from 1.9 percent to 3.3 percent of the data that we examined for oil
leases in Wyoming and the Gulf of Mexico were erroneous or missing, and
that 6 percent of the data that we examined for gas leases in the Gulf
of Mexico were anomalous, meaning that data values fell outside of
expected ranges.[Footnote 4] Similarly in 2004, we found that 40
percent of the royalty data that we examined for 10 geothermal projects
was either missing or erroneous.[Footnote 5] In 2006, we examined the
relationship between the increases in oil and gas prices from 2000 to
2005 and the amount of royalties collected during that time and found
that 8.5 percent of the data appeared anomalous.[Footnote 6] In 2008,
we reported that MMS's royalty management system lacked several
capabilities that would provide greater assurance that royalties are
collected accurately.[Footnote 7] These capabilities include readily
identifying changes that companies make to previously entered data,
detecting the absence of royalty reports, and implementing a process
for collecting the proper amount of royalties when MMS identifies that
oil and gas volumes have been incorrectly reported. Among other things,
we recommended MMS identify when royalty reports have not been filed as
required and when companies make changes to data provided to MMS after
the statutory limitation on such changes. We also reported that MMS was
taking steps to address these deficiencies.
In addition to GAO's work, Interior's Inspector General (IG) analyzed
MMS's auditing and compliance process and made several recommendations
in 2007 to improve these functions and the systems that track them.
Also, the Royalty Policy Committee (RPC)--a group empaneled by the
Secretary of the Interior and charged with providing advice on managing
federal and Indian leases and revenues--has identified numerous
deficiencies. In December 2007, the RPC issued a report that included
more than 100 recommendations to strengthen Interior's royalty
collections by improving BLM's and MMS's verification of production
volumes, improving many areas of MMS's audit and compliance efforts by
establishing a compliance strategy counsel, improving coordination
between MMS and BLM, and improving MMS's computer system.
MMS Has Ongoing Efforts to Improve the Accuracy of Payor-Reported
Royalty Data, but It Is Too Early to Assess the Effectiveness of These
Efforts:
MMS has three major efforts underway to improve the accuracy of payor-
reported royalty data used to collect and verify royalties, but it is
too early to evaluate the effectiveness of these efforts. First, MMS is
beginning to address GAO's recommendations concerning the
identification of missing royalty reports and the monitoring of
adjustments that companies make to their royalty data.[Footnote 8]
Second, MMS is implementing RPC recommendations concerning edit checks,
valuation regulations for natural gas, and coordination with BLM.
Third, MMS is continuing to develop processes to increase the accuracy
of royalty reporting data by improving edit checks on oil and gas sales
prices and using the CPT to identify errors in the amount of oil and
gas reportedly sold by payors.
MMS Is Beginning to Address GAO's Recommendations, but It Is Too Early
to Assess the Effectiveness of These Actions:
To address a past GAO recommendation, MMS is developing a process to
automatically detect within 6 months those cases in which a company has
not filed a royalty report when it has filed a production report. MMS
officials explained that 6 months is a reasonable timeframe, and that
companies make most corrections to missing or incorrect royalty data
within this time frame. Under the current royalty reporting system,
cases in which a company has not filed a royalty report may not be
detected until more than 2 years after the initial reporting date, when
MMS personnel in their compliance group begin to target leases for a
review or audit. According to MMS officials, personnel in the financial
management group are beginning to identify missing royalty reports by
identifying instances in which the royalty report--the Form MMS-2014--
is absent when a production report--the OGOR--was filed by the
operator. With few exceptions, MMS should receive corresponding royalty
reports for each production report it receives. MMS has additional
checks in place through its CPT for determining when both the OGOR and
the Form MMS-2014 are missing.
Also in response to a GAO recommendation, MMS is developing an
automated process to identify changes that royalty payors make to their
previously entered royalty data that exceed the 6-year statutory limit
on such adjustments or that occur after compliance work, including
audits, has been completed. Although these adjustments may change
payors' royalty payments, prior to this effort MMS's royalty reporting
system could not monitor them and payors could continue to adjust their
previously reported royalty data without prior MMS approval or review.
In addition, companies could change royalty data after an audit has
been completed, and MMS needs to be able to identify when this occurs,
as we have suggested in our previous work. While adjustments may occur
for legitimate reasons, and identifying them will not prevent them from
occurring, it could facilitate later scrutiny and follow up with
company officials. However, it is too early to evaluate the
effectiveness of these actions.
MMS Has Developed Plans to Address RPC Recommendations, but More
Progress Is Needed before Results Can Be Evaluated:
MMS is implementing action plans to address royalty reporting issues
raised by the 2007 RPC Report. The following actions directly relate to
four recommendations for improving the accuracy of the royalty
reporting process out of over 100 recommendations identified by the
RPC. First, MMS is in the process of using its existing edit checks and
adding additional edit checks to examine more data before the data are
entered into its database, instead of examining data that have already
been accepted and stored. Specifically, this change will affect royalty
data that payors submit through the electronic reporting interface--a
Web site-based portal through which MMS accepts almost 30 percent of
its data. According to MMS officials, the other 70 percent of royalty
records are accepted through the Electronic Data Interchange (EDI)--a
standardized method of transferring data electronically between
computer systems, such as a payor's system and MMS's system. Currently,
there are some edit checks built into the EDI software, but MMS's goal,
as outlined in its strategic business plan for 2008-2012, is to require
EDI reporters to implement most edits on their individual computer
systems before they submit the data through EDI. If they do not, then
payors must use MMS's other system for submitting data--the electronic
reporting interface--which accepts fewer royalty records at a time, but
already has these up-front edit checks built into its system. As GAO
has noted in prior reports, edit checks that prevent potentially
erroneous data from entering the databases offer advantages over
efforts to continually clean up erroneous data allowed into the system.
However, it is too early to tell how useful these specific efforts will
be. MMS's processes for checking data are outlined in figure 1.
Figure 1: MMS's Processes for Submitting, Checking, and Accepting
Royalty Data:
[Refer to PDF for image: illustration]
Data submission:
* MMS specified edit checks integrated into company information
systems.
* Company information systems: feeds Electronic data interchange.
* Electronic reporting interface.
Data acceptance:
* Electronic data interchange continues.
* MMS edit checks:
- If data pass, data allowed into MMS database;
- If data fail key edit checks, data are rejected.
Data used for operations:
* MMS information systems – royalty database.
* Additional MMS edit checks on database and research to correct
errors.
Source: GAO.
Note: Not all data are submitted electronically. Less than 1 percent is
submitted in paper format and are keypunched and loaded into the
database, where they are subjected to edit checks. All data submitted
through the electronic reporting interface that fail edit checks are
not rejected. Some data with errors that MMS considers less important
are accepted by the database.
[End of figure]
Second, MMS is working on a problem identified by the RPC concerning
the accuracy of reporting natural gas royalties. The RPC recommended
that MMS add a data field on the Form MMS-2014 that identifies the heat
content per cubic foot of natural gas, which is important in
determining the amount of royalties owed. State and tribal royalty
auditors with whom we spoke also identified the need to check on the
heat content of natural gas. In response to the RPC recommendation, MMS
officials said that they developed and recently implemented an
alternate plan for evaluating the information identified by the RPC
using data already collected on the Form MMS-2014 and maintained in its
databases. In particular, payors report to MMS the quantity of natural
gas sold (in thousands of cubic feet) as well as the total heating
value of all the gas sold (in millions of Btus, an industry standard
for selling natural gas). MMS officials told us they plan to calculate
the heating value per cubic foot from these existing data fields, by
dividing the total heating value by the quantity sold, and implement an
edit check on the reasonableness of the results of this calculation.
[Footnote 9] Moreover, MMS officials said that it was too costly to
change the structure of its database to accommodate a new data field
and modify how data are collected. We believe that MMS's alternative is
a reasonable approach and that it is likely to identify errors in
reported gas volumes.
Third, MMS is planning to publish proposed revisions to its gas
valuation regulations and guidelines that they believe will address
several problems. For example, MMS regulations provide a series of
benchmarks for companies to use in establishing the price of natural
gas when they sell it to their affiliates. However, according to the
RPC and state auditors, these benchmarks are difficult to apply and do
not reflect how gas is currently sold so they recommend that MMS should
replace these benchmarks with widely published market indexes. Another
problem that MMS intends to address with its new gas valuation
regulations relates to how companies can take deductions from gas
revenues. According to MMS regulations, the costs for transportation
and processing must be properly allocated among the individual products
that result from the processing of gas. However, gas purchasers can
"bundle" all of these charges together, making it difficult for the
payor to determine how to allocate these deductions and then to
calculate what is actually owed in royalties. While MMS has plans to
address these and other issues with its new regulations, they were
unable to give us sufficient details about how this would be done for
us to evaluate the effectiveness of the new regulations. MMS has a
target date for completion of the new proposed regulations of December
2009.
Fourth, in response to RPC recommendations that MMS improve its
interagency coordination with BLM, MMS has taken a first step to
improve coordination. Specifically, the RPC recommended that the
Department of the Interior establish a Production Coordination
Committee (PCC) that is charged with, among others things, defining and
coordinating common processes, defining common data standards, and
addressing technical issues for information sharing between the two
agencies. To begin this process, MMS, BLM, and the Bureau of Indian
Affairs held a 3-day PCC meeting in September 2008, during which a
number of key issues regarding the accuracy of royalty data were
discussed, including (1) placing more responsibility on industry to
provide clean data to MMS; (2) resolving invalid lease numbers; (3)
sharing information on rents, agreements, and Indian leases in a more
timely manner; and (4) providing notices to MMS when wells first start
to produce. This meeting was a first step in improving inter-agency
coordination, but it is too early to judge the effectiveness of the
committee. MMS officials said that additional meetings are planned on a
recurring basis.
MMS Has Other Efforts Underway to Improve the Quality of Payor-Reported
Royalty Data, but Their Preliminary Nature Precludes Assessing Their
Effectiveness:
MMS officials told us they are evaluating a process to incorporate more
detailed market prices into its system to compare sales prices that MMS
calculates from payor-reported royalty data to relevant market prices.
MMS does not require payors to report their sales prices but can
calculate an implicit sales price by dividing the total value of the
oil or gas that payors report (sales value) by the volume that payors
report as having sold (sales volume). Currently, MMS uses for
comparison a few oil and gas prices with a wide range of values for all
leases regardless of where the lease is located or the quality of oil
that is produced. MMS officials told us that they intend to incorporate
a more detailed price table into its royalty reporting system by 2010
that will include more specific sales prices related to geographic
areas and specific sales months. We believe that this could be a
significant improvement, but it remains too early to assess MMS's
efforts.
In addition, during the course of our work, MMS officials told us they
plan to expand the implementation of two edit checks. First, MMS plans
to expand the use of an edit check that will calculate the royalty rate
from payor-reported data and compare this with the royalty rate
specified in each lease. As with sales prices, MMS does not require
payors to report royalty rates but can calculate implicit royalty rates
from payor-reported data. MMS can calculate implicit royalty rates by
dividing the amount of royalties that payors report (royalty value) by
the total value of the oil or gas that payors report (sales value).
While MMS has checked royalty rates on Indian leases and prevented
erroneous data on these leases from entering its system since prior to
2001, MMS's checking of royalty rates has not prevented erroneous data
on federal leases from entering its system. However, MMS plans to
resolve this issue on federal leases by the end of fiscal year 2009.
Second, MMS recently began using an edit check that ensures payors take
processing allowances only on gas that is processed. MMS reported that
in April 2009 it implemented such an edit check in its electronic
reporting interface. This action will affect about 30 percent of data
entering MMS's system, but will not impact potentially erroneous data
that companies submit through the EDI. We believe that expanding the
use of both of these edit checks can improve MMS's ability to evaluate
self-reported royalty data, but we will be unable to evaluate the
effectiveness of these new processes until they are fully implemented.
In 2008, MMS auditors in its compliance group began to use the CPT to
identify discrepancies--based on certain thresholds--between the
volumes of oil and gas produced that lease operators reported on the
OGOR and the total volumes sold that payors reported on the Form MMS-
2014.[Footnote 10] When conducting this process, MMS also is able to
identify instances when a royalty payor fails to submit the required
Form MMS-2014. However until recently, these comparisons are not done
until over 2 years after royalty data have been submitted when MMS
begins to select leases for audit. While this volumetric comparison had
been done much sooner and routinely for all leases in the past, the
process was dropped when MMS implemented its current information system
in 2001 because the new module that was to perform this function was
not yet ready for implementation and because MMS wanted to expand the
comparison to include an examination of the amount of royalties paid
and the value of the oil and gas sold. MMS officials explained that
under the old system, potential mismatches between OGOR and 2014
volumes often involved errors in the royalties paid and/or the value of
the oil and gas sold, and it was important to look at all three of
these components at once. They further explained that the new module
was never implemented but instead was replaced with an expanded use of
the CPT, albeit at a much later date than initially anticipated. MMS
reported that in January 2009, it began using the CPT to compare
volumes and examine the amount of royalties paid and the value of the
oil and gas sold within 6 to 9 months after payors submit data.
Moreover, in 1992 when we last examined the comparison of volumes on
the OGOR with volumes on the Form MMS-2014, we determined that it was
cost effective to follow up on at least the largest of the
discrepancies and support MMS doing this within an earlier time frame,
such as 6 months after receiving royalty data.
In Several Instances, Data Used to Collect and Verify Royalties Are
Either Missing or Appear to Be Erroneous:
While much of the royalty data we examined from fiscal years 2006 and
2007 appears reasonable, we found several instances where key data were
missing or appear to be erroneous. For example, our close examination
of producing gas leases in the Gulf of Mexico indicated that up to 5.5
percent of the time, royalty reports were missing for these leases. We
also found that from about 2 to 7.4 percent of the time, depending on
the group of leases we examined, either the amount of royalties that
payors report due (royalty value) and/or the total value of the oil and
gas that payors report (sales value) appeared erroneous. In addition,
3.9 percent of sales values and/or the volume that payors report as
having sold (sales volume) from offshore oil leases in the Gulf of
Mexico appeared erroneous while about 6.6 percent of one or both of
these data elements appeared erroneous for offshore gas leases in the
Gulf of Mexico.
Checks for Completeness of Payor-Reported Royalty Data Indicate That
Certain Data Are Missing:
Our detailed examination of producing gas leases in the Gulf of Mexico
indicated that 5.5 percent of royalty reports were missing. Using
production reports filed by lease operators, we identified all leases
producing gas in the Gulf from January 2006 through September
2007.[Footnote 11] For each month in which operators reported gas
production, we checked MMS's monthly royalty reports to ensure that
payors reported sales of gas.[Footnote 12] We found that about 5.5
percent of the time that operators reported monthly gas production from
leases, payors did not submit the corresponding monthly royalty report.
The missing royalty reports for this production represent potentially
about $117 million in royalties that may not have been collected.
[Footnote 13] However, it is possible that instead of reporting
royalties on the appropriate reports, payors may have misreported these
royalties on reports for other leases, and as such, additional
royalties would not be due. We also observed instances in which the
total gas production on the royalty reports was substantially less than
that on the production reports, possibly indicating that one of
multiple payors on that lease may not have submitted a royalty report
for that month. While a significant number of the almost 1,500 leases
in our sample had royalty reports but no production reports, missing
production reports were more prevalent for the last 3 months of fiscal
year 2007, possibly indicating that these reports had not yet been
received or accepted by MMS's system. Missing royalty reports are
illustrated in figure 2.
Figure 2: Percentage of Gas Production Reports without Corresponding
Royalty Reports in the Offshore Gulf of Mexico for Fiscal Years 2006
and 2007:
[Refer to PDF for image: vertical bar graph]
Date: January 2006;
Percentage of reports: 4.77%.
Date: February 2006;
Percentage of reports: 4.67%.
Date: March 2006;
Percentage of reports: 6.02%.
Date: April 2006;
Percentage of reports: 6.14%.
Date: May 2006;
Percentage of reports: 6.60%.
Date: June 2006;
Percentage of reports: 6.42%.
Date: July 2006;
Percentage of reports: 4.13%.
Date: August 2006;
Percentage of reports: 5.45%.
Date: September 2006;
Percentage of reports: 5.26%.
Date: October 2006;
Percentage of reports: 5.28%.
Date: November 2006;
Percentage of reports: 4.72%.
Date: December 2006;
Percentage of reports: 4.57%.
Date: January 2007;
Percentage of reports: 5.29%.
Date: February 2007;
Percentage of reports: 5.70%.
Date: March 2007;
Percentage of reports: 6.07%.
Date: April 2007;
Percentage of reports: 6.01%.
Date: May 2007;
Percentage of reports: 6.02%.
Date: June 2007;
Percentage of reports: 6.07%.
Date: July 2007;
Percentage of reports: 6.69%.
Date: August 2007;
Percentage of reports: 4.94%.
Date: September 2007;
Percentage of reports: 5.43%.
Source: GAO analysis of MMS data.
[End of figure]
Checks for Reasonableness of Payor-Reported Royalty Data Indicate
Errors in Transportation and Processing Allowances:
We evaluated all royalty data for fiscal years 2006 and 2007--excluding
royalty-in-kind leases--for obvious errors in key reported royalty
variables, including volumes of oil and gas sold, the value of this oil
and gas, and royalties paid, and found that the error rate for these
variables ranged from 0 percent to about 2.3 percent, with the highest
levels of errors being found in transportation and processing
allowances. This analysis is summarized in table 1, along with
subsequent analyses discussed below. We used a different method than
MMS's edit checks to evaluate the reasonableness of royalty data. For
example, MMS's edit checks generally evaluate each royalty record
individually, and a royalty payor may submit multiple records for a
given lease each month, including the original royalty report and often
times multiple corrections to the volumes sold or the royalties paid.
However, we combined all royalty records associated with a given payor
for each month, product type, and lease. Unlike MMS's edit checks of
individual royalty records, our methodology is able to detect if
adjustments exceed the amount of the original entries. For example, in
checking the sum of the sales values, sum of sales volumes, and sum of
royalty values that payors submitted for a given month, product type,
and lease, we found that over 99.8 percent of the time these sums were
positive, as one would expect when payors owe royalties.[Footnote 14]
However, payors submit one payment per month for all their federal
leases; therefore a negative royalty value for an individual lease may
go undetected if it is small in comparison to the sum of the royalty
values for all their other leases. Although the 0.2 percent of royalty
values that we found to be negative is a small percentage, collectively
this represented about $41 million in royalties that may not be
collected if these instances are not detected in future compliance work
or audits. Further, a check for positive royalty values is not a
precise measure of accuracy. Rather, it is a gross check of
reasonableness and some positive royalty rates, which we did not
evaluate, could have been lower than they were supposed to be.
We found that transportation allowances and processing allowances,
which should always be negative values in the database, were positive
1.73 percent and 0.77 percent of the time, respectively. We also found
that about 2.3 percent of claimed processing allowances were incorrect.
These processing allowances were associated with either unprocessed
gas, which by definition is not entitled to a processing allowance, or
coalbed methane, which is never processed, and therefore should not
receive an allowance. Claiming processing allowances for gas that was
not processed could result in MMS collecting about $2 million less in
royalties than are due for the fiscal year 2006 and 2007 leases that we
examined. However, the gas reported as unprocessed gas could be
processed gas that was improperly reported as unprocessed gas by the
payors, and hence, no additional royalties would be due. Either way,
there are reporting errors that raise questions about the accuracy of
royalty collections. In addition, we checked that transportation and
processing allowances did not exceed regulatory limits and found that
they were within limits nearly 100 percent of the time. Lastly, we
checked and verified that payors did not report sales volumes when
reporting transportation and processing allowances separately from
royalty amounts. This is not permitted because the reporting of sales
volumes in this situation would lead to reporting the volumes sold
twice. Table 1 summarizes the types of errors for which we checked and
the percent of times they occurred.
Table 1: GAO Analysis of Key Royalty Variables, MMS's Oil and Gas
Royalty Data Exclusive of Royalty-in-Kind Transactions, Fiscal Years
2006 and 2007:
Definition of possible error associated with key royalty variables:
Reporting sales volume when reporting allowances separately from
royalties due;
Percent error rate found: 0.
Definition of possible error associated with key royalty variables:
Exceeding the regulatory limit for processing allowances[A];
Percent error rate found: 0.02.
Definition of possible error associated with key royalty variables:
Exceeding the regulatory limit for transportation allowances[A];
Percent error rate found: 0.06.
Definition of possible error associated with key royalty variables:
Reporting negative sales volume;
Percent error rate found: 0.12.
Definition of possible error associated with key royalty variables:
Reporting negative sales values;
Percent error rate found: 0.20.
Definition of possible error associated with key royalty variables:
Reporting negative royalty values;
Percent error rate found: 0.20.
Definition of possible error associated with key royalty variables:
Reporting positive processing allowances;
Percent error rate found: 0.77.
Definition of possible error associated with key royalty variables:
Reporting positive transportation allowances;
Percent error rate found: 1.73.
Definition of possible error associated with key royalty variables:
Claiming processing allowance for unprocessed gas or coalbed methane;
Percent error rate found: 2.29.
Source: GAO analysis of MMS data.
[A] Payors can exceed the regulatory limit with prior approval from
MMS.
[End of table]
Significant Amounts of Payor-Reported Data Appear Erroneous as
Indicated by Implicit Royalty Rates:
We found that, of the key royalty variables self-reported by royalty
payors, either the royalties owed, the value of the oil or gas sold, or
both, appeared erroneous from 2 to 7.4 percent of the time, depending
on the group of leases that we examined. MMS's royalty system does not
require payors to report royalty rates but rather the amount of their
royalty payment--royalty value--and the total amount they received for
the sale of oil or gas from each federal lease--sales value. We
calculated an implicit royalty rate by dividing royalty value by sales
value and compared this number to royalty rates generally specified in
federal leases. Because payors are not required to report the royalty
rate that applies to each individual lease and data were not readily
available to us, it was time prohibitive to individually compare each
calculation to the royalty rate specified in the lease. Instead, we
compared the calculated rates to general lease terms, allowing for
significant but common departures from these terms.
We found that either royalty values or sales values, or both, were
erroneous about 2.2 percent of the time for offshore oil leases and
about 2 percent of the time for offshore gas leases when we calculated
implicit royalty rates with fiscal year 2006 and 2007 data. We compared
our implicit royalty rates with standard offshore lease terms of either
12.5 percent or 16.67 percent, allowing for some rounding error in
these rates. Our analysis did not identify as erroneous those instances
when the calculated royalty rate was 12.5 percent, but the lease
royalty rate was actually 16.67 percent, or vice versa. We also
compared leases for which the calculated implicit royalty rates were
other than 12.5 or 16.67 percent to actual royalty rates as specified
in the federal lease and adjusted our analysis for those few times when
these calculated, but apparently erroneous royalty rates, were
legitimate. As such, a royalty rate that is different from general
lease terms means that either the payor-reported royalty value or the
sales value is erroneous. MMS acknowledged that erroneous royalty rates
could result from payors misreporting the sales value or the royalty
value owed to the federal government.
We found that either royalty values, sales values, or both, appeared
erroneous about 7.4 percent of the time for onshore oil leases and
about 4.8 percent of the time for onshore gas leases when we calculated
implicit royalty rates with fiscal year 2006 and 2007 data.[Footnote
15] We compared our implicit royalty rates with standard onshore oil
and gas lease terms of either 12.5 percent or a variable royalty rate
schedule that depended on production volumes for certain leases issued
before 1988. These variable rates ranged from 12.5 percent to 25
percent for oil production and were either 12.5 percent or 16.67
percent for gas production. We also assumed royalty rates of 5 and 10
percent as being correct because MMS indicated that these were common
royalty rates on certain older leases, and we verified this by
examining a sample of leases. We excluded all oil leases prior to
February 2006 because royalty rates below 12.5 percent were in effect
during that time for low volume or heavy oil production. Our analysis
did not identify as erroneous those instances when the implicit royalty
rate matched standard royalty rates but was nevertheless incorrect. In
addition to misreporting royalty values or sales values, MMS said that
the higher percentage of apparently erroneous royalty data for onshore
oil leases may be due to royalty payors continuing to incorrectly pay
royalties under expired provisions for low volume or heavy oil.
Erroneous royalty rates are summarized in table 2.
Table 2: Royalty Rate Calculations Outside of Expected Ranges for
Federal Oil and Gas Leases, Fiscal Years 2006 and 2007:
Type of lease: Offshore oil;
Apparent error rate: 2.2%.
Type of lease: Offshore gas;
Apparent error rate: 2.0%.
Type of lease: Onshore oil;
Apparent error rate: 7.4%.
Type of lease: Onshore gas;
Apparent error rate: 4.8%.
Source: GAO analysis of MMS data.
[End of table]
Significant Amounts of Payor-Reported Data Appear Erroneous as
Indicated by Implicit Sales Prices in the Gulf of Mexico:
We found that either sales values or sales volumes appeared erroneous
about 3.9 to 6.6 percent of the time we used fiscal year 2006 and 2007
royalty data to calculate implicit sales prices in the offshore Gulf of
Mexico.[Footnote 16] MMS does not require payors to report oil and gas
sales prices (prices per unit sold) but instead requires payors to
report the total amount they received for the sale of oil or gas from a
federal lease--sales value--and the total volume of oil or gas that
they sold--sales volume. We calculated an implicit sales price per unit
by dividing sales value by sales volume and compared this number to
prevailing market prices at the time.[Footnote 17]
For offshore oil in the Gulf of Mexico, we found that our implicit
sales prices fell outside of a wide range of prevailing market prices
3.9 percent of the time during fiscal years 2006 and 2007. We used a
range of market prices each month for comparison, the low price being
the lowest daily spot price that month for Mars oil--a low quality, low
value oil produced in the offshore Gulf--and the high price being the
highest daily spot price for light Louisiana sweet (LLS)--a high
quality, high value oil. The average difference between these prices
was about $16 per barrel of oil during the October 2005 through
September 2007 period we evaluated. We believe that this is a
conservative approach because the two prices are among the lowest and
highest prices that we found in the Gulf of Mexico. Therefore, while
there may be cases in which prices fall outside of this range for
legitimate reasons, we would expect this to be a rare occurrence.
Conversely, prices that fall within this range are reasonable but not
necessarily correct. This price range is illustrated in figure 3.
Figure 3: Range of Reasonable Oil Prices in the Offshore Gulf of Mexico
Based on Highest and Lowest Daily Spot Prices for Each Month:
[Refer to PDF for image: multiple line graph]
Date: October 2005;
LLS spot price per barrel: $68;
Mars spot price per barrel: $53.
Date: November 2005;
LLS spot price per barrel: $63;
Mars spot price per barrel: $48.
Date: December 2005;
LLS spot price per barrel: $62;
Mars spot price per barrel: $49.
Date: January 2006;
LLS spot price per barrel: $69;
Mars spot price per barrel: $56.
Date: February 2006;
LLS spot price per barrel: $68;
Mars spot price per barrel: $49.
Date: March 2006;
LLS spot price per barrel: $69;
Mars spot price per barrel: $52.
Date: April 2006;
LLS spot price per barrel: $76;
Mars spot price per barrel: $59.
Date: May 2006;
LLS spot price per barrel: $77;
Mars spot price per barrel: $61.
Date: June 2006;
LLS spot price per barrel: $76;
Mars spot price per barrel: $61.
Date: July 2006;
LLS spot price per barrel: $80;
Mars spot price per barrel: $66.
Date: August 2006;
LLS spot price per barrel: $81;
Mars spot price per barrel: $61.
Date: September 2006;
LLS spot price per barrel: $71;
Mars spot price per barrel: $51.
Date: October 2006;
LLS spot price per barrel: $62;
Mars spot price per barrel: $49.
Date: November 2006;
LLS spot price per barrel: $67;
Mars spot price per barrel: $50.
Date: December 2006;
LLS spot price per barrel: $68;
Mars spot price per barrel: $52.
Date: January 2007;
LLS spot price per barrel: $61;
Mars spot price per barrel: $44.
Date: February 2007;
LLS spot price per barrel: $65;
Mars spot price per barrel: $51.
Date: March 2007;
LLS spot price per barrel: $73;
Mars spot price per barrel: $53.
Date: April 2007;
LLS spot price per barrel: $74;
Mars spot price per barrel: $59.
Date: May 2007;
LLS spot price per barrel: $73;
Mars spot price per barrel: $57.
Date: June 2007;
LLS spot price per barrel: $77;
Mars spot price per barrel: $61.
Date: July 2007;
LLS spot price per barrel: $82;
Mars spot price per barrel: $67.
Date: August 2007;
LLS spot price per barrel: $79;
Mars spot price per barrel: $63.
Date: September 2007;
LLS spot price per barrel: $85;
Mars spot price per barrel: $69.
Source: GAO analysis of MMS data.
[End of figure]
In addition to possible errors in reported sales values or sales
volumes, MMS officials said that low oil prices may reflect poor
marketing, sales of low quantities of poor quality oil that settle in
storage tanks, or sales of oil at offshore platforms where the sales
price may be discounted for transportation. MMS officials also said
that royalty payors may also be netting the cost of transportation from
their sales value, which is against MMS regulations. On the other hand,
high oil prices may reflect good marketing. Figure 4 depicts the
percentage of our calculated oil prices that appeared erroneous and
distinguishes between when the prices fell below or above the expected
range.
Figure 4: Sales Prices for Oil from Federal Leases in the Offshore Gulf
of Mexico That Appear Erroneous, Fiscal Years 2006 and 2007:
[Refer to PDF for image: stacked vertical bar graph]
Percentage appearing erroneous:
Date: October 2005;
Percentage below reasonable range: 2.19%;
Percentage above reasonable range: 0.66%.
Date: November 2005;
Percentage below reasonable range: 1.66%;
Percentage above reasonable range: 2.45%.
Date: December 2005;
Percentage below reasonable range: 2.37%;
Percentage above reasonable range: 0.9%.
Date: January 2006;
Percentage below reasonable range: 5.88%;
Percentage above reasonable range: 0.16%.
Date: February 2006;
Percentage below reasonable range: 1.44%;
Percentage above reasonable range: 0.64%.
Date: March 2006;
Percentage below reasonable range: 2.69%;
Percentage above reasonable range: 0.4%.
Date: April 2006;
Percentage below reasonable range: 3.86%;
Percentage above reasonable range: 0.36%.
Date: May 2006;
Percentage below reasonable range: 2.72%;
Percentage above reasonable range: 0.14%.
Date: June 2006;
Percentage below reasonable range: 2.21%;
Percentage above reasonable range: 0.43%.
Date: July 2006;
Percentage below reasonable range: 4.52%;
Percentage above reasonable range: 0.13%.
Date: August 2006;
Percentage below reasonable range: 1.72%;
Percentage above reasonable range: 0.
Date: September 2006;
Percentage below reasonable range: 0.9%;
Percentage above reasonable range: 6.03%.
Date: October 2006;
Percentage below reasonable range: 2.06%;
Percentage above reasonable range: 6.97%.
Date: November 2006;
Percentage below reasonable range: 2.75%;
Percentage above reasonable range: 0.59%.
Date: December 2006;
Percentage below reasonable range: 2.39%;
Percentage above reasonable range: 0.4%.
Date: January 2007;
Percentage below reasonable range: 1.58%;
Percentage above reasonable range: 7.05%.
Date: February 2007;
Percentage below reasonable range: 2.38%;
Percentage above reasonable range: 0.2%.
Date: March 2007;
Percentage below reasonable range: 2.8%;
Percentage above reasonable range: 0.06%.
Date: April 2007;
Percentage below reasonable range: 5.29%;
Percentage above reasonable range: 0.13%.
Date: May 2007;
Percentage below reasonable range: 2.81%;
Percentage above reasonable range: 0.19%.
Date: June 2007;
Percentage below reasonable range: 2.96%;
Percentage above reasonable range: 0.19%.
Date: July 2007;
Percentage below reasonable range: 3.33%;
Percentage above reasonable range: 0.38%.
Date: August 2007;
Percentage below reasonable range: 1.34%;
Percentage above reasonable range: 0.32.
Date: September 2007;
Percentage below reasonable range: 2.28%;
Percentage above reasonable range: 0.72%.
Source: GAO analysis of MMS data.
[End of figure]
For gas produced offshore in the Gulf of Mexico, we found that our
calculated implicit sales prices fell outside of the range of
prevailing market prices 6.6 percent of the time. We used a range of
market prices at the Henry Hub--a major gas trading center in the Gulf
of Mexico--each month for comparison. To establish a low and a high
price, we examined three specific prices each month and chose the
highest and the lowest price from among the three. These three prices
are the maximum mid-day spot price during that month, the minimum mid-
day spot price during that month, and the First of the Month price.
[Footnote 18] All three prices are common prices upon which producers
sell their gas in the Gulf of Mexico, according to MMS, and we believe
this is a conservative approach. The average difference between the
highest and the lowest prices was about $3 per MMBtu during the period
October 2005 through September 2007. These prices are illustrated in
figure 5.
Figure 5: Range of Reasonable Gas Prices in the Gulf of Mexico Based on
Highest and Lowest Daily Spot Prices for Each Month and the First of
the Month Price at the Henry Hub (Dollars per MMBtu):
[Refer to PDF for image: multiple line graph]
Date: October 2005;
Highest gas price: $15;
Lowest gas price: $12.
Date: November 2005;
Highest gas price: $14;
Lowest gas price: $8.
Date: December 2005;
Highest gas price: $16;
Lowest gas price: $9.
Date: January 2006;
Highest gas price: $12;
Lowest gas price: $7.
Date: February 2006;
Highest gas price: $9;
Lowest gas price: $6.
Date: March 2006;
Highest gas price: $8;
Lowest gas price: $6.
Date: April 2006;
Highest gas price: $8;
Lowest gas price: $6.
Date: May 2006;
Highest gas price: $8;
Lowest gas price: $5.
Date: June 2006;
Highest gas price: $8;
Lowest gas price: $5.
Date: July 2006;
Highest gas price: $8;
Lowest gas price: $5.
Date: August 2006;
Highest gas price: $9;
Lowest gas price: $6.
Date: September 2006;
Highest gas price: $7;
Lowest gas price: $4.
Date: October 2006;
Highest gas price: $8;
Lowest gas price: $3.
Date: November 2006;
Highest gas price: $8;
Lowest gas price: $6.
Date: December 2006;
Highest gas price: $9;
Lowest gas price: $5.
Date: January 2007;
Highest gas price: $8;
Lowest gas price: $5.
Date: February 2007;
Highest gas price: $10;
Lowest gas price: $6.
Date: March 2007;
Highest gas price: $8;
Lowest gas price: $6.
Date: April 2007;
Highest gas price: $8;
Lowest gas price: $7.
Date: May 2007;
Highest gas price: $8;
Lowest gas price: $7.
Date: June 2007;
Highest gas price: $8;
Lowest gas price: $6.
Date: July 2007;
Highest gas price: $7;
Lowest gas price: $5.
Date: August 2007;
Highest gas price: $8;
Lowest gas price: $5.
Date: September 2007;
Highest gas price: $7;
Lowest gas price: $5.
Source: GAO analysis of MMS data.
[End of figure]
As with oil prices, being outside of the range does not necessarily
mean that the price is erroneous, but we would not expect this to be a
common occurrence. Conversely, being within this range means that the
sales price is reasonable but not necessarily correct. In addition to
possible errors in reported sales values or sales volumes, MMS
officials said that low or high prices can reflect marketing efforts.
Quality does not affect calculated prices because gas quality is
standardized by reporting sales prices per MMBtu. The percentage that
our calculated gas prices appeared erroneous is depicted in figure 6,
distinguishing between implicit prices that fell below and above the
expected range.
Figure 6: Sales Prices for Gas from Federal Leases in the Offshore Gulf
of Mexico That Appear Erroneous, Fiscal Years 2006 and 2007:
[Refer to PDF for image: stacked vertical bar graph]
Percentage appearing erroneous:
Date: October 2005;
Percentage below reasonable range: 16.8%;
Percentage above reasonable range: 2.5%.
Date: November 2005;
Percentage below reasonable range: 6%;
Percentage above reasonable range: 7.9%.
Date: December 2005;
Percentage below reasonable range: 6%;
Percentage above reasonable range: 1.3%.
Date: January 2006;
Percentage below reasonable range: 3%;
Percentage above reasonable range: 2%.
Date: February 2006;
Percentage below reasonable range: 0.9%;
Percentage above reasonable range: 3.1%.
Date: March 2006;
Percentage below reasonable range: 3%;
Percentage above reasonable range: 2.6%.
Date: April 2006;
Percentage below reasonable range: 2.7%;
Percentage above reasonable range: 2.5%.
Date: May 2006;
Percentage below reasonable range: 0.9%;
Percentage above reasonable range: 2%.
Date: June 2006;
Percentage below reasonable range: 1.8%;
Percentage above reasonable range: 1%.
Date: July 2006;
Percentage below reasonable range: 2.3%;
Percentage above reasonable range: 1.2%.
Date: August 2006;
Percentage below reasonable range: 2.8%;
Percentage above reasonable range: 1.8%.
Date: September 2006;
Percentage below reasonable range: 1.5%;
Percentage above reasonable range: 8.3%.
Date: October 2006;
Percentage below reasonable range: 1.2%;
Percentage above reasonable range: 2.2%.
Date: November 2006;
Percentage below reasonable range: 3.4%;
Percentage above reasonable range: 3.2%.
Date: December 2006;
Percentage below reasonable range: 1.9%;
Percentage above reasonable range: 1.5%.
Date: January 2007;
Percentage below reasonable range: 2.3%;
Percentage above reasonable range: 1.5%.
Date: February 2007;
Percentage below reasonable range: 1.3%;
Percentage above reasonable range: 1.2%.
Date: March 2007;
Percentage below reasonable range: 2.8%;
Percentage above reasonable range: 3.5%.
Date: April 2007;
Percentage below reasonable range: 7.9%;
Percentage above reasonable range: 4.7%.
Date: May 2007;
Percentage below reasonable range: 4.4%;
Percentage above reasonable range: 4.4%.
Date: June 2007;
Percentage below reasonable range: 1.8%;
Percentage above reasonable range: 5.5%.
Date: July 2007;
Percentage below reasonable range: 2.3%;
Percentage above reasonable range: 10.6%.
Date: August 2007;
Percentage below reasonable range: 2.3%;
Percentage above reasonable range: 1.2.
Date: September 2007;
Percentage below reasonable range: 5.7%;
Percentage above reasonable range: 2.9%.
Source: GAO analysis of MMS data.
[End of figure]
Multiple Factors Affect Oil and Gas Companies' Abilities to Accurately
Report Royalties Owed to the Federal Government:
Oil and gas company representatives reported that several factors can
affect their ability to accurately report royalty data, including
complex land ownership patterns, unit agreements, ambiguity in federal
regulations, short time frames for filing royalty reports, and
inaccuracies in MMS's internal databases.
Complexity of Ownership Can Make Accurate Reporting of Oil and Gas
Royalties More Difficult:
The complexity of unit agreements (units) can impact the accuracy of
royalty data. Upon the request of companies, BLM and MMS can
administratively combine contiguous leases into units to more
efficiently explore and develop an oil or gas reservoir and to lessen
the surface disruption caused by the building of roads and the
installation of pipelines and production equipment. MMS requires payors
to report royalties for each producing lease and, if a lease is
assigned to a unit, to provide information identifying the unit in the
agreement data field. If a lease does not belong to a unit, the
agreement data field should be left blank. However, companies can fail
to complete the agreement data field when a lease belongs to a unit,
which raises questions about whether the royalties paid were for
production belonging to a unit or for production outside of a unit.
This complicates the auditing of the royalty data. Figure 7 shows how
federal leases can be combined into a federal unit to explore for oil
and gas, and figure 8 illustrate the complexity of auditing these
leases when a payor fails to complete the agreement field.
Figure 7: Block Diagram Illustrating the Hypothetical Creation of a
Federal Unit:
[Refer to PDF for image: illustration]
Indicated on the illustration are the following entities:
Sandstone;
Limestone;
Salt;
Shale;
Lease number;
Lease boundary;
Boundary of unit A;
Boundary of unit B;
Oil reservoir;
Producing oil well.
Scenario A:
The most straightforward example of paying royalties occurs when
Company X, which owns lease 1004, drills well #1 and discovers oil in
the shallow sandstone, as illustrated in scenario A. Company X submits
one royalty report for lease 1004 and does not complete the agreement
data field since the lease is not part of an agreement. Auditors have
no difficulty in auditing this lease because there is only one
producing zone, the shallow sandstone.
Scenario B:
This simple example can become more complex over time, such as the
creation of a federal unit as illustrated in scenario B. Based on a
seismic survey, Company Y wants to develop what it believes is an oil
reservoir in the limestone on the leases it owns, leases 1001 and 1002.
Because it believes the reservoir also extends below leases 1003 and
1004, it approaches the owner of lease 1003, Company Z, and the owner
of lease 1004, Company X, to form an agreement combining all four
leases into Unit A, to share the risk and expenses of drilling and any
profits from the sale of oil. Companies X and Z agree to do so but
restrict the unit to production from the limestone. Company Y drills
well 2 on lease 1002 and finds oil in the limestone, and proceeds from
the sale of this oil is shared among the three companies. Each of the
companies reports their respective royalties on lease 1002 to MMS
separately, and all forget to complete the agreement field, which is
required by MMS regulations. Auditors have little difficultly in
auditing these royalty data because there is only one producing zone on
the lease.
Source: GAO.
[End of figure]
Figure 8: Block Diagram Illustrating a Hypothetical Complex
Relationship between Unit Agreements and Potential Impacts on
Oversight:
[Refer to PDF for image: illustration]
Indicated on the illustration are the following entities:
Sandstone;
Limestone;
Salt;
Shale;
Lease number;
Lease boundary;
Boundary of unit A;
Boundary of unit B;
Oil reservoir;
Producing oil well.
Scenario C:
Paying royalties becomes much more complicated when the boundaries of
units overlap as illustrated in scenario C. In this scenario, Company X
wants to develop what it believes is an oil reservoir in the deep
sandstone below its lease 1004 and Company Z‘s lease 1003. It
approaches Company Z, which agrees to combine the two leases into Unit
B to explore and develop the deep sandstone. Company X drills well #3
on lease 1004 and finds oil in both the deep sandstone and the
limestone. Proceeds from the sale of the oil from the deep sandstone is
shared among Companies X, and Z, but proceeds from the sale of oil from
the limestone must be shared among the three companies participating in
Unit A, according to the agreement. Each of the three companies reports
their royalties for lease 1004 to MMS individually, and each provides
royalty data for oil sold from the limestone and royalty data for oil
sold from the deep sandstone, according to MMS guidance, but all fail
to complete the agreement field. As a result, auditors have some
difficulty differentiating the production data from Unit A and Unit B.
In addition to reporting production data from Units A and B, Company X
must report data for production from the shallow sandstone from the
well located on its lease. Since company X has not populated the
agreement field on any of its reports, auditors have great difficulty
sorting out which production belongs to which of the three zones from
which Company X is producing. State and tribal auditors reported that
overlapping units involving onshore leases are common. In our work, we
observed leases in the Gulf of Mexico that belonged to many units.
Source: GAO.
[End of figure]
Complex ownership patterns of federal leases, particularly those issued
by BLM for onshore lands, may also further impact the accuracy of
royalty data, according to several oil and gas company representatives.
For example, when there are intermingled federal, state, and private
leases, royalty reporting can be challenging because companies said
that they may need to rely on multiple operators to provide royalty
information, which is not always consistent and clear, and because
different regulations and rules apply to federal, state, and private
leases. Confusion can sometimes cause the first royalty payment to MMS
to be delayed.
Industry Representatives Stated That Ambiguous Federal Regulations Can
Create Difficulty in Establishing Gas Prices:
Representatives from four companies reported that the ambiguity in
extensive federal regulations that establish prices for oil and gas
lead to difficulty in interpretation and hence, calculating the correct
royalty payment. Nine of the 11 state and tribal auditors that we
interviewed told us that the gas valuation regulations published in
1988 are out of date and that the series of benchmarks within these
regulations that prescribe prices for gas are impractical to apply.
Concerning the gas regulations, the RPC report noted the difficulty of
applying these benchmarks and recommended that MMS consider using
market indices to establish gas prices when companies sell to their
affiliates in lieu of the 1988 benchmarks.[Footnote 19] RPC also
recommended that MMS more clearly define allowable transportation and
processing deductions for natural gas in their regulations.
Royalty Reports May Be Due before Payors Have All the Necessary Data to
Accurately Complete These Reports, Which Necessitates Later
Adjustments:
In addition, three companies reported difficulty in paying royalties on
gas production in a timely manner because they do not receive data from
their gas purchasers in time to meet MMS's deadline for filing royalty
reports and must submit estimates and later correct them. For example,
a purchaser of oil and gas may report an adjustment to the volume of
the gas purchased or the quality of the oil purchased after the payors
are required to report, resulting in the payor having to make a
correction to the original data. Reporting on gas is especially
challenging, because gas transportation and processing are usually not
reconciled within 30 days. However, payors are required to report
royalties to MMS on or before the last day of the month following the
month the product was sold or removed from the lease. Therefore, to
stay in compliance with reporting requirements and avoid penalties,
some company representatives reported that they file estimated gas
royalty reports and keep funds deposited with MMS to cover variances in
royalties due. This is not problematic as long as companies correct
their original data as necessary and pay the correct amount of
royalties.
Royalty Reports on New Leases Are Rejected by MMS's System When BLM
Does Not Provide the Lease Information to MMS in a Timely Manner:
Oil and gas company representatives stated that BLM data on new leases
and units is not always incorporated into MMS's system in a timely
manner, resulting in edit checks rejecting correct payor data. Two of
these representatives reported that BLM's delays in revisions to data
on participating areas--the part of a unit for which participating
companies have agreed to a manner for allocating production--can cause
them to go back and adjust MMS royalty data that is over a year old.
[Footnote 20] This lack of coordination between BLM and MMS was also
addressed in the December 2007 RPC report, which found that incorrect
data leads to errors in royalty receipts and revenue distribution,
requiring MMS staff to correct the information and redistribute the
revenue. The RPC report recommended that BLM and MMS improve data
exchanges by establishing a coordinating committee with representatives
from senior management levels, which would be charged with defining
common data standards and developing solutions for technical issues of
coordination and information sharing at MMS and BLM. MMS is addressing
this issue.
Oil and Gas Company Representatives Generally Understand Key Data
Fields, but Better Clarification of Certain Codes Could Improve the
Accuracy of Payor Reports:
While oil and gas company representatives with whom we spoke reported
that they generally have little difficulty understanding key data
required to complete the Form MMS-2014, most state auditors with whom
we spoke identified some problems with company submitted data. All 10
of the representatives we contacted explained that the major data
fields, such as the sales value, sales volume, and royalty value, are
easy to understand and complete. Eight of the representatives added
that major royalty reporting codes, such as those that define product
types and that provide more information on the nature of the sale of
oil and gas, are also easy to understand. Only, two representatives
reported some difficulty with using certain codes. However, 8 of the 11
state and tribal royalty auditors that we contacted identified a
specific product code that creates difficulty for oil and gas companies
in reporting royalties. Specifically, state auditors told us that
product code 39 for coalbed methane is inconsistently used by payors
reporting royalties, creating difficulty in auditing leases. During our
analysis of MMS's royalty data, we also noted that some companies claim
a processing allowance for coalbed methane, which is not processed,
possibly indicating confusion on use of this code. Additionally, these
auditors told us that a certain code used to explain adjustments, known
as adjustment reason code 10, is commonly used by royalty payors for
all types of adjustments. They said that not having specific adjustment
reason codes for volume adjustments, price changes, royalty
adjustments, processing allowance adjustments, and transportation
allowance adjustments, makes it difficult for auditors to clearly
determine why a royalty payment was adjusted.
Conclusions:
Royalties paid to the federal government for the extraction of oil and
natural gas from federal lands and waters remain both a large source of
revenue to the federal government and a key element in the discussion
on how to balance the use of these lands. Our past work has
consistently raised questions about how MMS oversees the collection of
these royalties and ensures that the country receives fair value for
the resources removed.
MMS has ongoing efforts to improve the reasonableness and accuracy of
its royalty data. However, the agency still has more to do to ensure
that key data used to report, pay, and audit federal royalties are
accurate. In our view, MMS still lacks some effective controls to (1)
prevent erroneous data on allowances from being accepted into the
system, (2) detect errors in data once they are accepted into the
system, and (3) ensure that key data needed for complex oil and gas
units are consistently provided, and this can make the auditing and
other compliance work done by MMS staff more difficult and could result
in the federal government not receiving all the royalties it is due. In
particular, our detailed examination of a portion of key fiscal year
2006 and 2007 data has identified missing data, significant errors, and
questionable data, raising doubts about the 97 percent accuracy level
that MMS reports. In light of our findings, it seems unlikely that MMS
could sustain its goal of 98 percent data accuracy without taking
additional steps.
Recommendations for Executive Action:
To improve the accuracy of royalty data and to help provide a greater
assurance that federal oil and gas royalties are being accurately
reported, to improve the efficiency of audit and compliance activities,
and to increase the likelihood of collecting additional royalties in a
timely manner, we are recommending that the Secretary of the Interior
direct MMS to take five actions.
To better prevent the submission of erroneous data into MMS's database,
we are recommending that MMS:
* share with payors that submit their data through the Electronic Data
Interchange (EDI) MMS's recent edit check that prevents payors from
submitting data claiming processing allowances for gas that is not
processed, including coalbed methane.
To improve the quality of data that has been accepted by MMS's
database, we are recommending that MMS:
* design and implement additional edit checks to evaluate the net
impact of all adjustments on original entries for critical royalty
variables, including sales values, royalty values, sales volumes,
transportation allowances, and processing allowances, by summing each
month all entries for the variable submitted by each payor for each
lease and each commodity and highlight potentially erroneous
submissions to payors and appropriate MMS staff and:
* use the monthly sums of original and adjusting entries for royalty
values, sales values, and sales volumes to ensure that calculated
royalty rates and unit prices for each payor on each lease for each
commodity fall within expected ranges and highlight potentially
erroneous submissions to payors and appropriate MMS staff.
To simplify the auditing of leases and compliance work, we are
recommending that MMS:
* enforce current MMS requirements to populate the agreement field with
the correct agreement number and to populate the agreement field for
leases outside of agreements with a single unique code that is easily
identifiable, and:
* collaborate with state and tribal auditors on the possibility of
adding more specific adjustment reason codes that describe why payors
made corrections to royalty data on the Form MMS-2014.
Agency Comments and Our Evaluation:
We provided a draft of this report to Interior for review and comment.
Interior provided written comments, which are presented in appendix II.
In general, Interior agreed with our findings, concurring with four of
our five recommendations and partially concurring with the other
recommendation. With regard to this latter recommendation, which
involves populating the agreement field, Interior agreed with us that
it is important that MMS improve the enforcement of requirements for
populating the agreement field. However, Interior was uncertain about
how best to achieve this goal and stated that MMS is evaluating the
best methods to ensure accurate reporting for agreements.
As agreed with your offices, unless you publicly announce the contents
of this report earlier, we plan no further distribution until 30 days
from the report date. At that time, we will send copies of this report
to appropriate congressional committees, the Secretary of the Interior,
the Director of MMS, and other interested parties. In addition, the
report will be available at no charge on GAO's Web site at [hyperlink,
http://www.gao.gov].
If you or your staffs have any questions about this report, please
contact me at (202) 512-3841 or ruscof@gao.gov. Contact points for our
Offices of Congressional Relations and Public Affairs may be found on
the last page of this report. Key contributors to this report are
listed in appendix III.
Signed by:
Frank Rusco:
Director, Natural Resources and Environment:
[End of section]
Appendix I: Scope and Methodology:
To examine MMS's key efforts to improve the accuracy of royalty data,
we reviewed and discussed with MMS officials their action plans to
implement RPC recommendations, reviewed a demonstration of MMS's
Compliance Program Tool (CPT), discussed their implementation of the
CPT to systematically identify misreported volumes and missing royalty
reports, reviewed their plan to monitor adjustments, and discussed
efforts to adopt additional edit checks.
To assess the reasonableness and completeness of MMS's royalty data, we
obtained from MMS an extract from their financial management system
consisting of all oil and gas royalty records from fiscal years 2006
and 2007 and assessed the completeness and reasonableness of key data
fields based on extensive data reliability studies documented in two
previous GAO reports.[Footnote 21] We removed records related to rental
payments, gas storage agreements, taxes, contract settlements, and
geothermal operations by using transaction codes, and removed sulfur,
helium, nitrogen, and carbon dioxide, using product codes. We also
limited our analysis to cash royalty payments, excluding royalty-in-
kind (RIK) payments whenever possible or appropriate. Our resulting
analysis file consisted of about 4.1 million royalty records.
First, we assessed the completeness of MMS's data. We developed a
frequency distribution of the number of records per month and compared
these frequencies from month-to-month, looking for abnormal patterns.
We discovered that there were about half as many records for April 2007
as for other months on average. At our request, MMS investigated the
reason and discovered that the contractor who extracted the data
inadvertently excluded records accepted by MMS's system in June 2007--
the month in which much of the data from April 2007 would have been
submitted and accepted. We then obtained from MMS a new file of records
accepted in June 2007 and combined the new data with the rest of the
royalty data, and rechecked the monthly totals. This procedure revealed
a fairly consistent number of records and leases on a month-to-month
basis. We determined that the data we received from MMS were a complete
representation of what was in their data system through our study date
and was therefore reliable enough to allow us to use the extract in our
more detailed review of royalty data. This monthly consistency is
illustrated in figure 9.
Figure 9: Numbers of Oil and Gas Royalty Records and Leases Reported
per Month for Fiscal Years 2006 and 2007:
[Refer to PDF for image: multiple line graph]
Date: October 2005;
Number of Records: 189,880;
Number of Leases: 21,811.
Date: November 2005;
Number of Records: 191,395;
Number of Leases: 22,390.
Date: December 2005;
Number of Records: 183,936;
Number of Leases: 22,291.
Date: January 2006;
Number of Records: 188,488;
Number of Leases: 22,462.
Date: February 2006;
Number of Records: 192,930;
Number of Leases: 22,312.
Date: March 2006;
Number of Records: 189,561;
Number of Leases: 22,399.
Date: April 2006;
Number of Records: 184,503;
Number of Leases: 22,325.
Date: May 2006;
Number of Records: 175,147;
Number of Leases: 22,731.
Date: June 2006;
Number of Records: 171,641;
Number of Leases: 22,840.
Date: July 2006;
Number of Records: 177,064;
Number of Leases: 22,939.
Date: August 2006;
Number of Records: 173,084;
Number of Leases: 22,945.
Date: September 2006;
Number of Records: 164,749;
Number of Leases: 22,981.
Date: October 2006;
Number of Records: 166,901;
Number of Leases: 22,647.
Date: November 2006;
Number of Records: 168,325;
Number of Leases: 22,900.
Date: December 2006;
Number of Records: 176,174;
Number of Leases: 22,962.
Date: January 2007;
Number of Records: 189,830;
Number of Leases: 22,928.
Date: February 2007;
Number of Records: 159,642;
Number of Leases: 22,787.
Date: March 2007;
Number of Records: 160,375;
Number of Leases: 23,064.
Date: April 2007;
Number of Records: 163,465;
Number of Leases: 22,764.
Date: May 2007;
Number of Records: 153,948;
Number of Leases: 23,203.
Date: June 2007;
Number of Records: 152,484;
Number of Leases: 22,897.
Date: July 2007;
Number of Records: 149,203;
Number of Leases: 23,048.
Date: August 2007;
Number of Records: 136,109;
Number of Leases: 22,647.
Date: September 2007;
Number of Records: 126,943;
Number of Leases: 22,519.
Source: GAO analysis of MMS data.
[End of figure]
To examine the completeness of records in more detail, we analyzed a
subset of MMS's royalty data--leases that produced natural gas in the
offshore Gulf of Mexico. We chose this subset because of: (1) its
relatively manageable size--about 2,100 leases out of a total of about
29,000 producing federal and Indian oil and gas leases and (2) its
financial significance--the gas royalties from Gulf of Mexico leases in
fiscal year 2008 account for almost 30 percent of total federal and
Indian oil and gas royalty revenues.[Footnote 22] For each lease, we
compared gas volumes reportedly sold by payors on Form MMS-2014 to gas
volumes reportedly produced by operators on MMS's OGOR. Specifically,
for each lease we added together all sales volumes on the Form MMS-2014
of processed and unprocessed gas in thousands of cubic feet for each
month from January 2006 to September 2007 and compared these to gas
volumes disposed of on the OGOR-B for the same month. From the Form MMS-
2014, we included volumes for cash sales (transaction code 01), royalty-
in-kind sales (transaction codes 06 and 08), and non-royalty bearing
sales under provisions for deepwater royalty relief (transaction code
41). We excluded from our analysis October through December 2005
because major hurricanes disrupted production in the Gulf of Mexico,
resulting in many production facilities being shut down. We also used
data from MMS's Technical Information Management System (TIMS) to
identify all leases that belonged to unit agreements and excluded these
leases in order to simplify the analysis. This resulted in about 1,500
producing gas leases. Also, a significant number of these leases had
royalty reports but no production reports, but missing production
reports were more prevalent for the last 3 months of fiscal year 2007,
possibly indicating that these reports had not yet been received or
accepted by MMS's system.
To investigate the completeness of individual royalty records, we
examined key royalty data fields to ensure that they were populated.
These data fields are necessary to match royalty payments to the proper
payor, lease, sales month, and product code. Fields included payor
number, lease number, sales date, and transaction code. We also checked
that product code and sales type were populated. Because nearly 100
percent of these critical data fields were populated, we discontinued
additional tests on assessing the completeness of individual data
fields. However, we examined certain data fields to ensure that they
were not populated when they should not be. These fields included sales
value and sales volume for certain transaction codes, including minimum
royalty due (transaction code 02), estimated royalty payment
(transaction code 03), transportation allowance (transaction code 11),
processing allowance (transaction code 15), and quality bank adjustment
(transaction code 13). Population of these data fields could result in
counting sales values and sales volumes twice.
We then developed tests to investigate the gross reasonableness of
certain data fields that our past work highlighted as being
problematic, including royalty value, sales value, sales volume,
transportation allowance, and processing allowance. We identified
royalty-in-kind transactions from transaction codes (06 and 08) and
excluded them from this analysis. We employed a technique that is
different from MMS's edit checks, which generally examine only
individual royalty lines. We summed the data fields on all royalty
records for each month on each lease for each royalty payor and product
code. This technique aggregated the original royalty record with all
subsequent adjustments, allowing us to examine the net effect and
easily identify negative sums for royalty values, sales values, or
sales volumes, which MMS's edit checks of individual lines cannot
identify. Since payors generally submit one electronic fund transfer
for all the leases upon which they owe royalties for a given month, a
negative sum can go undetected if submitted along with many other
positive sums. Although we found a relatively small percentage (less
than or equal to 0.2 percent) of negative sums, we examined the
corresponding royalty lines to determine if their financial impact was
significant.
We used the same technique of summing royalty records to examine the
gross reasonableness of transportation and processing allowances. Being
deductions, these allowances should be negative. We found that
transportation allowances and processing allowances were positive 3.8
percent and 10.1 percent of the time, respectively. However when we
examined individual royalty records, we discovered that many of these
records were associated with royalty-in-kind transactions, and
therefore outside of the scope of our analysis. MMS, who creates the
royalty-in-kind data, did not properly identify these RIK leases with
the designated royalty-in-kind transaction codes (06 and 08), but
instead used the codes for transportation (11) and processing (15)
allowances. An MMS official with the RIK program explained that, due to
constraints in their RIK system, some transportation and processing
allowances could be positive due to their RIK system having populated
the transportation and processing data fields for the current month
with changes to prior months reported by pipelines and processing
plants. This official also said that the RIK system included all
revenues and expenses associated with natural gas liquids from the RIK
leases in the processing allowances. These processes for RIK leases are
inconsistent with processes for leases on which royalties are paid in
cash. For cash royalties, adjustments to previous periods are posted to
the specific sales month, not the current month. Also for cash
royalties, revenue is identified as sales value, and allowable
expenses, such as transportation or processing allowances, are
individually identified as transportation or processing allowances for
the appropriate product code. The MMS official said that they corrected
this system problem in July 2007. We were then able to identify the RIK
leases through their payor codes, which are alphanumeric as opposed to
the numeric payor codes of cash royalty payments, and subsequently
removed them. We also checked for transportation and processing
allowances being taken in excess of the maximum amounts allowed by
federal regulations and checked to see if transportation and processing
allowances were taken for transaction codes for which they are not
permitted, such as minimum royalties (transaction code 2), estimated
royalty payments (transaction code 3), quality banks (transaction code
13), and offshore deep water royalty relief (transaction code
41).[Footnote 23] Lastly, we examined royalty data to see if payors
reported processing allowances for products that are not processed,
such as oil, condensate, unprocessed gas, and coalbed methane.
We then investigated the reasonableness and accuracy of royalty values,
sales values, and sales volumes in more detail because these royalty
data fields appeared to be problematic in our previous work.[Footnote
24] Using the same method of summing these data fields each month for
all royalty records for each payor for each lease and each product, we
calculated the royalty rates by dividing royalty value prior to
allowances by sales value. We then compared our calculated royalty
rates to expected royalty rates based on general lease terms because we
did not have access to individual lease terms for the estimated 29,000
producing federal and Indian leases. For offshore leases (product codes
01, 02, 03, 04, and 07), we used royalty rates of 12.5 percent and
16.67 percent for comparison.[Footnote 25] We identified the lease
numbers associated with royalty rates outside of expected values and
compared the calculated royalty rates of these 331 leases to royalty
rates for these leases in the TIMS database. Sixteen of these leases
had royalty rates other than 12.5 or 16.67 percent, and we adjusted our
analysis accordingly. For onshore federal gas production (product codes
03, 04, and 07), we compared our calculated royalty rates to the same
royalty rates as for offshore leases. For onshore federal oil
production, we compared initially our calculated royalty rates to rates
of 12.5 percent to 25 percent.[Footnote 26] According to MMS, this
latter interval included a number of prescribed royalty rates that were
common for oil production from certain leases issued before 1988.
However because of the large number of calculated onshore oil and gas
royalty rates that fell outside of expected values, we selected a
sample of onshore leases for MMS to research. MMS reported that several
leases had royalty rates that were either 5 percent or 10 percent--
rates that they identified as common for certain older leases. We
adjusted our onshore comparison to include these two rates as
acceptable. Because few other leases had royalty rates that were
uncommon, we did not ask MMS to research additional onshore leases. For
Indian leases, we similarly calculated royalty rates and determined
that few leases had royalty rates of less than 12.5 percent, so we did
not pursue comparing these to actual lease terms.
We further investigated the reasonableness and accuracy of royalty
values, sales values, and sales volumes by calculating unit oil and gas
sales prices with Gulf of Mexico monthly data submitted by royalty
payors for each lease. We limited our analysis to the offshore Gulf of
Mexico because this area has well developed transparent markets where
regional prices are readily available, unlike onshore markets. To
compare oil prices, we used a range of market prices each month for
comparison, the low price being the lowest daily spot price that month
for Mars oil (rounded down to the nearest dollar), and the high price
being the highest daily spot price for light Louisiana sweet (rounded
up to the nearest dollar). We investigated doing similar comparisons
onshore but discovered that the price range onshore, with West Texas
Intermediate among the highest priced oil we found, and Wyoming
asphaltic being about the lowest priced oil we found, created a range
that was so wide that it made any comparison meaningless. To compare
gas prices, we examined the maximum mid-day spot price, the minimum mid-
day spot price, and the First of the Month price at the Henry Hub and
chose the highest and the lowest price from among the three (we rounded
the lowest price down to the nearest dollar and rounded the highest
price up to the nearest dollar). In calculating unit gas prices from
MMS royalty data, we used volumes expressed per MMBtu to remove the
effects of quality on price. As with oil prices, we investigated doing
gas price comparisons onshore but found that exceptionally low gas
prices at Opal, Wyoming created a range of prices that was so wide as
to make any comparisons meaningless.
To examine factors that affect oil and gas companies' abilities to
accurately report royalties owed to the federal government, we
interviewed a limited number of oil and gas company representatives. To
solicit views on oil and gas companies' experiences with reporting
royalty data to MMS, we used a nonprobability sample. To draw our
sample, we identified the 20 oil and gas companies that submitted the
highest number of royalty lines on Form MMS-2014 in fiscal years 2006
and 2007 and contacted representatives from the top 15 to request
information. The top 20 companies accounted for 63 percent of all the
royalty lines reported, and the top 15 accounted for more than 56
percent. In addition, we contacted the two largest national oil and gas
industry associations--American Petroleum Institute (API) and the
Independent Petroleum Association of the Mountain States (IPAMS)--to
request information. IPAMS describes itself as a non-profit trade
association representing more than 400 independent oil and natural gas
producers, service and supply companies, banking and financial
institutions, and industry consultants committed to environmentally
responsible oil and natural gas development in the Intermountain West.
API reports that it is the only national trade association that
represents all aspects of America's oil and natural gas industry. API
has 400 corporate members, from the largest major oil company to the
smallest of independents. They include producers, refiners, suppliers,
pipeline operators, and marine transporters, as well as service and
supply companies that support all segments of the industry.
For our semi-structured interview questions, we received a total of 10
responses from oil and gas companies. Specifically, of the 15 companies
with the most royalty lines, 2 responded to our request. From API
members we received two responses, and from IPAMS members we received
six responses. We personally met with two company representatives at
the IPAMS office and discussed their written responses to our
questions. Membership in these associations and being identified as 1
of the 15 companies is not mutually exclusive. Results from this
nonprobability sample cannot be used to make inferences about all oil
and gas companies, because the companies that were not included in our
list of the top royalty payors or members in the associations we
contacted had no chance of being selected as part of the sample.
[End of section]
Appendix II: Comments from the Department of the Interior:
United States Department of the Interior:
Office Of The Secretary:
Washington, DC 20240:
June 30, 2009:
Mr. Frank Rusco
Director, Natural Resources and Environment:
Government Accountability Office:
441 G Street, NW:
Washington, D.C. 20548:
Dear Mr. Rusco:
Thank you for the opportunity to review and comment on the Government
Accountability Office draft report entitled, Mineral Revenues: MMS
Could Do More to Improve the Accuracy of Key Data Used to Collect and
Verify Oil and Gas Royalties (GAO-09-549).
We generally agree with your findings and concur with four of your five
recommendations. We partially concur with Recommendation 4. Our
responses to each recommendation are provided in the Enclosure.
As noted in the draft report, the Minerals Management Service has
several efforts underway to improve the accuracy of the payor-reported
data used to collect and verify royalties. One key effort is the
implementation of recommendations identified by the Royalty Policy
Committee[Footnote 27] to improve edit checks, monitor the quality of
natural gas, revise gas valuation regulations, and improve coordination
with the Bureau of Land Management. The MMS is aggressively
implementing the RPC recommendations and has already taken steps to
improve the accuracy and completeness of royalty data.
As GAO noted in the draft report, MMS subjects payor-reported royalty
data to more than 140 edit checks and has incorporated up-front edits
to prevent payors who report their royalties via the Web from
submitting erroneous data. More recently, MMS has initiated a data
mining effort as a second level screening process to increase the
accuracy of payor-reported data before the data is subjected to
compliance reviews and ultimately to audit.
The diagram below illustrates MMS's overall data accuracy concept:
Figure: MRM Data Accuracy Efforts:
[Refer to PDF for image: illustration]
The illustration depicts an inverted triangle with the precision of
enforcement actions increasing at each subsequent level, using a risk-
based approach. The levels depicted are as follows:
Top level:
Up-Front System Edits;
Timeline: 1 month.
Second level:
Data Mining: Missing Reports, Volume Comparisons, LVS/GVS, High Level
Analyses of Sales Values Royalty Values, Adjustment Monitoring, etc.
Timeline: 6-9 months.
Third level:
Compliance Reviews;
Timeline: 2-3 years.
Fourth level:
Audits;
Timeline: 7 years (Fed. oil and gas).
[End of figure]
Current technology has opened new avenues for MMS to identify and
analyze erroneous data on a real-time basis. The MMS's data mining
processes and analyses, when fully implemented, will be similar to
Recommendations 2 and 3 in the draft report.
We appreciate GAO's insights and recommendations to improve royalty
data accuracy. If you have any questions, please contact Andrea Nygren,
MMS Audit Liaison Officer, at (202) 2084343.
Sincerely,
Signed by: [Illegible], for:
Ned Farquhar:
Acting Assistant Secretary Land and Minerals Management:
Enclosure:
[End of letter]
Enclosure:
Response to Government Accountability Office draft report entitled,
Mineral Revenues: MMS Could Do More to Improve the Accuracy of Key Data
Used to Collect and Verify Oil and Gas Royalties (GAO-09-549).
Recommendation 1: Share with payors that submit their data through the
Electronic Data Interface MMS's recent edit check that prevents payors
from submitting data claiming processing allowances for gas that is not
processed, including coalbed methane.
Response: Concur. The edit check that prevents payors that submit
royalty reports via the Web from claiming processing allowances against
unprocessed gas went into effect in April 2009. We have shared this
edit with those payors that submit their data through EDI so that they
may modify their systems. We are scheduled to implement this edit in
the Minerals Management Service Minerals Revenue Management financial
system in November 2009, so that the edit will apply to all payors,
including those who submit their data through the EDI.
Recommendation 2: Design and implement additional edit checks to
evaluate the net impact of all adjustments on original entries for
critical royalty variables, including sales values, royalty values,
sales volumes, transportation allowances, and processing allowances, by
summing each month all entries for the variable submitted by each payor
for each lease and each commodity and highlight potentially erroneous
submissions to payors and appropriate MMS staff.
Response: Concur. The MMS recently designed and is in the process of
implementing additional edit checks to improve the accuracy of royalty
rates and pricing data reported to MMS. In addition, MMS has initiated
a data mining effort as a second level screening process to increase
the accuracy of payor-reported data before the data are subjected to
compliance reviews and ultimately to audit. The MMS's data mining
process, when fully implemented, will address this recommendation and
will include monitoring adjustments made by payors to royalty reports,
detecting missing royalty reports, comparing payor-reported sales
volumes to third party source documentation, analyzing trends in payor-
reported data, and analyzing key royalty variables to ensure they fall
within expected ranges.
Recommendation 3: Use the monthly sums of original and adjusting
entries for royalty values, sales values, and sales volumes to ensure
that calculated royalty rates and unit prices for each payor on each
lease for each commodity fall within expected ranges and highlight
potentially erroneous submissions to payors and appropriate MMS staff
Response: Concur. The MMS recently designed and is in the process of
implementing additional edit checks to improve the accuracy of royalty
rates and pricing data reported to MMS. In addition, MMS has initiated
a data mining effort as a second level screening process to increase
the accuracy of payor-reported data before the data are subjected to
compliance reviews and ultimately to audit. The MMS's data mining
process, when fully implemented, will address this recommendation and
will include monitoring adjustments made by payors to royalty reports,
detecting missing royalty reports, comparing payor-reported sales
volumes to third party source documentation, analyzing trends in payor-
reported data, and analyzing key royalty variables to ensure they fall
within expected ranges.
Recommendation 4: Enforce current MMS requirements to populate the
agreement field with the correct agreement number and to populate the
agreement field for leases outside of agreements with a single unique
code that is easily identifiable.
Response: Partially Concur. The MMS is working to improve enforcement
of agreement field reporting. We are not confident that populating the
agreement number field for lease-basis reporting with a single unique
code is the best solution to enforce proper reporting. The MMS is
evaluating the best methods for ensuring that payors accurately
populate the agreement number field.
Recommendation 5: Collaborate with state and tribal auditors on the
possibility of adding more specific adjustment reason codes that
describe why payors made corrections to royalty data on the Form MMS-
2014.
Response: Concur. We agree that the Form MMS-2014 should identify why
payors make corrections to royalty data; however, we are not confident
that adding more adjustment reason codes is the best solution to
demonstrate reasons for corrections to royalty data. The MMS management
and internal audit staff will collaborate with State and Tribal
auditors to find the best solution.
Other: In addition to the above responses to GAO's recommendations, we
are bringing the following to your attention. On page 10 of the draft
report, GAO states that MMS has a target date for completion of new
proposed gas valuation regulations of December 2009. The MMS is
revising that target date pending direction from the Department
regarding royalty reform.
[End of section]
Appendix III: GAO Contact and Staff Acknowledgments:
GAO Contact:
Frank Rusco (202) 512-3841 or ruscof@gao.gov:
Staff Acknowledgments:
In addition to the individual named above, Jon Ludwigson, Assistant
Director; Ron Belak; Melinda Cordero; Alison O'Neill; Kim Raheb;
Barbara Timmerman; and Mary Welch made key contributions to this
report.
[End of section]
Footnotes:
[1] Offshore royalty rates for the leases included in the fiscal years
2006 and 2007 royalty data that we examined are typically 12.5 percent
or 16.67 percent while onshore royalty rates are typically 12.5 percent
or from 12.5 to 25 percent for leases issued before 1988, based on
production levels. For certain onshore leases producing heavy oil or
oil classified as stripper production--generally low producing leases
with higher relative costs--royalty rates may have been less than 12.5
percent for part of fiscal year 2006. Certain amounts of oil produced
in the Gulf of Mexico during fiscal years 2006 and 2007 may have been
exempt from royalties under provisions of the Outer Continental Shelf
Deep Water Royalty Relief Act. Royalty rates for newly issued offshore
leases in the Gulf of Mexico were increased twice in 2007 and currently
are 18.75 percent, but it is unlikely that any of the 2007 leases we
looked at would fall into that royalty category because it typically
takes several years at least to develop a lease and begin production.
[2] The Federal Oil and Gas Royalty Simplification and Fairness Act of
1996, Pub. L. No. 104-185, §5(a) (1996), allows payors 6 years to make
adjustments to royalty data.
[3] Five-Year Financial Management Business Plan, FY2008-2012,
Department of the Interior, Minerals Management Service, October 2008.
[4] GAO, Mineral Revenues: Cost and Revenue Information Needed to
Compare Different Approaches for Collecting Federal Oil and Gas
Royalties, [hyperlink, http://www.gao.gov/products/GAO-04-448]
(Washington, D.C.: Apr. 16, 2004).
[5] GAO, Renewable Energy: Increased Geothermal Development Will Depend
on Overcoming Many Challenges, [hyperlink,
http://www.gao.gov/products/GAO-06-629] (Washington, D.C.: May 24,
2006).
[6] GAO, Royalty Revenues: Total Revenues Have Not Increased at the
Same Pace as Rising Oil and Natural Gas Prices due to Decreasing
Production Sold, [hyperlink, http://www.gao.gov/products/GAO-06-786R]
(Washington, D.C.: June 21, 2006).
[7] GAO, Mineral Revenues: Data Management Problems and Reliance on
Self-Reported Data for Compliance Efforts Put MMS Royalty Collections
at Risk, [hyperlink, http://www.gao.gov/products/GAO-08-893R]
(Washington, D.C.: Sept. 12, 2008).
[8] GAO, Mineral Revenues: Data Management Problems and Reliance on
Self-Reported Data for Compliance Efforts Put MMS Royalty Collections
at Risk, [hyperlink, http://www.gao.gov/products/GAO-08-893R]
(Washington, D.C.: Sept. 12, 2008).
[9] Sales volumes for gas on the Form MMS-2014 are actually listed in
thousands of cubic feet (mcf). The industry standard for selling
natural gas is known as MMBtu and refers to millions of Btus, which is
equal to thousands of cubic feet times the heating value of a cubic
foot of gas expressed in Btus.
[10] MMS considers the precise thresholds used to be a confidential
element in its oversight.
[11] We excluded October through December 2005 because major hurricanes
disrupted production.
[12] We did not include all leases in our analysis because we found it
difficult to directly match the operator-reported data with the payor-
reported data for all 29,000 producing federal and Indian leases. Many
leases, particularly those located onshore, may belong to one or more
units. Operators may report production volumes either by unit or by
individual lease, but royalty payors must report royalties by lease and
indicate on their royalty report if the lease belongs to a unit, but it
is common for royalty reporters not to identify the unit, creating
possibilities for mismatching the operator-reported and payor-reported
data. Furthermore, we found MMS's published lists identifying the
leases that belong to units to be incomplete. As such, we used MMS's
Technical Information Management System (TIMS) database, which appears
to be complete but contains data only for offshore leases, to identify
offshore leases within federal units. We then excluded all onshore
leases and the offshore lease belonging to units. We also excluded
offshore oil production because oil, unlike gas, can be held in storage
tanks before being sold, and MMS officials said that there are problems
with the volumes reportedly sold from some of these storage tanks. Our
resulting sample of offshore gas leases numbers about 1,500. Because we
did not evaluate all federal and Indian leases, or even random samples
of all the various types of leases--onshore and offshore, oil and gas,
large and small, for example--the results of this analysis cannot be
extrapolated to the entire universe of federal and Indian leases.
However, offshore gas leases account for a significant amount of gas
production from all federal leases.
[13] This estimate is based on the production volumes reported on the
OGORs, an average Gulf of Mexico royalty rate of 14.7 percent for gas
in fiscal years 2006 and 2007 after allowances, and the average monthly
spot prices per MMBtu at the Henry Hub--a major gas-trading center--
during the month royalty reports were missing.
[14] When we report on royalty data, such as sales volumes, we sum all
sales volumes that an individual payor reports on each lease for each
product code during each sales month. For example, if one company
reports 100 barrels of oil sold from a lease during December and its
partner reports 3 barrels of oil sold from the same lease during the
same month, we have 2 sales volumes. We would then calculate the
percentage of these two sales volumes that are positive--either 0, 50,
or 100 percent.
[15] We could not compare our calculated implicit onshore royalty rates
with the actual royalty rates established in the lease terms because
the latter data were not readily available to us. However, we examined
a sample and found few onshore leases that departed from the royalty
rate ranges we used for comparison. Because of the wide range of
onshore royalty rates that we used, we believe that this is a
conservative approach. Nevertheless, because of the possibility that a
calculated royalty rate that is different from general onshore lease
terms can be legitimate, we refer to the royalty values or the sales
values for onshore leases in this situation as appearing erroneous,
rather than being erroneous.
[16] We refer to these sales values or sales volumes as appearing
erroneous rather than being erroneous because there could be legitimate
reasons for these prices being outside of expected ranges.
[17] We reviewed sales in the offshore Gulf of Mexico because of the
readily available transparent markets there, as opposed to the many
different markets onshore that complicate the valuation of oil and gas.
As in our analyses of sales volumes, sales values, royalty values, and
transportation and processing allowances, we combined all royalty
records submitted by a given payor for each month, product type, and
lease.
[18] First of the Month is a price that is published on the first day
of the month in the publication entitled Inside FERC's Gas Marketing
Report.
[19] A sale of gas by a company to its affiliate is commonly referred
to as a non arm's-length transaction, and according to the gas
valuation regulations, the value of the gas is established according to
the benchmarks. If a company sells gas to another company with which it
is not affiliated, the transaction is commonly referred to as an arm's-
length transaction, and the value of the gas is the sales price and any
additional compensation that accrues from the sale.
[20] In some cases, units are revised to either expand or contract to
reflect better understanding of how oil and gas reservoirs are
connected and can be developed.
[21] [hyperlink, http://www.gao.gov/products/GAO-04-448] and
[hyperlink, http://www.gao.gov/products/GAO-06-786R].
[22] Lease data are from MMS's Web site and include onshore and
offshore leases current to November 14, 2008. We assumed that all
offshore leases in the Gulf of Mexico produced some gas.
[23] Maximum permitted transportation allowances are 50 percent of
sales value. Maximum permitted processing allowances are 66 and 2/3
percent of the sales value less the cost of transportation.
[24] [hyperlink, http://www.gao.gov/products/GAO-06-786R], p. 12.
[25] Specifically, we identified exceptions to be outside of the range
12.4 to 12.6 percent and 16.567 to 16.767 percent, to account for
rounding error.
[26] Specifically, we identified exceptions to be outside of the range
12.4 to 25.1 percent, to account for rounding error.
[27] The Royalty Policy Committee is chartered to provide advice to the
Secretary of the Interior on managing Federal and Indian mineral leases
and revenues.
[End of section]
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