Natural Resources Research

, Volume 19, Issue 4, pp 253–268 | Cite as

Development of an Improved Methodology to Assess Potential Unconventional Gas Resources

  • Jesus Salazar
  • Duane A. McVay
  • W. John Lee


Considering the important role played today by unconventional gas resources in North America and their enormous potential for the future around the world, it is vital to both policy makers and industry that the volumes of these resources and the impact of technology on these resources be assessed. To provide for optimal decision making regarding energy policy, research funding, and resource development, it is necessary to reliably quantify the uncertainty in these resource assessments. Since the 1970s, studies to assess potential unconventional gas resources have been conducted by various private and governmental agencies, the most rigorous of which was by the United States Geological Survey (USGS). The USGS employed a cell-based, probabilistic methodology which used analytical equations to calculate distributions of the resources assessed. USGS assessments have generally produced distributions for potential unconventional gas resources that, in our judgment, are unrealistically narrow for what are essentially undiscovered, untested resources. In this article, we present an improved methodology to assess potential unconventional gas resources. Our methodology is a stochastic approach that includes Monte Carlo simulation and correlation between input variables. Application of the improved methodology to the Uinta–Piceance province of Utah and Colorado with USGS data validates the means and standard deviations of resource distributions produced by the USGS methodology, but reveals that these distributions are not right skewed, as expected for a natural resource. Our investigation indicates that the unrealistic shape and width of the gas resource distributions are caused by the use of narrow triangular input parameter distributions. The stochastic methodology proposed here is more versatile and robust than the USGS analytic methodology. Adoption of the methodology, along with a careful examination and revision of input distributions, should allow a more realistic assessment of the uncertainty surrounding potential unconventional gas resources.


Resource assessment unconventional resources natural gas uncertainty quantification 



billion cubic feet


coalbed methane


Energy Information Administration


number of potential untested cells


National Petroleum Council


minimum value for triangular distribution


percentile representing a 5% probability that at least the value exists


percentile representing a 50% probability that at least the value exists


percentile representing a 95% probability that at least the value exists


maximum value for triangular distribution


Potential Gas Committee


untested percentage of assessment-unit area


potential percentage of untested AU area


potential untested percentage of AU area


trillion cubic feet


total petroleum system


assessment-unit area


United States Geological Survey


area per cell of untested cells


potential untested area of assessment unit (AU)


total recovery per cell


total gas resources in the assessment unit


standard deviation


mean value



This research project was funded by the ConocoPhillips and the Crisman Institute for Petroleum Research at the Harold Vance Department of Petroleum Engineering at Texas A&M University. We acknowledge the important contributions of Loring P. White, a USGS consultant. This paper was originally presented as SPE 107974 at the 2007 Rocky Mountain Oil & Gas Technology Symposium, held April 16–18 in Denver, Colorado.


  1. Brighton-Webs, 2007, Triangular distributions: see also:
  2. Crovelli, R. A., 1993, Probability and statistics for petroleum resource assessment: US Geological Survey Open File Report 93-582, 143 p.Google Scholar
  3. Curtis, J. B., and Montgomery, S. L., 2002, Recoverable natural gas resource of the United States: summary of recent estimates: AAPG Bull., v. 86, no. 10, p. 1671–1678.Google Scholar
  4. EIA, 2005, Annual Energy Outlook 2005, Energy Information Administration: see also:
  5. Haskett, W. J., and Brown, P. J., 2005, Evaluation of unconventional resource plays: Society of Petroleum Engineers Paper 96879 presented at the Annual Technical Conference and Exhibition, Dallas, Texas, 9–12 October 2005, 11 p.Google Scholar
  6. Hudak, D. G., 1994, Adjusting triangular distributions for judgmental bias: Risk Anal., v. 14, no. 6, p. 1025–1031.CrossRefGoogle Scholar
  7. NPC, 2003, Balancing natural gas policy: National Petroleum Council, Washington, DC.Google Scholar
  8. PGC, 2003, Potential supply of natural gas in the United States: Potential Gas Committee, Potential Gas Agency, Colorado School of Mines, Golden, Colorado.Google Scholar
  9. Schmoker, J. W., 2002, Resource assessment perspectives for unconventional gas systems: AAPG Bull., v. 86, no. 11, p. 1993–1999.Google Scholar
  10. Schuenemeyer, J. H., and Gautier, D. L., 2010, Aggregation methodology for the circum-arctic resource appraisal: Math. Geosci., v. 42, no. 5, p. 583–594.CrossRefGoogle Scholar
  11. Terasaki, D., and Fujita, K., 2005, The Role of unconventional natural gases in the next 30 years in Asia: Society of Petroleum Engineers Paper 93779 presented at the Asia Pacific Oil and Gas Conference, Jakarta, Indonesia, 5–7 April, 2005, 8 p.Google Scholar
  12. USGS, 1996, 1995 National Assessment of United States Oil and Gas Resources—results, methodology and supporting data: US Geological Survey Digital Data Series DDS-30, Release 2.Google Scholar
  13. USGS, 2002, Petroleum Systems and Geologic Assessment of Oil and Gas in the Uinta–Piceance Province, Utah and Colorado: US Geological Survey Digital Data Series 69-B.Google Scholar

Copyright information

© International Association for Mathematical Geology 2010

Authors and Affiliations

  1. 1.Department of Petroleum Engineering, 3116 TAMUTexas A&M UniversityCollege StationUSA

Personalised recommendations