Formulation of a correlated variables methodology for assessment of continuous gas resources with an application to the Woodford play, Arkoma Basin, eastern Oklahoma
DOI:
https://doi.org/10.21701/bolgeomin.122.4.006Keywords:
collocated cokriging, estimated ultimate recovery, gas shale, sequential stochastic simulationAbstract
Shale gas is a form of continuous unconventional hydrocarbon accumulation whose resource estimation is unfeasible through the inference of pore volume. Under these circumstances, the usual approach is to base the assessment on well productivity through estimated ultimate recovery (EUR). Unconventional resource assessments that consider uncertainty are typically done by applying analytical procedures based on classical statistics theory that ignores geographical location, does not take into account spatial correlation, and assumes independence of EUR from other variables that may enter into the modeling. We formulate a new, more comprehensive approach based on sequential simulation to test methodologies known to be capable of more fully utilizing the data and overcoming unrealistic simplifications. Theoretical requirements demand modeling of EUR as areal density instead of well EUR. The new experimental methodology is illustrated by evaluating a gas play in the Woodford Shale in the Arkoma Basin of Oklahoma. Differently from previous assessments, we used net thickness and vitrinite reflectance as secondary variables correlated to cell EUR. In addition to the traditional probability distribution for undiscovered resources, the new methodology provides maps of EUR density and maps with probabilities to reach any given cell EUR, which are useful to visualize geographical variations in prospectivity.
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References
Cardott, B.J. 2008. Overview of Woodford gas-shale play in Oklahoma. Oklahoma Gas Shales Conference. Electronically available at http://www.ogs.ou.edu/pdf/Cardott_Overview.pdf. Accessed in July 2011.
Cook, T. 2005. Calculation of Estimated Ultimate Recovery (EUR) for Wells in Continuous-Type Oil and Gas Accumulations of the Uinta-Piceance Province. In: Petroleum Systems and Geologic Assessment of Oil and Gas in the Uinta-Piceance Province, Utah and Colorado, Chapter 23, U.S. Geological Survey Digital Data Series DDS-69-D, 5 p. Electronically available at http://pubs.usgs.gov/dds/dds-069/dds-069-d/REPORTS/69_D_CH_23.pdf. Accessed in July 2011.
Crovelli, R.A. 2000. Analytic resource assessment method for continuous (unconventional) oil and gas accumulation-the ACCESS method. U.S. Geological Survey Open-File Report 00-044, 34 p. https://doi.org/10.3133/ofr0044
Deutsch, C.V. 2002. Geostatistical reservoir modeling. Oxford University Press, New York, 384 p. https://doi.org/10.1093/oso/9780195138061.001.0001
Gómez-Hernández, J.J. and Cassiraga, E.F. 1994. Theory and practice of sequential simulation. In: Armstrong, M. and Dowd, P.A., eds., Geostatistical simulation, Kluwer Academic Publishers, Dordrecht, 111-124. https://doi.org/10.1007/978-94-015-8267-4_10
Goovaerts, P. 1997. Geostatistics for natural resources evaluation. Oxford University Press, New York, 483 p. https://doi.org/10.1093/oso/9780195115383.001.0001
Haskett, W.J. and Brown, P. J. 2005. Evaluation of unconventional resource plays. Society of Petroleum Engineers Paper 96879, 11 p. https://doi.org/10.2118/96879-MS
Houseknecht, D.W., Coleman, J.L., Milici, R.C., Garrity, C.P., Rouse, W.A., Fulk, B.R., Paxton, S.T., Abbot, M.M., Mars, J.C., Cook, T.A., Schenk, C.J., Charpentier, R.R., Klett, T.R., Pallastro, R.M., and Ellis, G.S. 2010. Assessment of undiscovered natural gas resources of the Arkoma Basin province and geologically related areas. U. S. Geological Survey Fact Sheet 2010-3043, 4p. Electronically available at http://pubs.usgs.gov/fs/2010/3043/pdf/FS10-3043.pdf. Accessed in July 2011.
Klett, T.R. and Schmoker, J.W. 2005. U.S. Geological Survey input-data form and operational procedure for assessment of continuous petroleum accumulations, 2002. In: Petroleum Systems and Geological Assessment of Oil and Gas in the Southwestern Wyoming Province, Wyoming, Colorado, and Utah, Chapter 18, U.S. Geological Survey Digital Data Series DDS-69-D, 8 p.
Miller, R. and Young, R. 2007. Characterization of the Woodford Shale in outcrop and subsurface in Pontotoc and Coal Counties, Oklahoma. American Association of Petroleum Geologists, Search and Discovery Article #50052, 3 posters.
NOGA Assessment Team. 1995. 1995 National Assessment of United States Oil and Gas Resources. U.S. Geological Survey Circular 1118, 20 p.
Olea, R.A. 2007. Declustering of clustered preferential sampling for global histogram and semivariogram inference. Mathematical Geology, 39 (5), 453-467. https://doi.org/10.1007/s11004-007-9108-6
Olea, R.A. 2008. Inference of distributional parameters for compositional samples containing nondetects. Proceedings of CoDaWork'08, Girona, Spain, http://dugi-doc.udg.edu/handle/10256/708. Accessed in July 2011.
Remy, N., Boucher, A., and Wu, J. 2009. Applied geostatistics with SGeMS: a user's guide. Cambridge University Press, New York, 284 p. and one CD-ROM. https://doi.org/10.1017/CBO9781139150019
Salazar, J., McVay, D.A., and Lee, W.J. 2010. Development of an improved methodology to assess potential unconventional resources. Natural Resources Research. Accessed in September 2010. https://doi.org/10.1007/s11053-010-9126-9
Schmoker, J.W. 1995. Method for assessing continuous type (unconventional) hydrocarbon accumulations. In: Gautier, D.L., Dolton, G.L., Takahashi, K.I., Varnes, K.L., eds. 1995 Natural Assessment of United States Oil and Gas Resources-Results, Methodology, Supporting Data. U.S. Geological Survey Digital Data Series DDS-30, one CD-ROM.
Schmoker, J.W. 1999. U.S. Geological Survey assessment model for continuous (unconventional) oil and gas accumulations-The "FORSPAN" model. U.S. Geological Survey Bulletin 2168, 9 p., only electronically available at http://pubs.usgs.gov/bul/b2168/. Accessed in July 2011.
Shmaryan, L.E. and Journel, A.G. 1999. Two Markov models and their applications. Mathematical Geology 31 (8), 965-988. https://doi.org/10.1023/A:1007505130226
Verly, G. 1993. Sequential Gaussian cosimulation: A simulation method integrating several types of information. In: Soares, A., editor, Geostatistics Tróia '92. Kluwer Academic Publishers, Dordrecht, vol. 1, p. 543-554. https://doi.org/10.1007/978-94-011-1739-5_42
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