Cockrell School of Engineering
The University of Texas at Austin


Michael Pyrcz

 

Associate Professor

Email: mpyrcz@austin.utexas.edu
Phone: (512) 471-3252
Office: CPE 4-186B

Research Areas: Integrated Reservoir Characterization; Unconventional Resources; Petrophysics and pore-scale processes; Geologic Carbon Storage;

Educational Qualifications:

B.Sc. Engineering (Class Rank #1), Mining Engineering, School of Mining and Petroleum Engineering, University of Alberta, Canada

Ph.D. Engineering, Geostatistical Reservoir Modeling, University of Alberta, Canada

PGE Courses:

PGE 337 – Introduction to Geostatistics (Spring 2018)

PGE 383 - Stochastic Methods for Reservoir Modeling (Fall 2017)

Research:

My current research focusses on improving reservoir characterization and modeling for enhanced development planning, minimized environmental impact, stronger profitability and better utilization of valuable natural resources. My students and I work on reservoir modeling related problems of improved integration of geological concepts, modeling for unconventional plays, improved data integration, multiscale and multivariate modeling, machine learning, and optimal decision-making in the presence of uncertainty.

Awards & Honors:

Association of Professional Engineers and Geoscientists of Alberta (APEGA) Gold Medal for B.Sc. Class Rank #1, 2000

National Science and Engineering Research Council of Canada (NSERC), Post Graduate Scholarships (PGS) A and B, 2000-2004.

Best Heavy Oil Paper, Canadian Society of Petroleum Geologists, Canadian Heavy Oil Association, 2004.

Outstanding Technical Editor, Society of Petroleum Engineers, Reservoir Evaluation & Engineering Journal, 2008.

American Association Petrol Geologists, A.I. Levorsen Award for Best Paper Pacific Section, Ventura, California, for paper "Allocyclicity of Sediment Volume and Composition Provide the Basis for a Predictive Model of Turbidite Channel Architectures", T. McHargue, J. Clark, M. Sullivan, M. Pyrcz, A. Fildani, M. Levy, H. Posamentier, B. W. Romans, and J. A. Covault, May 3-5, 2009.

Geological Society of London, Reservoir Modeling Conference at University of Aberdeen, Invited Keynote Speaker, Talk “When Reservoir Models Become Unfit for Purpose”, 2015

International Association of Mathematical Geoscientists Council Nominee, 2016

Geostatistical Congress 2016 Scientific Committee, 2016

Associate Editor, Computers and Geosciences, International Association of Mathematical Geosciences, 2017

Professional Engineer Alberta, Canada, current

Highlighted Publications and Google Scholar Profile:

Book

Pyrcz, M.J., and Deutsch, C.V., 2014, Geostatistical Reservoir Modeling, 2nd Edition, Oxford University Press, New York, p. 448

Peer Reviewed Journal Articles

Pyrcz, M.J., Janele, P., Weaver, D. and Strebelle, S., 2017, Geostatistical Methods for Unconventional Reservoir Uncertainty Assessments, Geostatistics Valencia 2016, Springer, pp. 671-683.

Pyrcz, M.J. and White, C.D., 2015, Uncertainty in reservoir modeling, Interpretation, v. 3 (2), SQ7-SQ19.

Pyrcz, M.J., Sech, R.P., Covault, J.A., Willis, B.J., Sylvester, Z. and Sun, T., 2015, Stratigraphic rule-based reservoir modeling, Bulletin of Canadian Petroleum Geology 63 (4), pp. 287-303.

Hassanpour, M., Pyrcz, M.J., and Deutsch, C.V., 2013, Improved Geostatistical Models of Inclined Heterolithic Strata for McMurray Formation: Alberta, Canada, AAPG Bulletin, v. 97, no. 7, p. 1209-1224.

Boisvert, J., Pyrcz, M.J., and Deutsch, C.V., 2010, Multiple Point Metrics to Assess Categorical Variable Models: Natural Resources Research, (19) 3, pages 165-174.

M.J. Boisvert, J. and Deutsch, C.V., 2009, Alluvsim: a Conditional Event-based Fluvial Model: Computers & Geosciences.doi:10.1016/j.cageo.2008.09.012.

Pyrcz, M.J., Boisvert, J. and Deutsch, C.V., 2007, A Library of Training Images for Fluvial and Deepwater Reservoirs and Associated Code: Computers and Geosciences, doi:10.1016/j.cageo.2007.05.015.

Pyrcz, M.J., Gringarten, E., Frykman, P., and Deutsch, C.V., 2006, Representative Input Parameters for Geostatistical Simulation, in T.C. Coburn, R.J. Yarus and R.L. Chambers, eds., Stochastic Modeling and Geostatistics: Principles, Methods and Case Studies, Volume II: AAPG Computer Applications in Geology 5, pp. 123-137.

Pyrcz, M.J., Catuneanu, O. and Deutsch, C.V., 2005, Stochastic Surface-based Modeling of Turbidite Lobes: American Association of Petroleum Geologists Bulletin, Vol. 89., No. 2, pp 177-191.