MICHAEL J. PYRCZ, Ph.D., P.Eng., Associate Professor
Cockrell School of Engineering, Jackson School of Geosciences
and Bureau of Economic Geology

The University of Texas at Austin, Austin, Texas, USA

Peer-reviewed Publications

Paper 1.  Faechner, T., Pyrcz, M.J., and Deutsch, C.V., 2000, Prediction of Yield Response to Soil Remediation: Geoderma, Elsevier, v. 97, pp. 21-38.

Paper 2.  Pyrcz, M.J., and Deutsch, C.V., 2001, Two Artifacts of Probability Field Simulation: Math Geology, Vol. 33, No. 7, pp. 775-799.

Paper 3.  Pyrcz, M.J., and Deutsch, C.V., 2003, "The Whole Story on the Hole Effect: in Searston, S. (eds.) Geostatistical Association of Australasia, Newsletter 18, May.

Paper 4.  Pyrcz, M.J., and Deutsch, C.V., 2003, Declustering and Debiasing: in Searston, S. (eds.) Geostatistical Association of Australasia, Newsletter 19, October.

Paper 5.  Pyrcz, M.J. and Deutsch, C.V., 2005, Conditional Event-based Simulation: in O. Leuangthong and C.V. Deutsch (eds.), Geostatistics Banff 2004, Springer, Netherlands, pp 135-144.

Paper 6.  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.

Paper 7.  Pyrcz, M.J., and Deutsch, C.V., 2006, Semivariogram Models Based On Geometric Offsets: Math Geology, Vol. 38, No. 4, pp. 475-488.

Paper 8.  Pyrcz, M.J., and Deutsch, C.V., 2006, Spectrally Corrected Semivariogram Models: Math Geology, Vol. 38, No. 7.

Paper 9.  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.

Paper 10.  Pyrcz, M.J., and Strebelle, S., 2006, Event-based Geostatistical Modeling of Deepwater Systems: Reservoir Characterization: Integrating Technology and Business Practices: Gulf Coast Section-SEPM Twenty-Sixth Annual Research Conference, pp. 893-922.

Paper 11.  Pyrcz, M.J., Clark, J, Drinkwater, N., Sullivan, M., Fildani, A and McHargue, T., 2006, Event-based Models as a Quantitative Laboratory for Testing Quantitative Rules Associated with Deepwater Distributary Lobes: Reservoir Characterization: Integrating Technology and Business Practices: Gulf Coast Section-SEPM Twenty-Sixth Annual Research Conference, pp. 923-950.

Paper 12.  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.

Paper 13.  Boisvert, J., Pyrcz, M.J., and Deutsch, C.V., 2007, Multiple Point Selection of Training Images: Natural Resources Research, doi: 10.1007/s11053-008-9058-9. http://www.springerlink.com/content/k9843627l327lx02/

Paper 14.  Khan, D., Strebelle, S.,  Hanggoro, D., Willis, B., and Pyrcz, M.J., 2008, Non-stationary Multiple Point simulation to model complex deltaic deposits for flow simulation: in Ortiz, J. and Emery, X. (eds.), Geostatistics Santiago 2008, Springer, Netherlands.

Paper 15.  Zhang, K., Pyrcz, M.J., and Deutsch, C.V., 2008, Advanced Stochastic Surface-based Modeling: in Ortiz, J. and Emery, X. (eds.), Geostatistics Santiago 2008, Springer, Netherlands.

Paper 16.  Pyrcz, M.J., and Strebelle, S., 2008, Event-based Geostatistical Modeling: in Ortiz, J. and Emery, X. (eds.), Geostatistics Santiago 2008, Springer, Netherlands.

Paper 17.  Zhang, K., Pyrcz, M.J., and Deutsch, C.V., 2009, Stochastic Surface-based Modeling for Integration of Geological Information in Turbidite Reservoir Model: Petroleum Geoscience and Engineering. http://dx.doi.org/10.1016/j.petrol.2009.06.019.

Paper 18.  Pyrcz, 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.

Paper 19.  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.

Paper 20.  McHargue,T., Pyrcz,M.J., Sullivan, M.D.,  Clark, J., Fildani, A., Romans, B., Covault, J., Levy, M., Posamentier, and H., Drinkwater,N., 2010, Architecture of turbidite channel systems on the continental slope: patterns and predictions: Marine and Petroleum Geology, Marine and Petroleum Geology, doi:10.1016/j.marpetgeo.2010.07.008.

Paper 21.  Pyrcz, M.J., Sullivan, M.D., McHargue, T.R., Fildani, A., Drinkwater, N.J., Clark, J., and Posamentier, H.W., 2011, Numerical Modeling of Channel Stacking from Outcrop: in Martinsen, O., Pulham, A., Haughton, P., and Sullivan, M. (eds.), SEPM special publication -  Outcrops Revitalized: Tools,  Techniques and Applications.

Paper 22.  McHargue, T.R., Pyrcz, M.J., Sullivan, M.D., Clark, J., Fildani, A., Drinkwater, N.J., Levy M., Posamentier, H.W., Romans, B. and Couvalt, J.,  2011, Numerical Modeling of Channel Stacking from Outcrop: in Martinsen, O., Pulham, A., Haughton, P., and Sullivan, M. (eds.), SEPM special publication -  Outcrops Revitalized: Tools,  Techniques and Applications.

Paper 23.  Cavelius, C., Pyrcz, M.J. and Strebelle, S., 2012, Continuous Trends in Multiple Point Statistics: 2012 Geostatistical Congress, Oslo, Norway

Paper 24.  Pyrcz, M.J., McHargue, T., Clark, J.,  Sullivan, M. and Strebelle, S., 2012, Event-based Geostatistical Modeling: Description and Applications, 2012 Geostatistical Congress, Oslo, Norway, peer-reviewed proceedings.

Paper 25.  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.

Paper 26.  Boisvert, J.B., Pyrcz, M.J., 2014, Conditioning 3D Object-Based Models to a Large Number of Wells: A Channel Example: Mathematics of Planet Earth, 575-579

Paper 27.  Sprunt, E., Howes, S. and Pyrcz, M.J., 2014, Talent & Technology — Impact of the Big Crew Change on Employee Retention, Journal of Petroleum Technology: V. 66,  No. 3, http://www.spe.org/jpt/article/5908-talent-technology-impact-of-the-big-crew-change-on-employee-retention/

Paper 28. Pyrcz, M.J., and White, C.D., 2015, Uncertainty in reservoir modeling, Interpretation, v. 3 (2), SQ7-SQ19.

Paper 29. 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.

Paper 30. Pyrcz, M.J., 2016, Mariethoz, and Caers: Multiple-point Geostatistics (Book Review), Mathematical Geosciences, v. 48 (3), pp. 349-351.

Paper 31. Kaplan, R., Pyrcz, M.J., and Strebelle, S., 2017,  Deepwater Reservoir Connectivity Reproduction from MPS and Process-Mimicking Geostatistical Methods, Geostatistics Valencia 2016, Springer, pp. 601-611.

Paper 32. 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.

Paper 33. Strebelle, S., Vitel, S. and Pyrcz, M.J., 2017,  Integrating New Data in Reservoir Forecasting Without Building New Models, Geostatistics Valencia 2016, Springer, pp. 721-731.

Paper 34. Sullivan, M., Power, B., Laugier, F., Pyrcz, M.J., Dunn, T., Zarra, L. and Covault, J., 2017, Relationship between Reservoir Quality, Facies and Depositional Environment: Working Towards a Predictive Model for the Deepwater Wilcox, Houston Geological Society Bulletin 59 (7), 17

Paper 35. Zhang, J., Covault, J., Pyrcz, M.J., Sharman, G.R., Carvajal, C., Milliken, K., 2018, Quantifying sediment supply to continental margins: Application to the Paleogene Wilcox Group, Gulf of Mexico, AAPG Bulletin v. 102, No. 9., pp. 1685-1702. DOI:10.1306/01081817308

Paper 36. Nwachukwu, A., Jeong, H., Pyrcz, M.J. and Lake, L.W., 2018, Fast evaluation of well placements in heterogeneous reservoir models using machine learning, Journal of Petroleum Science and Engineering 163, 463-475

Paper 37. Wang, Y.C., Pyrcz, M.J., Catuneanu, O. and Boisvert, J.B., 2018, Conditioning 3D object-based models to dense well data, Computers & Geosciences v. 115, pp. 1-11

Paper 38. Griffith, C., Daigle, H., Pyrcz, M.J., Tian, X., and Zhang, B., in press., A Comparison of Clustering Algorithms applied to Fluid Characterization using NMR T1-T2 Maps of Shale, Computers and Geosciences, submission: CAGEO_2018_896.

Paper 39. Hedge, C., Millwater, H., Daigle, H., Pyrcz, M.J., and Gray, K.E., 2019, Rate of penetration (ROP) optimization in drilling with vibration control, Journal of Natural Gas Science and Engineering, v. 67, p. 71-81.

Paper 40. Jo, H., and Pyrcz, M.J., 2019, Robust Rule-based Aggradational Lobe Reservoir Models, Natural Resources Research, v. 29, pp 1193-1213.

Paper 41. Pyrcz, M.J., 2019, Data analytics and geostatistical workflows for modeling uncertainty in unconventional reservoirs, Bulletin for Canadian Society of Petroleum Geologists, v. 67(4), pp 273-282.

Paper 42. Brown, C., Fadili, A., Holubnyak, Y., Kristensen, M., Leetaru, H., Pyrcz, M.J., Sullivan, C., Williams, M., and Reza, Z., 2019, Introduction to special section: Wastewater disposal and CO2 transport in the subsurface, Interpretations, vol. 7(4), pp. SLi-SLii.

Paper 43. Hedge, C., Millwater, H., Daigle, H., Pyrcz, M.J., and Gray, K.E., 2020, Fully coupled end-to-end drilling optimization model using machine learning, Journal of Petroleum Science and Engineering, Journal of Petroleum Science and Engineering, v 180, p 106681.

Paper 44. Santos, J.E., Xu, D., Jo, H., Landry, C.J., Prodanović, M., Pyrcz, M.J., 2020, PoreFlow-Net: A 3D convolutional neural network to predict fluid flow through porous media, Advances in Water Resources v. 138, p. 103539

Paper 45. Khanna, P., Pyrcz, M.J., Droxler, A., Harris, P.M., and Lehrmann, D., 2020, Implications for controls on Upper Cambrian microbial build-ups across 1 multiple-scales, Mason County, Central Texas, USA, Marine and Petroleum Geology, accepted.

Paper 46. Jo, H., Santos, J.E., Pyrcz, M.J., 2020, Conditioning Well Data to Rule-based Lobe Model by Machine Learning with a Generative Adversarial Network, Energy Exploration & Exploitation.

Paper 47. Liu, W., Pyrcz, M.J., in press, Spatial Correlation-based Anomaly Detection Method for Subsurface Modeling, Mathematical Geosciences.

Paper 48. Liu, W., Ikonnikova, S., Hamlin, S., Sivila, L. and Pyrcz, M.J., accepted, Demonstration and Mitigation of Spatial Sampling Bias for Machine Learning Predictions, SPE Reservoir Evaluation & Engineering.

Paper 49. Pisel, J., Pyrcz, M.J., in press, Classifying basin-scale stratigraphic geometries from well logs with machine learning, The Depositional Record.

Paper 50. Jo, H., Pyrcz, M.J., in press, Automatic Semivariogram Modeling by Convolutional Neural Network, Mathematical Geosciences.

Paper 51. Pan, W., Pyrcz, M.J., Torres-Verdin, C., in press, Stochastic Pix2Pix: A New Machine Learning Method for Geophysical and Well Conditioning of Rule-Based Channel Reservoir Models, Natural Resources Research

Paper 52. Santos, J.E., Mehana, M., Wu, H., Prodanovic, M., Pyrcz, M.J., Kang, Q., Lubbers, N., and Viswanathan, H., in press, Modeling nanoconfinement effects using active learning, Journal of Physical Chemistry C.

Paper 53. Salazar. J.J., and Pyrcz, M.J., in prep, Practical Workflow for Assessing Significance of Differences for Nonstationary Subsurface Phenomenon, SPE Reservoir Evaluation & Engineering.

Paper 54. Farell, R., Bickel, E., and Pyrcz, M.J., in prep, Estimating Proved Oil Reserves in Unconventional Assets: Spatial Bootstrapping with N-Effective, Petroleum Science and Engineering.

Paper 55. Laugier, F.L., Sullivan, M.D., and Pyrcz, M.J., in prep, Stratigraphic Controls on Connectivity and Flow Performance in Deepwater Lobe-Dominated Reservoirs, AAPG Bulletin.