| Geostatistical reservoir modeling MJ Pyrcz, CV Deutsch Oxford university press, 2014 | 2028 | 2014 |
| Architecture of turbidite channel systems on the continental slope: patterns and predictions T McHargue, MJ Pyrcz, MD Sullivan, JD Clark, A Fildani, BW Romans, ... Marine and petroleum geology 28 (3), 728-743, 2011 | 375 | 2011 |
| Stochastic surface-based modeling of turbidite lobes MJ Pyrcz, O Catuneanu, CV Deutsch AAPG bulletin 89 (2), 177-191, 2005 | 168 | 2005 |
| PoreFlow-Net: A 3D convolutional neural network to predict fluid flow through porous media JE Santos, D Xu, H Jo, CJ Landry, M Prodanović, MJ Pyrcz Advances in Water Resources 138, 103539, 2020 | 123 | 2020 |
| ALLUVSIM: A program for event-based stochastic modeling of fluvial depositional systems MJ Pyrcz, JB Boisvert, CV Deutsch Computers & Geosciences 35 (8), 1671-1685, 2009 | 120 | 2009 |
| Fast evaluation of well placements in heterogeneous reservoir models using machine learning A Nwachukwu, H Jeong, M Pyrcz, LW Lake Journal of Petroleum Science and Engineering 163, 463-475, 2018 | 110 | 2018 |
| The whole story on the hole effect MJ Pyrcz, CV Deutsch Geostatistical Association of Australasia, Newsletter 18, 3-5, 2003 | 88 | 2003 |
| Multiple-point statistics for training image selection JB Boisvert, MJ Pyrcz, CV Deutsch Natural Resources Research 16, 313-321, 2007 | 87 | 2007 |
| A library of training images for fluvial and deepwater reservoirs and associated code MJ Pyrcz, JB Boisvert, CV Deutsch Computers & Geosciences 34 (5), 542-560, 2008 | 86 | 2008 |
| Stochastic surface modeling of deepwater depositional systems for improved reservoir models X Zhang, MJ Pyrcz, CV Deutsch Journal of Petroleum Science and Engineering 68 (1-2), 118-134, 2009 | 57 | 2009 |
| Improved geostatistical models of inclined heterolithic strata for McMurray Formation, Alberta, CanadaGeostatistical Models of Inclined Heterolithic Strata, Alberta MM Hassanpour, MJ Pyrcz, CV Deutsch AAPG bulletin 97 (7), 1209-1224, 2013 | 56 | 2013 |
| Integration of geologic information into geostatistical models MJ Pyrcz | 55 | 2004 |
| Stratigraphic rule-based reservoir modeling MJ Pyrcz, RP Sech, JA Covault, BJ Willis, Z Sylvester, T Sun Bulletin of Canadian Petroleum Geology 63 (4), 287-303, 2015 | 54 | 2015 |
| Machine learning-based optimization of well locations and WAG parameters under geologic uncertainty A Nwachukwu, H Jeong, A Sun, M Pyrcz, LW Lake SPE improved oil recovery conference, 2018 | 47 | 2018 |
| Computationally efficient multiscale neural networks applied to fluid flow in complex 3D porous media JE Santos, Y Yin, H Jo, W Pan, Q Kang, HS Viswanathan, M Prodanović, ... Transport in porous media 140 (1), 241-272, 2021 | 44 | 2021 |
| Declustering and debiasing MJ Pyrcz, CV Deutsch Newsletter 19, 1-14, 2003 | 39 | 2003 |
| Multiple point metrics to assess categorical variable models JB Boisvert, MJ Pyrcz, CV Deutsch Natural resources research 19, 165-175, 2010 | 37 | 2010 |
| Quantifying sediment supply to continental margins: Application to the Paleogene Wilcox Group, Gulf of Mexico J Zhang, J Covault, M Pyrcz, G Sharman, C Carvajal, K Milliken AAPG Bulletin 102 (9), 1685-1702, 2018 | 36 | 2018 |
| Prediction of yield response to soil remediation T Faechner, MJ Pyrcz, CV Deutsch Geoderma 97 (1-2), 21-38, 2000 | 33 | 2000 |
| Modeling nanoconfinement effects using active learning JE Santos, M Mehana, H Wu, M Prodanovic, Q Kang, N Lubbers, ... The Journal of Physical Chemistry C 124 (40), 22200-22211, 2020 | 32 | 2020 |
Morgan SullivanChevronVerified email at chevron.com
