Michael J. Pyrcz - Concepedia

Author

Michael J. Pyrcz

Also Known As

Honggeun Jo, Léan Garland, M Pyrcz, M. J. Pyrcz, M. Pyrcz, M.J. Pyrcz, MICHAEL J. PYRCZ, Michael J. Pyrcz, Michael J Pyrcz, Michael J. Pyrcz

162

Publications

2.5K

Citations

H-Index

106

Concepts

All Affiliations

The University of Texas at Austin University of Alberta Chevron (United States)Bureau of Economic Analysis Bureau of Economic Geology

About

Michael J. Pyrcz is an author at The University of Texas at Austin specializing in engineering, data science, and machine learning.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	22	30	1.9K
2	Natural Sciences	4	4	163
3	Management	1	1	45
4	Medicine	1	1	12
5	Public Health	1	1	15

Michael J. Pyrcz

Publications

2.2K

Citations

H-Index

Page 1

	Year	Citations
Architecture of turbidite channel systems on the continental slope: Patterns and predictions T. McHargue, Michael J. Pyrcz, Morgan D. Sullivan, Marine and Petroleum Geology GeophysicsMarine GeologyBasin EvolutionEarth ScienceEngineering	2010	352
PoreFlow-Net: A 3D convolutional neural network to predict fluid flow through porous media Javier E. Santos, Duo Xu, Honggeun Jo, Advances in Water Resources Pore StructureConvolutional Neural NetworkEngineeringMachine LearningFluid Mechanics	2020	225
Fast evaluation of well placements in heterogeneous reservoir models using machine learning Azor Nwachukwu, Hoonyoung Jeong, Michael J. Pyrcz, Journal of Petroleum Science and Engineering EngineeringMachine LearningData ScienceCivil EngineeringFormation Evaluation	2018	138
ALLUVSIM: A program for event-based stochastic modeling of fluvial depositional systems Michael J. Pyrcz, Jeff Boisvert, Clayton V. Deutsch Computers & Geosciences HydrogeologyEarth ScienceEngineeringDebris FlowEvent-based Stochastic Modeling	2009	120
Stochastic surface-based modeling of turbidite lobes Michael J. Pyrcz, Octavian Catuneanu, Clayton V. Deutsch AAPG Bulletin Stochastic Surface-based ModelingEngineeringGeomorphologyCompensational StackingGeological Modeling	2005	111
Fair train-test split in machine learning: Mitigating spatial autocorrelation for improved prediction accuracy Jose J. Salazar, Léan Garland, J. Ochoa, Journal of Petroleum Science and Engineering EngineeringMachine LearningData SciencePattern RecognitionPredictive Analytics	2021	79
Multiple-Point Statistics for Training Image Selection Jeff Boisvert, Michael J. Pyrcz, Clayton V. Deutsch Natural Resources Research Image ClassificationMachine VisionImage AnalysisEngineeringPattern Recognition	2007	76
A library of training images for fluvial and deepwater reservoirs and associated code Michael J. Pyrcz, Jeff Boisvert, Clayton V. Deutsch Computers & Geosciences HydrogeologyImage AnalysisEngineeringWater ResourcesData Science	2007	71
Stratigraphic rule-based reservoir modeling Michael J. Pyrcz, Richard P. Sech, Jacob A. Covault, Bulletin of Canadian Petroleum Geology Louisiana StreetPetroleum EngineeringFluid PropertiesEngineeringStratigraphic Rule-based Reservoir	2015	66
Quantifying sediment supply to continental margins: Application to the Paleogene Wilcox Group, Gulf of Mexico Jinyu Zhang, Jacob A. Covault, Michael J. Pyrcz, AAPG Bulletin Sedimentary RecordEngineeringGeomorphologyPaleogene Wilcox GroupSedimentary Geology	2018	65

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