Michael J. Pyrcz

发表

Demonstration and Mitigation of Spatial Sampling Bias for Machine-Learning Predictions

Svetlana Ikonnikova, Wendi Liu, H. Scott Hamlin, 2020 .

Fast evaluation of well placements in heterogeneous reservoir models using machine learning

Larry W. Lake, Michael J. Pyrcz, Azor Nwachukwu, 2018 .

ALLUVSIM: A program for event-based stochastic modeling of fluvial depositional systems

Clayton V. Deutsch, Michael J. Pyrcz, Jeff B. Boisvert, 2009, Comput. Geosci..

Selection of Geological Models for Uncertainty Assessment with a Novel Streamline Approach

G. Michael Shook, Michael J. Pyrcz, Michael D. Hogg, 2010 .

Multiple-Point Statistics for Training Image Selection

Clayton V. Deutsch, Michael J. Pyrcz, Jeff B. Boisvert, 2007 .

Conditioning 3D object-based models to dense well data

Michael J. Pyrcz, Jeff B. Boisvert, Yimin C. Wang, 2018, Comput. Geosci..

Event-Based Geostatistical Modeling: Description and Applications

Sebastien Strebelle, Michael J. Pyrcz, Julian David Clark, 2012 .

Characterizing effective flow units in a multiscale porous medium

Duo Xu, Michael J. Pyrcz, Javier E. Santos, 2020 .

Conditioning 3D Object Based Models to a Large Number of Wells: A Channel Example

Michael J. Pyrcz, Jeff B. Boisvert, 2014 .

Rate of penetration (ROP) optimization in drilling with vibration control

Harry R. Millwater, Michael J. Pyrcz, Kenneth E. Gray, 2019, Journal of Natural Gas Science and Engineering.

A Spatial Correlation-Based Anomaly Detection Method for Subsurface Modeling

Michael J. Pyrcz, Wendi Liu, 2020, Mathematical Geosciences.

Fully coupled end-to-end drilling optimization model using machine learning

Harry R. Millwater, Michael J. Pyrcz, Chiranth Hegde, 2020 .

CONDITIONING RULE-BASED MODEL TO STRATIGRAPHY WITH MACHINE LEARNING: DEMONSTRATION IN DEEPWATER LOBE SYSTEM

Not Provided, Michael J. Pyrcz, Honggeun Jo, 2020 .

A comparison of clustering algorithms applied to fluid characterization using NMR T1-T2 maps of shale

Xiao Tian, Han Jiang, Michael J. Pyrcz, 2019, Comput. Geosci..

Modeling nanoconfinement effects using active learning pdf

Nicholas Lubbers, Michael J. Pyrcz, Hao Wu, 2020, The Journal of Physical Chemistry C.

Impact of the Big Crew Change on Employee Retention

Susan Howes, Michael J. Pyrcz, Eve Sprunt, 2014 .

A library of training images for fluvial and deepwater reservoirs and associated code

Clayton V. Deutsch, Michael J. Pyrcz, Jeff B. Boisvert, 2008, Comput. Geosci..

Stochastic Pix2pix: A New Machine Learning Method for Geophysical and Well Conditioning of Rule-Based Channel Reservoir Models

Michael J. Pyrcz, Wen Pan, Carlos Torres-Verdín, 2020, Natural Resources Research.

Machine Learning-Based Optimization of Well Locations and WAG Parameters under Geologic Uncertainty

Larry W. Lake, Alexander Y. Sun, Michael J. Pyrcz, 2018 .

Integrating New Data in Reservoir Forecasting Without Building New Models

Sebastien Strebelle, Michael J. Pyrcz, Sarah Vitel, 2017 .

Introduction to this special section: Machine learning and AI

Michael J. Pyrcz, Margarita Corzo, Olga Brusova, 2020 .

Optimal Placement of Public Electric Vehicle Charging Stations Using Deep Reinforcement Learning pdf

Michael J. Pyrcz, Aidan Petratos, Allen Ting, 2021, ArXiv.

Automatic Feature Highlighting in Noisy RES Data With CycleGAN pdf

Michael J. Pyrcz, Jesse R. Pisel, Nicholas Khami, 2021, ArXiv.

Machine learning-based porosity estimation from spectral decomposed seismic data pdf

Michael J. Pyrcz, Pengcheng Fu, Honggeun Jo, 2021, ArXiv.

Geostatistical significance of differences for spatial subsurface phenomenon

Michael J. Pyrcz, Jose J. Salazar, M. Pyrcz, 2021 .

Tuning machine learning dropout for subsurface uncertainty model accuracy

Michael J. Pyrcz, Eduardo Maldonado-Cruz, 2021 .

Stochastic surface-based modeling of turbidite lobes

Clayton V. Deutsch, Michael J. Pyrcz, Octavian Catuneanu, 2005 .

Process-mimicking Modeling Considerations

Michael J. Pyrcz, Tao Sun, Brian J. Willis, 2014 .

Representative Input Parameters for Geostatistical Simulation

Clayton V. Deutsch, Michael J. Pyrcz, E. Gringarten, 2006 .

Geostatistical Assignment of Reservoir Properties on Unstructured Grids

Clayton V. Deutsch, Michael J. Pyrcz, C. Deutsch, 2002 .

Improved geostatistical models of inclined heterolithic strata for McMurray Formation, Alberta, Canada

Clayton V. Deutsch, Michael J. Pyrcz, C. Deutsch, 2013 .

Stratigraphic Rule-based Reservoir Modeling

Michael J. Pyrcz, Tao Sun, Brian J. Willis, 2015 .

PoreFlow-Net: A 3D convolutional neural network to predict fluid flow through porous media

Duo Xu, Michael J. Pyrcz, Honggeun Jo, 2020, Advances in Water Resources.

Event-Based Geostatistical Modeling: Application to Deep-Water Systems

Sebastien Strebelle, Michael J. Pyrcz, S. Meddaugh, 2006 .

Stochastic surface modeling of deepwater depositional systems for improved reservoir models

Clayton V. Deutsch, Michael J. Pyrcz, C. Deutsch, 2009 .

Conditioning Event-based Fluvial Models

Clayton V. Deutsch, Michael J. Pyrcz, C. Deutsch, 2005 .

Choosing Training Images and Checking Realizations with Multiple Point Statistics

Clayton V. Deutsch, Michael J. Pyrcz, Jeff Boisvert, 2006 .

Multiple Point Metrics to Assess Categorical Variable Models

Clayton V. Deutsch, Michael J. Pyrcz, Jeff B. Boisvert, 2010 .