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Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.

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253 Commits
About_Michael_Pyrcz.pdf
About_Michael_Pyrcz.pdf
Feb 5, 2019
Binomial_Demo_Environmental.xlsx
Binomial_Demo_Environmental.xlsx
Jul 1, 2020
Bootstrap.ipynb
Bootstrap.ipynb
Nov 13, 2017
Convolution_Simulation_Demo.ipynb
Convolution_Simulation_Demo.ipynb
Dec 12, 2017
DT_Demo.ipynb
DT_Demo.ipynb
May 31, 2018
Declustering.ipynb
Declustering.ipynb
Jan 9, 2019
GeostatsPy_Confidence_Hypothesis.ipynb
GeostatsPy_Confidence_Hypothesis.ipynb
Jan 24, 2019
GeostatsPy_Monte_Carlo_simulation.ipynb
GeostatsPy_Monte_Carlo_simulation.ipynb
Jan 22, 2019
GeostatsPy_bootstrap.ipynb
GeostatsPy_bootstrap.ipynb
Feb 17, 2019
GeostatsPy_datadistributions.ipynb
GeostatsPy_datadistributions.ipynb
Jan 29, 2021
GeostatsPy_declustering.ipynb
GeostatsPy_declustering.ipynb
Mar 30, 2020
GeostatsPy_ensemble_declustering.ipynb
GeostatsPy_ensemble_declustering.ipynb
Feb 8, 2021
GeostatsPy_indicator_kriging.ipynb
GeostatsPy_indicator_kriging.ipynb
Mar 9, 2019
GeostatsPy_inv_distance.ipynb
GeostatsPy_inv_distance.ipynb
Apr 13, 2020
GeostatsPy_kriging.ipynb
GeostatsPy_kriging.ipynb
Jan 6, 2021
GeostatsPy_multivariate.ipynb
GeostatsPy_multivariate.ipynb
Jan 22, 2019
GeostatsPy_overfit.ipynb
GeostatsPy_overfit.ipynb
Jan 24, 2019
GeostatsPy_plottingdata.ipynb
GeostatsPy_plottingdata.ipynb
Jan 17, 2019
GeostatsPy_simulation.ipynb
GeostatsPy_simulation.ipynb
Mar 30, 2019
GeostatsPy_simulation_postsim.ipynb
GeostatsPy_simulation_postsim.ipynb
Jan 6, 2021
GeostatsPy_sisim.ipynb
GeostatsPy_sisim.ipynb
Apr 22, 2019
GeostatsPy_spatial_continuity_directions.ipynb
GeostatsPy_spatial_continuity_directions.ipynb
Jun 29, 2020
GeostatsPy_spatial_updating.ipynb
GeostatsPy_spatial_updating.ipynb
Jan 27, 2019
GeostatsPy_synthetic_well_maker.ipynb
GeostatsPy_synthetic_well_maker.ipynb
Jan 13, 2020
GeostatsPy_transformations.ipynb
GeostatsPy_transformations.ipynb
Jan 19, 2019
GeostatsPy_trends.ipynb
GeostatsPy_trends.ipynb
Jan 21, 2019
GeostatsPy_univariate_simulation.ipynb
GeostatsPy_univariate_simulation.ipynb
Apr 29, 2019
GeostatsPy_variable_ranking.ipynb
GeostatsPy_variable_ranking.ipynb
Feb 17, 2019
GeostatsPy_variogram_calculation.ipynb
GeostatsPy_variogram_calculation.ipynb
Jan 26, 2019
GeostatsPy_variogram_modeling.ipynb
GeostatsPy_variogram_modeling.ipynb
Apr 15, 2020
GeostatsPy_volume_variance.ipynb
GeostatsPy_volume_variance.ipynb
Apr 7, 2019
Interactive_Bootstrap.ipynb
Interactive_Bootstrap.ipynb
Mar 17, 2020
Interactive_Bootstrap_Simple.ipynb
Interactive_Bootstrap_Simple.ipynb
Jan 6, 2021
Interactive_Central_Limit_Theorem.ipynb
Interactive_Central_Limit_Theorem.ipynb
Mar 25, 2020
Interactive_Confidence_Interval.ipynb
Interactive_Confidence_Interval.ipynb
Jan 12, 2021
Interactive_Correlation_Coefficient.ipynb
Interactive_Correlation_Coefficient.ipynb
Sep 14, 2020
Interactive_Hypothesis_Testing.ipynb
Interactive_Hypothesis_Testing.ipynb
Sep 24, 2020
Interactive_LASSO_Regression.ipynb
Interactive_LASSO_Regression.ipynb
Aug 13, 2020
Interactive_Monte_Carlo_simulation.ipynb
Interactive_Monte_Carlo_simulation.ipynb
Feb 3, 2021
Interactive_NeuralNetwork_SingleLayer.ipynb
Interactive_NeuralNetwork_SingleLayer.ipynb
Aug 6, 2020
Interactive_Norms.ipynb
Interactive_Norms.ipynb
Oct 15, 2020
Interactive_Optimization.ipynb
Interactive_Optimization.ipynb
Dec 14, 2020
Interactive_Overfit.ipynb
Interactive_Overfit.ipynb
Nov 14, 2020
Interactive_PCA.ipynb
Interactive_PCA.ipynb
Aug 3, 2020
Interactive_ParametricDistributions.ipynb
Interactive_ParametricDistributions.ipynb
Feb 3, 2021
Interactive_Ridge_Regresion.ipynb
Interactive_Ridge_Regresion.ipynb
Aug 13, 2020
Interactive_Shapley_Values.ipynb
Interactive_Shapley_Values.ipynb
Feb 7, 2021
Interactive_Simple_Kriging.ipynb
Interactive_Simple_Kriging.ipynb
Nov 14, 2020
Interactive_Simulation.ipynb
Interactive_Simulation.ipynb
Nov 14, 2020
Interactive_Sivia_Coin_Toss.ipynb
Interactive_Sivia_Coin_Toss.ipynb
Mar 16, 2020
Interactive_Spatial_Aggregate_Uncertainty.ipynb
Interactive_Spatial_Aggregate_Uncertainty.ipynb
May 22, 2020
Interactive_Spectral_Clustering.ipynb
Interactive_Spectral_Clustering.ipynb
Jun 2, 2020
Interactive_Spurious_Correlations.ipynb
Interactive_Spurious_Correlations.ipynb
Mar 24, 2020
Interactive_String_Effect.ipynb
Interactive_String_Effect.ipynb
Mar 30, 2021
Interactive_Uncertainty_Checking.ipynb
Interactive_Uncertainty_Checking.ipynb
Sep 10, 2020
Interactive_Variogram_Calculation.ipynb
Interactive_Variogram_Calculation.ipynb
May 25, 2020
Interactive_Variogram_Calculation_Modeling.ipynb
Interactive_Variogram_Calculation_Modeling.ipynb
Oct 30, 2020
Interactive_Variogram_Modeling.ipynb
Interactive_Variogram_Modeling.ipynb
Mar 24, 2021
LICENSE
LICENSE
Mar 2, 2019
LU+Decomposition.ipynb
LU+Decomposition.ipynb
Oct 13, 2017
Lorenz_coefficient_demo.ipynb
Lorenz_coefficient_demo.ipynb
Jun 29, 2020
Lorenz_coefficient_function.ipynb
Lorenz_coefficient_function.ipynb
Jun 29, 2020
NSCORE.ipynb
NSCORE.ipynb
Mar 13, 2018
PCA_Demo.ipynb
PCA_Demo.ipynb
May 16, 2018
PyGSLIB_declus_python_demo.ipynb
PyGSLIB_declus_python_demo.ipynb
Oct 19, 2018
PyGSLIB_variogram_python_demo.ipynb
PyGSLIB_variogram_python_demo.ipynb
Oct 25, 2018
PythonDataBasic_Univariate_Statistics.ipynb
PythonDataBasic_Univariate_Statistics.ipynb
Jun 8, 2020
PythonDataBasics_Bivariate_Statistics.ipynb
PythonDataBasics_Bivariate_Statistics.ipynb
Jun 11, 2020
PythonDataBasics_BoostrapHypothesis.ipynb
PythonDataBasics_BoostrapHypothesis.ipynb
Feb 21, 2021
PythonDataBasics_Bootstrap.ipynb
PythonDataBasics_Bootstrap.ipynb
Feb 19, 2021
PythonDataBasics_BootstrapConfidence.ipynb
PythonDataBasics_BootstrapConfidence.ipynb
Mar 7, 2021
PythonDataBasics_DataFrame.ipynb
PythonDataBasics_DataFrame.ipynb
Mar 7, 2021
PythonDataBasics_DistributionsTransformations.ipynb
PythonDataBasics_DistributionsTransformations.ipynb
Feb 1, 2021
PythonDataBasics_Hypothesis.ipynb
PythonDataBasics_Hypothesis.ipynb
Nov 11, 2018
PythonDataBasics_HypothesisTesting.ipynb
PythonDataBasics_HypothesisTesting.ipynb
Feb 21, 2021
PythonDataBasics_LinearRegression.ipynb
PythonDataBasics_LinearRegression.ipynb
Nov 12, 2018
PythonDataBasics_MachineLearning.ipynb
PythonDataBasics_MachineLearning.ipynb
Oct 27, 2020
PythonDataBasics_ParametricDistributions.ipynb
PythonDataBasics_ParametricDistributions.ipynb
Jan 6, 2021
PythonDataBasics_ParametricDistributions_Fitting.ipynb
PythonDataBasics_ParametricDistributions_Fitting.ipynb
Sep 5, 2019
PythonDataBasics_Univariate_Statistics.ipynb
PythonDataBasics_Univariate_Statistics.ipynb
Feb 21, 2021
PythonDataBasics_Univariate_Visualization.ipynb
PythonDataBasics_Univariate_Visualization.ipynb
Mar 19, 2021
PythonDataBasics_ndarrays.ipynb
PythonDataBasics_ndarrays.ipynb
Mar 17, 2021
README.md
README.md
May 16, 2019
Ripley_K_demo.ipynb
Ripley_K_demo.ipynb
Sep 23, 2020
Spatial_Bootstrap.ipynb
Spatial_Bootstrap.ipynb
Feb 8, 2019
SubsurfaceDataAnalytics_Basic_Data_Loading_Display.ipynb
SubsurfaceDataAnalytics_Basic_Data_Loading_Display.ipynb
Jan 6, 2021
SubsurfaceDataAnalytics_BayesianRegression.ipynb
SubsurfaceDataAnalytics_BayesianRegression.ipynb
Oct 20, 2019
SubsurfaceDataAnalytics_Clustering.ipynb
SubsurfaceDataAnalytics_Clustering.ipynb
Aug 21, 2019
SubsurfaceDataAnalytics_ConditionalGenerativeAdversarialNetwork.ipynb
SubsurfaceDataAnalytics_ConditionalGenerativeAdversarialNetwork.ipynb
Jan 12, 2021
SubsurfaceDataAnalytics_Confidence_Hypothesis.ipynb
SubsurfaceDataAnalytics_Confidence_Hypothesis.ipynb
Apr 13, 2019
SubsurfaceDataAnalytics_Convolution_Operators.ipynb
SubsurfaceDataAnalytics_Convolution_Operators.ipynb
Nov 19, 2020
SubsurfaceDataAnalytics_ConvolutionalNeuralNetworks.ipynb
SubsurfaceDataAnalytics_ConvolutionalNeuralNetworks.ipynb
Nov 10, 2020
SubsurfaceDataAnalytics_ConvolutionalNeuralNetworks_Classfier.ipynb
SubsurfaceDataAnalytics_ConvolutionalNeuralNetworks_Classfier.ipynb
Nov 14, 2020
SubsurfaceDataAnalytics_DataFrame.ipynb
SubsurfaceDataAnalytics_DataFrame.ipynb
Sep 3, 2020
SubsurfaceDataAnalytics_DecisionTree.ipynb
SubsurfaceDataAnalytics_DecisionTree.ipynb
Nov 24, 2020
SubsurfaceDataAnalytics_EnsembleTrees.ipynb
SubsurfaceDataAnalytics_EnsembleTrees.ipynb
Jul 14, 2019
SubsurfaceDataAnalytics_Feature_Imputation.ipynb
SubsurfaceDataAnalytics_Feature_Imputation.ipynb
Jan 18, 2021
SubsurfaceDataAnalytics_Feature_Ranking.ipynb
SubsurfaceDataAnalytics_Feature_Ranking.ipynb
Jan 26, 2021
SubsurfaceDataAnalytics_Feature_Transformations.ipynb
SubsurfaceDataAnalytics_Feature_Transformations.ipynb
Aug 8, 2019
SubsurfaceDataAnalytics_GenerativeAdversarialNetwork.ipynb
SubsurfaceDataAnalytics_GenerativeAdversarialNetwork.ipynb
Jan 24, 2021
SubsurfaceDataAnalytics_Gradient_Boosting.ipynb
SubsurfaceDataAnalytics_Gradient_Boosting.ipynb
Aug 15, 2019
SubsurfaceDataAnalytics_Gradient_Boosting_Simple.ipynb
SubsurfaceDataAnalytics_Gradient_Boosting_Simple.ipynb
Aug 16, 2019
SubsurfaceDataAnalytics_Gridded_Data.ipynb
SubsurfaceDataAnalytics_Gridded_Data.ipynb
Sep 3, 2020
SubsurfaceDataAnalytics_IsotonicRegression.ipynb
SubsurfaceDataAnalytics_IsotonicRegression.ipynb
Oct 22, 2019
SubsurfaceDataAnalytics_Lasso.ipynb
SubsurfaceDataAnalytics_Lasso.ipynb
Jul 30, 2019
SubsurfaceDataAnalytics_LinearRegression.ipynb
SubsurfaceDataAnalytics_LinearRegression.ipynb
Jul 5, 2019
SubsurfaceDataAnalytics_MultidimensionalScaling_Cities.ipynb
SubsurfaceDataAnalytics_MultidimensionalScaling_Cities.ipynb
Oct 6, 2020
SubsurfaceDataAnalytics_Multidimensional_Scaling.ipynb
SubsurfaceDataAnalytics_Multidimensional_Scaling.ipynb
Oct 29, 2020
SubsurfaceDataAnalytics_MultipleModels.ipynb
SubsurfaceDataAnalytics_MultipleModels.ipynb
Jan 3, 2020
SubsurfaceDataAnalytics_Multivariate.ipynb
SubsurfaceDataAnalytics_Multivariate.ipynb
May 5, 2020
SubsurfaceDataAnalytics_NaiveBayes.ipynb
SubsurfaceDataAnalytics_NaiveBayes.ipynb
Nov 14, 2020
SubsurfaceDataAnalytics_NeuralNet.ipynb
SubsurfaceDataAnalytics_NeuralNet.ipynb
May 14, 2019
SubsurfaceDataAnalytics_NeuralNetv2.ipynb
SubsurfaceDataAnalytics_NeuralNetv2.ipynb
Nov 24, 2020
SubsurfaceDataAnalytics_PCA.ipynb
SubsurfaceDataAnalytics_PCA.ipynb
Oct 7, 2020
SubsurfaceDataAnalytics_PolygonalRegression.ipynb
SubsurfaceDataAnalytics_PolygonalRegression.ipynb
Jan 3, 2020
SubsurfaceDataAnalytics_RidgeRegression.ipynb
SubsurfaceDataAnalytics_RidgeRegression.ipynb
Jul 6, 2019
SubsurfaceDataAnalytics_Spatial_Bootstrap.ipynb
SubsurfaceDataAnalytics_Spatial_Bootstrap.ipynb
Apr 20, 2019
SubsurfaceDataAnalytics_SupportVectorMachines.ipynb
SubsurfaceDataAnalytics_SupportVectorMachines.ipynb
Nov 22, 2019
SubsurfaceDataAnalytics_TimeSeries.ipynb
SubsurfaceDataAnalytics_TimeSeries.ipynb
Nov 10, 2019
SubsurfaceDataAnalytics_advanced_clustering.ipynb
SubsurfaceDataAnalytics_advanced_clustering.ipynb
Jun 2, 2020
SubsurfaceDataAnalytics_bootstrap.ipynb
SubsurfaceDataAnalytics_bootstrap.ipynb
Apr 13, 2019
SubsurfaceDataAnalytics_clustering.ipynb
SubsurfaceDataAnalytics_clustering.ipynb
May 14, 2019
SubsurfaceDataAnalytics_kNearestNeighbour.ipynb
SubsurfaceDataAnalytics_kNearestNeighbour.ipynb
Jul 11, 2019
SubsurfaceDataAnalytics_scikit_learn.ipynb
SubsurfaceDataAnalytics_scikit_learn.ipynb
Jul 5, 2019
SuportVectorMachines.ipynb
SuportVectorMachines.ipynb
Jun 20, 2018
Variogram.ipynb
Variogram.ipynb
Jun 29, 2018
image2GSLIB.py
image2GSLIB.py
Jun 29, 2018
make_nonlinear_MV_spatial_data.ipynb
make_nonlinear_MV_spatial_data.ipynb
Jun 4, 2020
make_nonlinear_MV_spatial_data_v3.ipynb
make_nonlinear_MV_spatial_data_v3.ipynb
Nov 14, 2020
make_nonlinear_facies.ipynb
make_nonlinear_facies.ipynb
May 27, 2020
make_planview2D_spatial_data.ipynb
make_planview2D_spatial_data.ipynb
May 6, 2020

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PythonNumericalDemos

A collection of Python demos for spatial data analytics, geostatistics and machine learning methods.

I use these demonstrations for:

  1. in-lecture walkthroughs
  2. hands-on experiential learning with specific tasks suggested in the accompanying lecture notes
  3. example workflows to support my students

Other resources that you might be interested in include:

While I have more than 20 years experience coding in FORTRAN, C++ and VBA, I just started with Python a couple of years ago. I love it. I code less and get more done! I recommend Python to any engineers or scientists. Here's some reasons to learn to code:

  1. Transparency – no compiler accepts hand waiving! Coding forces your logic to be uncovered for any other scientist or engineer to review.

  2. Reproducibility – run it, get an answer, hand it over, run it, get the same answer. This is a main principle of the scientific method.

  3. Quantification – programs need numbers. Feed the program and discover new ways to look at the world.

  4. Open-source – leverage a world of brilliance. Check out packages, snippets and be amazed with what great minds have freely shared.

  5. Break Down Barriers – don’t throw it over the fence. Sit at the table with the developers and share more of your subject matter expertise for a better product.

  6. Deployment – share it with others and multiply the impact. Performance metrics or altruism, your good work benefits many others.

  7. Efficiency – minimize the boring parts of the job. Build a suite of scripts for automation of common tasks and spend more time doing science and engineering!

  8. Always Time to Do it Again! – how many times did you only do it once? It probably takes 2-4 times as long to script and automate a workflow. Usually worth it.

  9. Be Like Us – it will change you. Users feel limited, programmers truly harness the power of their applications and hardware.

Alright, that is enough of my ranting. Especially, since I haven't even introduced myself yet!

The Author:

Michael Pyrcz, Associate Professor, University of Texas at Austin

Novel Data Analytics, Geostatistics and Machine Learning Subsurface Solutions

With over 17 years of experience in subsurface consulting, research and development, Michael has returned to academia driven by his passion for teaching and enthusiasm for enhancing engineers' and geoscientists' impact in subsurface resource development.

For more about Michael check out these links:

Twitter | GitHub | Website | GoogleScholar | Book | YouTube | LinkedIn

Want to Work Together?

I hope this content is helpful to those that want to learn more about subsurface modeling, data analytics and machine learning. Students and working professionals are welcome to participate.

  • Want to invite me to visit your company for training, mentoring, project review, workflow design and / or consulting? I'd be happy to drop by and work with you!

  • Interested in partnering, supporting my graduate student research or my Subsurface Data Analytics and Machine Learning consortium (co-PIs including Profs. Foster, Torres-Verdin and van Oort)? My research combines data analytics, stochastic modeling and machine learning theory with practice to develop novel methods and workflows to add value. We are solving challenging subsurface problems!

  • I can be reached at mpyrcz@austin.utexas.edu.

I'm always happy to discuss,

Michael

Michael Pyrcz, Ph.D., P.Eng. Associate Professor The Hildebrand Department of Petroleum and Geosystems Engineering, Bureau of Economic Geology, The Jackson School of Geosciences, The University of Texas at Austin

More Resources Available at: Twitter | GitHub | Website | GoogleScholar | Book | YouTube | LinkedIn

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Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.

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