2 Day Course - Data Analytics, Geostatistics and Machine Learning
2D course on geostatistics and machine learning
Course Objectives:
You will gain:
- knowledge concerning basic data analytics, geostatistics and machine learning for subsurface modeling.
Course Agenda
- Introduction: objectives, plan
- General Overview - essential concepts from geostatistics
- Data analytics - definitions, bootstrap, declustering
- Spatial continuity - variogram calculation and modeling, trend modeling and spatial estimations
- Limitations with Subsurface Data-driven, Data Analytics, Geostatistics and Machine Learning
- Machine Learning - dimensionality reduction, k-nearest neighbours, decision trees
- Conclusions
The Instructor:
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 that this 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.
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Want to invite me to visit your company for training, mentoring, project review, workflow design and consulting, I'd be happy to drop by and work with you!
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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!
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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