A 10,000 ft. [Subsurface] View on Why You Should Learn Geostatistics

Data Science, Geoscience, Geostatistics, Subsurface , , , ,
Michael Pyrcz, PhD, P.Eng (daytum Founding Advisor) Statistics provide quantitative lens for a new perspective on subsurface data and to better understand subsurface uncertainty. Learning Geostatistics will help you leverage: Deductive Statistics – Pooling data for the purpose of quantification of univariate, multivariate and spatial phenomenon Inferential Statistics – Methods to make inferences concerning the…
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Let’s Get Technical, Technical – Criteria for Facies / Rock Types in Subsurface Modeling

Engineering, Geoscience, Geostatistics, Petroleum Engineering, Reservoir Modeling , , , , ,
Michael Pyrcz, PhD, P.Eng (daytum Founding Advisor) After the last lengthy post, this one is short, sweet, [slightly] technical, and vintage... As you can imagine, Facies / Rock type is an important decision for subsurface modeling. Below are a few comments, perspectives, and criteria on the topic. Comments and Perspectives: - When contemplating facies, the…
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Brief Musings on Subsurface Data Analytics and Machine Learning

Coding, Data Science, Engineering, Geoscience, Machine Learning, Petroleum Engineering, Statistics , , , , ,
Michael Pyrcz, PhD, P.Eng (daytum Founding Advisor) Subsurface is Unique Due to (1) sparse data, (2) heterogeneous spatial system, (3) high degree of uncertainty, (4) thick layer of unavoidable interpretation, and (5) extremely high value development decisions We must go beyond the data! Data analytics is the application of data cleaning and statistical analysis to…
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