The repository includes PyTorch code, and the data, to reproduce the results for our paper titled "A Machine Learning Benchmark for Facies Classification" (published in the SEG Interpretation Journal, August 2019).
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Updated
Nov 18, 2022 - Python
The repository includes PyTorch code, and the data, to reproduce the results for our paper titled "A Machine Learning Benchmark for Facies Classification" (published in the SEG Interpretation Journal, August 2019).
Codes related to the publication Gaussian mixture Markov chain Monte Carlo method for linear seismic inversion
Python package for Exploratory Lithology Analysis
Supervised classification to predict rock facies and a T-test flow to evaluate the prediction performance.
Analysis notebooks for the geolink well log dataset
Facies modeling using GANs
The code snippets and repositories are for generating embedded markov model to establish facies changes in the stratigraphic succession
Calculate each facies proportion for each well in a field and plot them as bubble map distribution
Calculate facies percentage within specific intervals
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