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Jackson's Projects

adseismic.jl icon adseismic.jl

A General Approach to Seismic Inversion Problems using Automatic Differentiation

anisotropy_nn icon anisotropy_nn

Source code for my project of estimating anisotropy parameters with Deep Learning including data creation (earth models and synthetic seismic gathers)

asi-pytorch icon asi-pytorch

Pytorch implementations of "Automatic Seismic Interpretation" publications and repositories

awesome-open-geoscience icon awesome-open-geoscience

Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome

bayes-drt icon bayes-drt

Hierarchical Bayesian methods for inversion of electrochemical impedance spectroscopy (EIS) data

bayesian_seismic_inversion icon bayesian_seismic_inversion

The class computes the Bayesian Seismic Inversion results . Some modules are missing due to its proprietary natures, updates with an executable file is coming soon.

birgit icon birgit

Pre- and Postprocessing tools for full waveform inversion

bruges icon bruges

Geophysics library with various helpful functions

cnn-for-asi icon cnn-for-asi

Tutorial: Convolutional Neural Networks for Automated Seismic Interpretation

cnn_on_seis_ampl icon cnn_on_seis_ampl

An optimized patch-point based approach to seismic fault interpretation using CNN.

cnn_vti_inversion icon cnn_vti_inversion

Determination of the elastic parameters of a VTI medium from sonic logging data using deep learning

d2geo icon d2geo

Framework for computing seismic attributes with Python.

deeplearning_wavelet-lstm icon deeplearning_wavelet-lstm

【本科毕业设计】LSTM + Wavelet(长短期记忆神经网络+小波分析):深度学习与数字信号处理的结合

devito-examples icon devito-examples

Set of seismic modeling and inversion examples using Devito for different wave equations.

easy_hmm icon easy_hmm

A easy HMM program written with Python, including the full codes of training, prediction and decoding.

em-gaussian icon em-gaussian

Implemented EM fitting of a mixture of gaussians on the two-dimensional data set points.dat. Tried different numbers of mixtures, as well as tied vs. separate covariance matrices for each gaussian.

facies_classification_benchmark icon facies_classification_benchmark

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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