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Starred repositories
Object-oriented python wrapper for the VIPhreeqc module
Rapid modelling of reactive transport in porous media using machine learning: limitations and solutions
CO2GraVISim is a reduced physics model of the flow of CO2 injected into a porous reservoir
clustering using t-SNE (t-Distributed Stochastic Neighbor Embedding) and PCA
A compositional model able to generate the composition of a multi-component hydrocarbon fluid. Also a ternary diagram add-on, compliments to python-ternary@github:marcharper
Getting data in and out of Schlumberger Petrel
A cloud platform for greenhouse gas (GHG) data analysis and collaboration.
MGN-LSTM - a graph neural network-based, deep-learning models for multiphase flow in carbon capture and storage (CCS) reservoirs with complex fault systems
Classification and Regression Trees (CART) in python from scratch.
Projects/Works that I have carried out in python to date
Machine Learning in Sci-kit Learn: supervised/unsupervised
Decision Tree Implementation for Machine Learning Class
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
Physics-Informed Neural Networks Trained with Particle Swarm Optimization
Codomain attention neural operator for single to multi-physics PDE adaptation.
Knowledge-driven stochastic modeling of geological geometry features conditioned on drillholes, outcrops, and geophysics
Python scripts for analyzing data extracted from TESCAN Integrated Mineral Analyzer (TIMA)