GloVe and BERT language models re-trained using geological text.
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Updated
Jul 31, 2023 - Jupyter Notebook
GloVe and BERT language models re-trained using geological text.
Visualization of lithology alongside well log data using Python libraries, primarily Matplotlib, to create a detailed lithology track, Plot of formation tops and exploratory data analysis on well log data to distinguish between various geological formations.
Calculate each facies proportion for each well in a field and plot them as bubble map distribution
Python scripts voor bewerken Nederlandse en Vlaamse bodeminformatie
Calculate facies percentage within specific intervals
A package to extract information from drillholes to feed 3D modelling packages
A mini dataset of lithology microscopic images. This Dataset was developed under supervision of Dr. Keyvan RahimiZadeh and in collabotion with Prof. Amin Beheshti.
SyleFileCrator for INSPIRE
Tools for plotting and analyzing stratigraphic data in R
A probability based approach to characterize lithology using drilling data and Random Forests
This project will explore, analyse and visualise publicly available wells datasets from the United States offshore data centre, the USGS boreholes website - Bureau of Safety and Environmental Enforcement (BSEE) https://www.data.bsee.gov/Main/Default.aspx with a particular focus on the Gulf of Mexico (GOM) wells. This project will study sandstone…
Handle classification within volcanic formation using supervised learning.
Python package for Petrophysical analysis.
Analysis notebooks for the geolink well log dataset
To identify lithologies, geoscientists use subsurface data such as wireline logs and petrophysical data. However, this process is often tedious, repetitive, and time-consuming. This project aims to use machine learning techniques to predict lithology from petrophysical logs, which are direct indicators of lithology.
We have used the new hierarchical carbonate reservoir benchmarking case study created by Costa Gomes J, Geiger S, Arnold D to be used for reservoir characterization, uncertainty quantification and history matching.
Python package for Exploratory Lithology Analysis
GebPy is a Python-based, open source tool for the generation of geological data of minerals, rocks and complete lithological sequences. The data can be generated randomly or with respect to user-defined constraints, for example a specific element concentration within minerals and rocks or the order of units within a complete lithological profile.
Global Scalable Paleo Landscape Evolution Model
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