lithology

There are 22 repositories under lithology topic.

  • RichardScottOZ/mineral-exploration-machine-learning

    List of resources for mineral exploration and machine learning, generally with useful code and examples.

    18913030
  • gospl

    Geodels/gospl

    Global Scalable Paleo Landscape Evolution Model

    Language:Python6561211
  • GebPy

    MABeeskow/GebPy

    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.

    Language:Jupyter Notebook27313

  • csiro-hydrogeology/pyela

    Python package for Exploratory Lithology Analysis

    Language:Python242225

  • Philliec459/Jupyter-Notebooks_for-Characterization-of-a-New-Open-Source-Carbonate-Reservoir-Benchmarking-Case-St

    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.

    Language:Jupyter Notebook214010

  • RamySaleem/Machine-Predict-Lithologies-Using-Wireline-logs

    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.

    Language:Jupyter Notebook16102

  • LukasMosser/geolink_dataset

    Analysis notebooks for the geolink well log dataset

    Language:Jupyter Notebook9402

  • imranfadhil/quick_pp

    Python package for Petrophysical analysis.

    Language:Python6100

  • aifenaike/Probabilistic-Lithology-Characterization

    A probability based approach to characterize lithology using drilling data and Random Forests

    Language:Jupyter Notebook5101

  • luthfigeo/Litho-Classification

    Handle classification within volcanic formation using supervised learning.

    Language:Jupyter Notebook5203

  • RamySaleem/Reservoir-Quality-in-Producing-Sandstones

    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 sandstones quality as a reservoir, the production history of the operators on the Gulf of Mexico and a well summary report to highlight any possible problem. The reservoir quality analysis will examine relationships between average values of porosity, permeability, depth, temperature, pressure, thickness, age, and play type for data files from 2009 until 2019.The porosity plotted and shown in a wide range of plots as a function of permeability and burial depth. Also, the median (P50) porosity will be plotted against depth to examine the porosity trend. Moreover, this project will investigate the companies oil and gas production in the gulf of Mexico for the last five years. Lastly, the analysis will include an investigation of well summary reports of five wells. The project will include web scrapping to collect online well summary reports to generate a word cloud. The project results can be useful for specifying realistic distributions of parameters for both exploration risk evaluation and/or reservoir modelling by machine learning algorithms in the next project.

    Language:Jupyter Notebook4100

  • AhmadTaheri2021/Lithology-microscopic-images-mini-dataset

    A mini dataset of lithology microscopic images. This Dataset was developed under supervision of Dr. Keyvan RahimiZadeh and in collabotion with Prof. Amin Beheshti.

    Language:Python2101

  • geolba/StyleFileCreator

    SyleFileCrator for INSPIRE

    Language:C#2100

  • pacifikus/oil-hack

    Lithology type classification

    Language:Jupyter Notebook2200

  • warnuk/strattools

    Tools for plotting and analyzing stratigraphic data in R

    Language:R2100
  • Algemeen

    Died1808/Algemeen

    Python scripts voor bewerken Nederlandse en Vlaamse bodeminformatie

    Language:Python1200

  • luthfigeo/Facies-Bubble-Map

    Calculate each facies proportion for each well in a field and plot them as bubble map distribution

    Language:Python1201

  • luthfigeo/Facies-Percentage

    Calculate facies percentage within specific intervals

    Language:Jupyter Notebook1202

  • RichardScottOZ/dh2loop

    A package to extract information from drillholes to feed 3D modelling packages

    Language:Jupyter Notebook1001

  • AnishKS7/-Lithology-Visualization-and-Advanced-Well-Log-Plots-

    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.

    Language:Jupyter Notebook00

  • rafiarsy/Facies-Classification-and-Clustering

    Facies Classification is one of the process to devine the lithology, with unsupervised learning K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) it will be easily devine type of lithology with automation classification.

    Language:Jupyter Notebook

  • RichardScottOZ/geoscience_language_models

    GloVe and BERT language models re-trained using geological text.

    Language:Jupyter Notebook00