vmolchan Goto Github PK

geosciencebc_2019-008

Repository for the data, machine learning code, and models for the Geoscience BC project: Statistical Assessment of Operational Risks for Induced Seismicity from Hydraulic Fracturing in the Montney, Northeast BC

hackathon_kaust_2022

Tutorial data and project data.

hacktops

Hackaton Schlumberger 2019-03 @CentraleSupelec, Team Paradise

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hausdorff_bench

hdf5reader

C# lib for reading HDF5 (.h5) files

high-performance-computing

hingle_basin

Kushal, Destiny, and Dylan's geostats semester 1 final project

intro2stats

Introduction to Statistics using Python

junctionx-kaust-2019

Forecasting Solar Power for NEOM

learning-tensorflow

A guidebook to building deep learning systems by Tom Hope, Yehezkel S. Resheff and Itay Lieder

lectures

Lectures, notes, code, and other auxiliary materials

lithograph

machine-learning

machine-learning-competition-2020

SPWLA PDDA’s 1st Petrophysical Data-Driven Analytics Contest -- Sonic Log Synthesis

machine_learning

Introduction to machine learning

machinelearning_faciesclassification

My attempt to try different ML algorithms to classify rock facies from well log data

machinelearningsamples-predictivemaintenance

MachineLearningSamples-PredictiveMaitenance

mannvillegroup_strat_hackathon

stratigraphic machine-learning - active work moved to Predictatops

materials_summer2018

mcw-predictive-maintenance-for-remote-field-devices

ml

multivariate-analysis-

Multivariate Analysis

mystic-bit

Learning whilst drilling

ncs-overview

Oversikt over norsk sokkel, oljeproduksjon, gassproduksjon og petroleumproduksjon

nearwellbore_streamline

Source Code of SPE-182614-MS

norne-initial-ensemble

This repository contains Matlab code and description for generating an initial ensemble for the Norne model.

numpy-tutorial-scipyconf-2019

Numpy-Tutorial-SciPyConf-2019

offfaultdef_kausthack

Off Fault deformation project in the First Kaust Hackathon in Geoscience

oil-well-performance-prediction