wassemalward Goto Github PK
Name: Wassem Alward
Type: User
Company: Schlumberger
Bio: Geoscientist & Reservoir Engineer in Schlumberger, Interested in AI & ML for Energy applications, Oil & Gas
Twitter: wassemalward
Location: Worldwide
Name: Wassem Alward
Type: User
Company: Schlumberger
Bio: Geoscientist & Reservoir Engineer in Schlumberger, Interested in AI & ML for Energy applications, Oil & Gas
Twitter: wassemalward
Location: Worldwide
Convolutional neural network for seismic impedance inversion
Neural network based petrophysical property inversion
Lecture notes and source codes from Code Lab's Introduction to Machine Learning bootcamp.
Documentation behind the model used to analyse companies in Simply Wall St
Python implementations in geophysical methods: seismic and gravity
:mortar_board: Path to a free self-taught education in Computer Science!
Teaching materials for the applied machine learning course at Cornell Tech
List of Computer Science courses with video lectures.
2 Day short course on spatial stat analytics, geostatistics and machine learning.
A collection of datasets of ML problem solving
Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016)
Velocity model building by deep learning. Multi-CMP gathers are mapped into velocity logs.
Deep learning for rapid characterization of porous materials
Reading and eventually writing DLIS/LAS/LIS/SEGY files in golang. Very much work in progress.... at the alpha level
Python library for working with the well log format Digital Log Interchange Standard (DLIS V1)
Open source, public notebooks for working with DLISIO
Repository for data science book
Multiscale electrofacies analysis on borhole data
Codes and data for a manuscript in Interpretation Journal, Aug 2019
Code and data to reproduce the figures included in the manuscript
The repository has the PyTorch codes to reproduce the results for our recently accepted paper, "Estimation of Acoustic Impedance from Seismic Data using Temporal Convolutional Network", in SEG Technical Program Expanded Abstracts, 2019.
Face Depixelizer based on "PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models" repository.
The repository includes PyTorch code, and the data, to reproduce the results for our paper titled "A Machine Learning Benchmark for Facies Classification" (accepted for publication in the SEG Interpretation Journal, May 2019).
The repository includes PyTorch code, and the data, to reproduce the results for our paper titled "Facies Classification with Weak and Strong Supervision -- A Comparative Study" (accepted for publication in the SEG Extended abstracts, May 2019).
FlowNet - Data-Driven Reservoir Predictions
the results, code and the data for the Force 2020 Machine learning competition after the completion of the competition in October 2020.
Python tools for structural geology and borehole image analysis which includes data handling, frequency and geometric analysis, and reservoir geomechanics.
A simple jupyter notebook showcasing a static fracture analysis workflow
[MATLAB inside] Comparative research well log prediction: Genetic algorithm vs Neural Network
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.