tobi-ore Goto Github PK

2020-aachen-inverse-problems

Short course on geophysical inversion at RWTH Aachen University.

500-ai-machine-learning-deep-learning-computer-vision-nlp-projects-with-code

500 AI Machine learning Deep learning Computer vision NLP Projects with code

ai_curriculum

Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.

aiaiart

Course content and resources for the AIAIART course.

awesome-open-geoscience

Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome

brittleness-predicition-using-machine-learning

Brittleness is known to be an important reservoir property in hydraulic fracturing. Under a certain level of differential stress, brittle rocks fail creating planes of weakness that are kept open by the injected proppant, causing secondary permeability in the rock. This repo contains python scripts to estimate brittleness using elastic and mineralogical properties and to predict brittleness using machine learning.

cnn_based_petrophysical_inversion

Neural network based petrophysical property inversion

cnnforfaultinterpretation

Deep Convolutional Neural Network for Automatic Fault Recognition from 3D Seismic Dataset

cracking-the-coding-interview-python-solutions-and-explanations

Cracking the Coding Interview in Python 3. The solutions all have detailed explanations with visuals.

ddpm-segmentation

Label-Efficient Semantic Segmentation with Diffusion Models (ICLR'2022)

deep-seismic-fav-docs

Papers related to Deep Learning, GANs, applied to seismic

dermosegdiff

[MICCAI 2023] DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation

dformer

explore_australia

Access to Australia-wide public data for OZ Minerals/Unearthed Explorer challenge

faultnet

fault picking with 3D-UNets

faultseg

Using synthetic datasets to train an end-to-end CNN for 3D fault segmentation (We are working on an improved version!)

fcnvmb-deep-learning-based-seismic-velocity-model-building

Deep-learning inversion: A next-generation seismic velocity model building method

ga_mineral_model

Code for defining mineral model input matrix using a GA and application of tuned matrix for mineral predictions.

hw_0

Homework 0: Make a README.md

hw_1

Homework 1 for GEOG693

hw_11

apply and loops

hw_2

hw_4

wget loop

hw_5

Wget loop for any state

hw_6

Finding Ed Cook

hw_7

Github rivers script

hw_8

hw_9

Subsetting Data Frames

kaust-iraya_summerschool2021

Material for KAUST and Iraya's virtual summer school on Utilising unstructured data in geoscience.

machine-learning-competition-2020

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