Learning whilst drilling through real-time, near-bit prediction ahead of the drill-bit, using offset well log data.
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Updated
Mar 22, 2019 - HTML
Learning whilst drilling through real-time, near-bit prediction ahead of the drill-bit, using offset well log data.
Framework for correlating two or more well logs using feature vectors generated from CNN's in Pytorch
Estimation of Shear wave velocity in oil sands from other well logs
Handle classification within volcanic formation using supervised learning.
Basic Well Log Interpretation with python, pandas, matplotlib. Added lasio to handle LASfile input. Simplyfying vshale calculation. Added Indonesian and Simandoux equation.
Velocity model building by deep learning. Multi-CMP gathers are mapped into velocity logs.
El objetivo de este proyecto es obtener un método tal que la computadora sea capaz de realizar una interpretación de registros geofísicos de manera automática y sin intervención humana alguna dado un set de datos que contenga registros geofísicos.
This project attempts to construct a missing well log from other available well logs, more specifically an NMR well log from the measured Gamma Ray (GR), Caliper, Resistivity logs and the interpreted porosity from a well.
LAS (Log Ascii Standard v2.0) parser in c++: beta-level-software
[MATLAB inside] Comparative research well log prediction: Genetic algorithm vs Neural Network
Electrofacies classification using supervised learning algortihms
LAS (Log Ascii Standard) web utilities in no-framework procedural php
To check log data availability in a LAS file
Generating synthetic DT log
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