Zahid Aramai (zahidaramai)

zahidaramai

Geek Repo

Company:KLCube Network

Location:Kuala Lumpur

Home Page:https://zahidaramai.com

Twitter:@aramai_zahid

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Zahid Aramai's repositories

PhaseAttrib

Phase attribute that correlates with gamma ray logs to detect depositional sequences

License:GPL-3.0Stargazers:0Issues:0Issues:0

infinite-ajax-scroll

Turn your existing pagination into infinite scrolling pages with ease

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segam18

Deep-learning seismic facies on state-of-the-art CNN architectures

License:MITStargazers:0Issues:0Issues:0

digidisc

Digital discovery for geoscientists

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PseudoGR

Generate pseudo gamma ray logs from crossplotting acoustic vs shear impedance

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HorizonMachineLearning

Machine Learning Horizon Guided attributes for reservoir properties prediction

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VTI_AVO

Modeling impact of VTI on AVO

License:MITStargazers:0Issues:0Issues:0

MLattrib

Building ML models for any data set

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FaciesClassification-Tensorflow

Machine Learning Algorithm using tensorflow to classify facies from well log data

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Salt-Classification

Kaggle Challenge: Machine Learning algorithm using U-Net to classify salt from images of seismic data

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BootstrapBayesErrorAnalysis

Any model prediction error analysis using bootstrap and bayesian approaches, then applying correction

License:MITStargazers:0Issues:0Issues:0

PorosityProbabilityfromAI

Computing probabilities from well xplot of porosity vs AI for a segy AI volume generating P10, P50, & P90 segy

License:MITStargazers:0Issues:0Issues:0

SeismicVelocityAnalysis

Fit quadratic functions to seismic velocities for depth conversion with probabilities

License:MITStargazers:0Issues:0Issues:0

DepthConversion

Seismic Depth Conversion using Quadratic Functions

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Econstants

Computation of elastic constants and anisotropy from logs

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TerraeMotus

Earthquake warning system using recurrent neural networks

License:MITStargazers:0Issues:0Issues:0

Geological-Log-Data-Machine-Learning-with-Python

A geological log data from a well in Kansas, USA is analyzed using Machine Learning (M.L.) techniques in Python. The data is overviewed, cleaned and analyzed for important patterns and relationships with which we found relationships of logs with each other and correlation of types of formations with the logs. Using this, we can eliminate the use of logs which are correlated or have no relative importance to the type of formation when we have prior geological knowledge of the area. Also, predictions of formation type were made successfully once the data is trained with the M.L. algorithms.

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aspittel.github.io

Personal Site

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animate.css

🍿 A cross-browser library of CSS animations. As easy to use as an easy thing.

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LASinfections

Examples of LAS files that have been infected, diseased, broken, and in need of treatment.

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give-ipay88-payment-gateway

iPay88 Payment Gateway Plugin for Give Donation Platform

License:GPL-3.0Stargazers:0Issues:0Issues:0

keras_extensions

A collection of small extensions to Keras (RBM, momentum schedule, ..)

License:MITStargazers:0Issues:0Issues:0

rege-minyak

A shell script to parse KPDNKK's web page for Malaysia's weekly fuel price

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petrophysics

A python package with useful functions for well log interpretation.

License:MITStargazers:0Issues:0Issues:0

2016-ml-contest

Machine learning contest - October 2016 TLE

License:Apache-2.0Stargazers:0Issues:0Issues:0

sortmatch

A website that uses Glicko2 to run tournaments

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fuzzyLAS

Fuzzy search for well log curves and tools

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recipes

Well data recipes

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Basic-Well-Log-Interpretation

Basic Well Log Interpretation with python, pandas, matplotlib

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