RamySaleem/Machine-Predict-Lithologies-Using-Wireline-logs
To identify lithologies, geoscientists use subsurface data such as wireline logs and petrophysical data. However, this process is often tedious, repetitive, and time-consuming. This project aims to use machine learning techniques to predict lithology from petrophysical logs, which are direct indicators of lithology.
This project helps geoscientists quickly identify subsurface rock types, or lithologies, from well data. You provide raw wireline log data, and it outputs predictions for different rock formations like sandstone, claystone, or limestone. Geoscientists in the oil and gas industry who need to interpret geological formations would find this useful.
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Use this if you need to automate or accelerate the process of identifying subsurface lithologies from wireline log datasets.
Not ideal if your primary goal is manual, expert-driven petrophysical interpretation or if you lack access to comprehensive wireline log data.
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MIT
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Feb 22, 2025
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