What is it about?

Acoustic borehole images present important information about lithofacies. However, it is very time-consuming and laborious to classify them manually. Thus, we propose a advanced Machine Learning model trained with a smart strategy to classify the image logs automatically. The ML model can provide highly accurate facies prediction for image logs in negligible time, greatly contributing to a comprehensive geological understanding.

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Why is it important?

We proposed an automatic, highly-efficient, and accurate facies classification method for the Brazil Pre-salt data, greatly enhancing reservoir characterization.

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This page is a summary of: Enhancing Automatic Facies Classification of Brazilian Pre-salt Acoustic Image Logs with SwinV2-Unet: Leveraging Transfer Learning and Confident Learning, Geophysics, March 2024, Society of Exploration Geophysicists,
DOI: 10.1190/geo2023-0453.1.
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