AUTOMATED METHODS FOR GENERATING LABELED BENCHMARK DATA SET OF GEOLOGICAL THIN-SECTION IMAGES FOR MACHINE LEARNING AND GEOSPATIAL ANALYSIS
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United States of America
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Mar 6, 2025
app pub date -
Aug 29, 2023
filing date -
Aug 29, 2023
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Abstract
A method and a system for generating a labeled benchmark dataset are disclosed. The method includes obtaining a plurality of sources related to a thin section using web scraping and extracting a plurality of images from the plurality of sources related to the thin section, the plurality of images including a plurality of thin section images and a plurality of non-thin section images. Further, the method includes determining the plurality of thin section images from the plurality of extracted images and generating a classification of the plurality of thin section images based on a given classification criteria. The geological thin-section based machine learning models is trained based on the generated classification of the plurality of thin section images and a wellbore drilling plan is generated based on the geological thin-section based machine learning models.
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