Fracture Conductivity Prediction Based on Machine Learning in Shale – Part I
DOI:
https://doi.org/10.31224/3757Keywords:
Linear Regression, Shale formations, flow and fractureAbstract
Hydraulic fracturing extracts oil and gas from deep underground, with fracture conductivity being crucial for efficient production. Traditional lab techniques for measuring conductivity are costly and time-consuming. This paper explores using machine learning, specifically multivariate regression, to predict fracture conductivity based on experimental data like Poisson’s ratio and proppant size. Optimizing these models can enhance hydraulic fracturing efficiency in shale formations.
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Posted
2024-06-11
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Copyright (c) 2024 Ella Meyer
This work is licensed under a Creative Commons Attribution 4.0 International License.