Machine learning on field data for hydraulic fracturing design optimization-Reference-Cited by-同舟云学术

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Machine learning on field data for hydraulic fracturing design optimization

Published:2019-10-07 Issue: Volume: Page:
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Author:

Mutalova Renata,Morozov Anton,Osiptsov Andrei,Vainshtein Albert,Burnaev Evgeny,Shel Egor,Paderin Grigory

Publisher

California Digital Library (CDL)

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Integration Between Different Hydraulic Fracturing Techniques and Machine Learning in Optimizing and Evaluating Hydraulic Fracturing Treatment;Day 2 Tue, February 13, 2024;2024-02-12

2. Tight and Shale Oil Exploration: A Review of the Global Experience and a Case of West Siberia;Energies;2023-09-07

3. Application of Integration of Geophysics, Geology and Engineering in Hydraulic Fracturing;Proceedings of the 2022 International Petroleum and Petrochemical Technology Conference;2023

4. Classifying Facies in 3D Digital Rock Images Using Supervised and Unsupervised Approaches;Energies;2022-10-17

5. A State-of-the-Art Review on Machine Learning-Based Multiscale Modeling, Simulation, Homogenization and Design of Materials;Archives of Computational Methods in Engineering;2022-08-05

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