Practical Aspects of Hydraulic Fracturing Design Optimization using Machine Learning on Field Data: Digital Database, Algorithms and Planning the Field Tests (Russian)-Reference-Cited by-同舟云学术

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Practical Aspects of Hydraulic Fracturing Design Optimization using Machine Learning on Field Data: Digital Database, Algorithms and Planning the Field Tests (Russian)

Published:2020 Issue: Volume: Page:
ISSN:
Container-title:SPE Symposium: Hydraulic Fracturing in Russia. Experience and Prospects
language:
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Author:

Duplyakov Viktor,Morozov Anton,Popkov Dmitry,Vainshtein Albert,Osiptsov Andrei,Burnaev Evgeny,Shel Egor,Paderin Grigory,Kabanova Polina,Fayzullin Ildar,Uchuev Ruslan,Mukhametov Albert,Prutsakov Alexander,Vikhman Ivan,Staritsyn Maxim

Publisher

Society of Petroleum Engineers

Cited by 11 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. Machine Learning in Reservoir Engineering: A Review;Processes;2024-06-14

2. Physics-Informed Machine Learning for Hydraulic Fracturing—Part I: The Backbone Model;Day 2 Tue, April 23, 2024;2024-04-22

3. Machine learning-based fracturing parameter optimization for horizontal wells in Panke field shale oil;Scientific Reports;2024-03-13

4. Digital Integration Scope in Fracturing: Leveraging Domain Knowledge for Intelligent Advisors—Part I;Day 2 Tue, February 13, 2024;2024-02-12

5. A data-driven workflow for prediction of fracturing parameters with machine learning;Thermal Science;2024

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