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A Workflow to Integrate Numerical Simulation, Machine Learning Regression and Bayesian Inversion for Induced Seismicity Study: Principles and a Case Study

Crossref DOI link: https://doi.org/10.1007/s00024-022-03140-7

Published Online: 2022-09-20

Published Print: 2022-10

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Szafranski, Dawid https://orcid.org/0000-0003-4954-9822
Duan, Benchun https://orcid.org/0000-0003-2622-3811
Funding

Funding for this research was provided by:

Berg-Hughes Center for Petroleum and Sedimentary Systems

Crisman Institute for Petroleum Research, Texas A and M University (HF.11.19B)

Society of Exploration Geophysicists Foundation
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Text and Data Mining valid from 2022-09-20

Version of Record valid from 2022-09-20
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Article History

Received: 28 February 2022

Revised: 31 July 2022

Accepted: 24 August 2022

First Online: 20 September 2022

Declarations

:

: The authors have no relevant financial or non-financial interests to disclose.

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