Modeling injection-induced fault slip using long short-term memory networks

Mital, Utkarsh; Hu, Mengsu; Guglielmi, Yves; Brown, James; Rutqvist, Jonny

doi:10.1016/j.jrmge.2024.09.006

Title: Modeling injection-induced fault slip using long short-term memory networks

Journal Article · 01 November 2024 · Journal of Rock Mechanics and Geotechnical Engineering

DOI: https://doi.org/10.1016/j.jrmge.2024.09.006 · OSTI ID:2439800

; Hu, Mengsu; Guglielmi, Yves; Brown, James;

Not Available

View Journal Article

Cite

Export

Save

Sponsoring Organization:: USDOE Office of Nuclear Energy (NE)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 2439800

Journal Information:: Journal of Rock Mechanics and Geotechnical Engineering, Journal Name: Journal of Rock Mechanics and Geotechnical Engineering Journal Issue: 11 Vol. 16; ISSN 1674-7755

Publisher:: ElsevierCopyright Statement

Country of Publication:: China

Language:: English

References (30)

Modeling of Coupled Thermo-Hydro-Mechanical Processes with Links to Geochemistry Associated with Bentonite-Backfilled Repository Tunnels in Clay Formations Rutqvist, Jonny; Zheng, Liange; Chen, Fei Rock Mechanics and Rock Engineering, Vol. 47, Issue 1 https://doi.org/10.1007/s00603-013-0375-x	journal	March 2013
ISRM Suggested Method for Step-Rate Injection Method for Fracture In-Situ Properties (SIMFIP): Using a 3-Components Borehole Deformation Sensor Guglielmi, Yves; Cappa, Frederic; Lançon, Hervé Rock Mechanics and Rock Engineering, Vol. 47, Issue 1 https://doi.org/10.1007/s00603-013-0517-1	journal	December 2013
Machine Learning Techniques to Predict Rock Strength Parameters Mahmoodzadeh, Arsalan; Mohammadi, Mokhtar; Ghafoor Salim, Sirwan Rock Mechanics and Rock Engineering, Vol. 55, Issue 3 https://doi.org/10.1007/s00603-021-02747-x	journal	January 2022
Pore pressure modeling and in situ stress determination in Raniganj basin, India Banerjee, Abir; Chatterjee, Rima Bulletin of Engineering Geology and the Environment, Vol. 81, Issue 1 https://doi.org/10.1007/s10064-021-02502-0	journal	December 2021
A predictive deep learning framework for path-dependent mechanical behavior of granular materials Ma, Gang; Guan, Shaoheng; Wang, Qiao Acta Geotechnica, Vol. 17, Issue 8, p. 3463-3478 https://doi.org/10.1007/s11440-021-01419-y	journal	January 2022
Gas generation and migration in Boom Clay, a potential host rock formation for nuclear waste storage Ortiz, L.; Volckaert, G.; Mallants, D. Engineering Geology, Vol. 64, Issue 2-3 https://doi.org/10.1016/S0013-7952(01)00107-7	journal	May 2002
A physics-informed deep learning framework for inversion and surrogate modeling in solid mechanics Haghighat, Ehsan; Raissi, Maziar; Moure, Adrian Computer Methods in Applied Mechanics and Engineering, Vol. 379 https://doi.org/10.1016/j.cma.2021.113741	journal	June 2021
Towards a more accurate characterization of granular media 2.0: Involving AI in the process Cevallos, Stefano Buitrón; Jerves, Alex X.; Mital, Utkarsh Computers and Geotechnics, Vol. 160 https://doi.org/10.1016/j.compgeo.2023.105510	journal	August 2023
Seismicity induced by geological CO2 storage: A review Cheng, Yuxiang; Liu, Wenna; Xu, Tianfu Earth-Science Reviews, Vol. 239 https://doi.org/10.1016/j.earscirev.2023.104369	journal	April 2023
Estimating maximum sustainable injection pressure during geological sequestration of CO2 using coupled fluid flow and geomechanical fault-slip analysis Rutqvist, J.; Birkholzer, J.; Cappa, F. Energy Conversion and Management, Vol. 48, Issue 6 https://doi.org/10.1016/j.enconman.2007.01.021	journal	June 2007
A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition Ben Taieb, Souhaib; Bontempi, Gianluca; Atiya, Amir F. Expert Systems with Applications, Vol. 39, Issue 8 https://doi.org/10.1016/j.eswa.2012.01.039	journal	June 2012
Prediction of the residual strength of clay using functional networks Khan, S. Z.; Suman, Shakti; Pavani, M. Geoscience Frontiers, Vol. 7, Issue 1 https://doi.org/10.1016/j.gsf.2014.12.008	journal	January 2016
Field-scale fault reactivation experiments by fluid injection highlight aseismic leakage in caprock analogs: Implications for CO2 sequestration Guglielmi, Yves; Nussbaum, Christophe; Cappa, Frédéric International Journal of Greenhouse Gas Control, Vol. 111 https://doi.org/10.1016/j.ijggc.2021.103471	journal	October 2021
An international model comparison study of controlled fault activation experiments in argillaceous claystone at the Mont Terri Laboratory Rutqvist, Jonny; Graupner, Bastian; Guglielmi, Yves International Journal of Rock Mechanics and Mining Sciences, Vol. 136 https://doi.org/10.1016/j.ijrmms.2020.104505	journal	December 2020
Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations Raissi, M.; Perdikaris, P.; Karniadakis, G. E. Journal of Computational Physics, Vol. 378 https://doi.org/10.1016/j.jcp.2018.10.045	journal	February 2019
Application of artificial intelligence to rock mechanics: An overview Lawal, Abiodun Ismail; Kwon, Sangki Journal of Rock Mechanics and Geotechnical Engineering, Vol. 13, Issue 1 https://doi.org/10.1016/j.jrmge.2020.05.010	journal	February 2021
Mesh generation and optimization from digital rock fractures based on neural style transfer Hu, Mengsu; Rutqvist, Jonny; Steefel, Carl I. Journal of Rock Mechanics and Geotechnical Engineering, Vol. 13, Issue 4 https://doi.org/10.1016/j.jrmge.2021.02.002	journal	August 2021
Fault Stability Perturbation by Thermal Pressurization and Stress Transfer Around a Deep Geological Repository in a Clay Formation Urpi, L.; Rinaldi, A. P.; Rutqvist, J. Journal of Geophysical Research: Solid Earth, Vol. 124, Issue 8 https://doi.org/10.1029/2019JB017694	journal	August 2019
Machine Learning‐Based Analysis of Geological Susceptibility to Induced Seismicity in the Montney Formation, Canada Wozniakowska, Paulina; Eaton, David W. Geophysical Research Letters, Vol. 47, Issue 22 https://doi.org/10.1029/2020GL089651	journal	November 2020
Learning representations by back-propagating errors Rumelhart, David E.; Hinton, Geoffrey E.; Williams, Ronald J. Nature, Vol. 323, Issue 6088 https://doi.org/10.1038/323533a0	journal	October 1986
Earthquake Prediction Based on Spatio-Temporal Data Mining: An LSTM Network Approach Wang, Qianlong; Guo, Yifan; Yu, Lixing IEEE Transactions on Emerging Topics in Computing, Vol. 8, Issue 1 https://doi.org/10.1109/TETC.2017.2699169	journal	January 2020
Managing injection-induced seismic risks Lee, Kang-Kun; Ellsworth, William L.; Giardini, Domenico Science, Vol. 364, Issue 6442 https://doi.org/10.1126/science.aax1878	journal	May 2019
Induced Seismicity Keranen, Katie M.; Weingarten, Matthew Annual Review of Earth and Planetary Sciences, Vol. 46, Issue 1 https://doi.org/10.1146/annurev-earth-082517-010054	journal	May 2018
Long Short-Term Memory Hochreiter, Sepp; Schmidhuber, Jürgen Neural Computation, Vol. 9, Issue 8 https://doi.org/10.1162/neco.1997.9.8.1735	journal	November 1997
In situ behaviour of a stiff layered clay subject to thermal loading: observations and interpretation Gens, A.; Vaunat, J.; Garitte, B. Géotechnique, Vol. 57, Issue 2 https://doi.org/10.1680/geot.2007.57.2.207	journal	March 2007
Small Seismic Events in Oklahoma Detected and Located by Machine Learning–Based Models Ma, Xiaofei; Chen, Ting Bulletin of the Seismological Society of America https://doi.org/10.1785/0120220029	journal	September 2022
The December 2018 ML 5.7 and January 2019 ML 5.3 Earthquakes in South Sichuan Basin Induced by Shale Gas Hydraulic Fracturing Lei, Xinglin; Wang, Zhiwei; Su, Jinrong Seismological Research Letters, Vol. 90, Issue 3 https://doi.org/10.1785/0220190029	journal	April 2019
Rainfall–runoff modelling using Long Short-Term Memory (LSTM) networks Kratzert, Frederik; Klotz, Daniel; Brenner, Claire Hydrology and Earth System Sciences, Vol. 22, Issue 11 https://doi.org/10.5194/hess-22-6005-2018	journal	January 2018
The seismo-hydromechanical behavior during deep geothermal reservoir stimulations: open questions tackled in a decameter-scale in situ stimulation experiment Amann, Florian; Gischig, Valentin; Evans, Keith Solid Earth, Vol. 9, Issue 1 https://doi.org/10.5194/se-9-115-2018	journal	January 2018
The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation Chicco, Davide; Warrens, Matthijs J.; Jurman, Giuseppe PeerJ Computer Science, Vol. 7 https://doi.org/10.7717/peerj-cs.623	journal	July 2021

Similar Records

Improving the estimation of atmospheric water vapor pressure using interpretable long short-term memory networks

Journal Article · 2024 · Agricultural and Forest Meteorology · OSTI ID:2294123

Gao, B.; Coon, E. T.; Thornton, P. E.; +1 more

Recognition of ships based on vector sensor and bidirectional long short-term memory networks

Journal Article · 2020 · Applied Acoustics · OSTI ID:1693578

Li, Sichun; Yang, Shuyu; Liang, Jinghan

Modelling the water injection induced fault slip and its application to in-situ stress estimation

Journal Article · 2020 · International Journal of Rock Mechanics and Mining Sciences · OSTI ID:2280094

Shiu, Wenjie; Guglielmi, Yves; Graupner, Bastian; +1 more

Title: Modeling injection-induced fault slip using long short-term memory networks

Citation Formats

References (30)

Similar Records

Related Subjects