Hamiltonian Monte Carlo to Characterize Induced Earthquakes: Application to a ML 3.4 Event in the Groningen Gas Field and the Role of Prior

Hamiltonian Monte Carlo to Characterize Induced Earthquakes: Application to a ML 3.4 Event in the Groningen Gas Field and the Role of Prior

Abstract The Hamiltonian Monte Carlo algorithm is known to be highly efficient when sampling high‐dimensional model spaces due to Hamilton's equations guiding the sampling process. For weakly non‐linear problems, linearizing the forward problem enhances this efficiency. This study integrates th...

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Bibliographic Details
Main Authors: La Ode Marzujriban Masfara, Cornelis Weemstra
Format: Article
Language:English
Published: American Geophysical Union (AGU) 2024-01-01
Series:Earth and Space Science
Subjects:
moment tensor
induced seismicity
Groningen
inversion
probabilistic
Bayesian
Online Access:https://doi.org/10.1029/2023EA003184

Internet

https://doi.org/10.1029/2023EA003184

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