Investigating Injection Pressure as a Predictor to Enhance Real-Time Forecasting of Fluid-Induced Seismicity: A Bayesian Model Comparison

Feng, Yu1; Mignan, Arnaud1; Sornette, Didier1; Gao, Ke2

2023-03-01

10.1785/0220220309

SEISMOLOGICAL RESEARCH LETTERS   影响因子和分区

0895-0695

1938-2057

Fluid-induced seismicity is now a growing concern in the spotlight and managing its risks entails a probabilistic forecast model suited to real-time applications, which com-monly relies on the operational parameter of injection rate in a nonhomogeneous Poisson process. However, due to potential injectivity change, gas kicks, and other proc-esses, injection rate may not provide as robust a proxy for the forcing process as injec-tion pressure, which embodies fluid-rock interactions. Hence, we present a Bayesian approach to prospective model comparison with parameter uncertainties considered. We tested nine geothermal stimulation case studies to comprehensively demonstrate that injection pressure is indeed the main physical predictor of induced seismicity rel-ative to injection rate, and when combined with the latter as predictors, can give the best-performing model and robustly enhance real-time probabilistic forecasting of induced seismicity. We also discussed the implications of our results for seismic risk management and potential directions for further model improvement.

SCI ; EI

英语

第一 ; 通讯

National Natural Science Foundation of China[U2039202] ; Shenzhen Science and Technology Program[RCBS20210609103200001]

Geochemistry & Geophysics

Geochemistry & Geophysics

WOS:000990328200001

SEISMOLOGICAL SOC AMER

20231313813168

Bayesian networks ; Earthquakes ; Induced Seismicity ; Risk management

Seismology:484 ; Combinatorial Mathematics, Includes Graph Theory, Set Theory:921.4

GEOSCIENCES

Web of Science

1.Southern Univ Sci & Technol, Inst Risk Anal Predict & Management, Acad Adv Interdisciplinary Studies, Shenzhen, Peoples R China
2.Southern Univ Sci & Technol, Dept Earth & Space Sci, Shenzhen, Peoples R China

Feng, Yu,Mignan, Arnaud,Sornette, Didier,et al. Investigating Injection Pressure as a Predictor to Enhance Real-Time Forecasting of Fluid-Induced Seismicity: A Bayesian Model Comparison[J]. SEISMOLOGICAL RESEARCH LETTERS,2023,94(2A):708-719.

Feng, Yu,Mignan, Arnaud,Sornette, Didier,&Gao, Ke.(2023).Investigating Injection Pressure as a Predictor to Enhance Real-Time Forecasting of Fluid-Induced Seismicity: A Bayesian Model Comparison.SEISMOLOGICAL RESEARCH LETTERS,94(2A),708-719.

Feng, Yu,et al."Investigating Injection Pressure as a Predictor to Enhance Real-Time Forecasting of Fluid-Induced Seismicity: A Bayesian Model Comparison".SEISMOLOGICAL RESEARCH LETTERS 94.2A(2023):708-719.