Active and passive seismic monitoring of laboratory-based injection-driven fault reactivation

Research output: Contribution to conferencePaperpeer-review

20 Downloads (Pure)


Robust and reliable prediction of (induced) earthquakes remains a challenging task. Seismicity predictions are made using probabilistic models, precursors such as average earthquake size distribution. Pore pressure variations cause stress perturbations along pre-existing fault planes in the subsurface, resulting in shear slip and seismicity. Monitoring these stress changes before fault reactivation and its resulting seismicity could greatly improve forecasting seismicity. Stress changes can be determined by changes in acoustic or seismic velocities. Therefore, experiments are performed to detect the preparatory phase of an earthquake using acoustic monitoring. Faulted sandstone samples are reactivated in the laboratory by imposing pore pressure changes by fluid injection under reservoir pressures, while continuously performing passive and active (transmission) acoustics measurements. Using coda wave interferometry (CWI) and decorrelation (K), changes in velocity and scattering are obtained before and during fault reactivation. We show that fault reactivation can be identified by a large velocity drop and an increase in K or by micro-seismic foreshocks. We show that CWI velocity change is most sensitive to both the preparatory phase and the fault reactivation. These results show acoustic monitoring of fault reactivation in the laboratory is feasible, which could improve the prediction of induced seismicity.
Original languageEnglish
Number of pages5
Publication statusPublished - 2023
Event84th EAGE ANNUAL Conference and Exhibition 2023 - Vienna, Austria
Duration: 5 Jun 20238 Jun 2023
Conference number: 84


Conference84th EAGE ANNUAL Conference and Exhibition 2023
Abbreviated titleEAGE 2023


Dive into the research topics of 'Active and passive seismic monitoring of laboratory-based injection-driven fault reactivation'. Together they form a unique fingerprint.

Cite this