Completed Projects

Projects

GMG-1 (2018 - 2021) - Infrastructure system resiliency via InSAR ground deformation monitoring

Experimental plan:

Identify ground deformation (landslides, settlement) in Los Angeles affecting the risk of water infrastructure.
Develop automated process of deformation map retrieval using interferometric data and image correlation.
Compare with ground-based measurements from state-of-practice site surveying of said features.

Publications:

Li, B. Q., Khoshmanesh, M., & Avouac, J.-P. (2021). Surface deformation and seismicity induced by poroelastic stress at the Raft River geothermal field, Idaho, USA. Geophysical Research Letters, 48, e2021GL095108. https://doi.org/10.1029/2021GL095108 [PDF] *GMGPUB5

GMG-2 (2018 - 2021) - Seismicity due to hydraulic stimulation for geothermal energy production.

Experimental plan:

WP1: Develop a code to model thermo-poro-elastic stress variations and deformation due to fluid injection. (Y1)
WP2: Use Observations from Brawley to test/calibrate the model and analyze the relation to seismicity (Y1)

Publications:

Im, K. & Avouac, J.P., (2021). On the role of thermal stress and fluid pressure in triggering seismic and aseismic faulting at the Brawley Geothermal Field, California, Geothermics, 97. [PDF] *GMGPUB7

Im, Kyungjae and Avouac, Jean-Philippe (2021) Tectonic tremor as friction-induced inertial vibration. Earth and Planetary Science Letters, 576 . Art. No. 117238. ISSN 0012-821X. doi:10.1016/j.epsl.2021.117238. [PDF] *GMGPUB6

Im, K., Avouac, JP., Heimisson, E.R. et al. Ridgecrest aftershocks at Coso suppressed by thermal destressing. Nature 595, 70–74 (2021). https://doi.org/10.1038/s41586-021-03601-4 https://rdcu.be/cnuGU *GMGPUB4

Avouac, J-P, Vrain, M., Kim, T., Smith, J., Ader, T., Ross, Z., Saarno, T., (2021) A Convolution Model for Earthquake Forecasting Derived from Seismicity Recorded During the ST1 Geothermal Project on Otaniemi Campus, Finland, Proceedings World Geothermal Congress. [PDF] *GMGPUB3

GMG-3 (2018) - Relating ground subsidence, seismicity and reservoir operations at Groningen

Experimental plan:

WP1: Enhanced seismicity seismicity catalog with AI methods for phase detection, association, & EQs location
WP2: Use production data to estimate pore pressure, assimilating surface subsidence information. Test effect of heterogeneities of elastic properties.

GMG-5 (2018-2019) - Modeling and simulation of hydraulic fracturing processes, microseismicity, and environmental impact

Experimental plan:

Further validate MMHF against imaging experiments..
Apply MMHF to estimate fracking performance in the desired settings.
Apply MMHF to estimate fracking fluid leak off to nearby groundwater formations.

GMG-7 & 8 (2018) - Microseismic Monitoring with Deep Learning

Experimental plan:

Adapt the method for vertical only data. Apply to SAF and SBB arrays, and the geothermal data.

Publications:

Smith, Jonthan D. and Ross, Zachary E. and Azizzadenesheli, Kamyar et al. (2022) HypoSVI: Hypocentre inversion with Stein variational inference and physics informed neural networks. Geophysical Journal International, 228 (1). pp. 698-710. ISSN 0956-540X. doi:10.1093/gji/ggab309. [PDF]

Smith, Jonathan D. and Azizzadenesheli, Kamyar and Ross, Zachary E. (2021) EikoNet: Solving the Eikonal Equation with Deep Neural Networks. IEEE Transactions on Geoscience and Remote Sensing, 59 (12). pp. 10685-10696. ISSN 0196-2892. doi:10.1109/TGRS.2020.3039165. https://resolver.caltech.edu/CaltechAUTHORS:20200526-084219717 *GMGPUB10.

GMG-10 (2020) - Characterizing geothermal tremor

Experimental plan:

WP1: Noise discrimination study source-path-receiver analysis to discriminate what resonances are not associated with geothermal tremor (e.g., environmental or anthropogenic).
WP2 Time-frequency analysis. a search for relationships between injection / production flow and pressure changes and amplitude / frequency responses.
WP3: Numerical model building of sources. Use known geothermal reservoir rock and fluid properties (e.g., viscosity), well-field performance (e.g., flow rate) and known crack-wave (e.g., Krauklis waves) and fluid-flow physics (e.g., turbulent flow) to iteratively forward model for geothermal tremor by perturbing fracture properties (e.g., fracture width, aperture and geometry).

Publications:

Im, Kyungjae and Avouac, Jean-Philippe (2021) Tectonic tremor as friction-induced inertial vibration. Earth and Planetary Science Letters, 576. Art. No. 117238. ISSN 0012-821X. https://doi.org/10.1016/j.epsl.2021.117238. [PDF] *GMGPUB6.
Kyungjae Im, Jean-Philippe Avouac, (2022). "Linear stability analysis of the condition for vibration during frictional slip". Journal of the Mechanics and Physics of Solids, Volume 167, 104993, ISSN 0022-5096. https://doi.org/10.1016/j.jmps.2022.104993. [PDF]

GMG-12 (2022-2024) - A vertically integrated model of coupled multiphase flow and multiphysics to enable real-time forecasting of carbon storage

Experimental plan:

WP 1: Incorporate real thermodynamic properties of CO2 into single-phase flow model to understand how initial temperature and in-situ pressure variations impact pressure diffusion in the Gronnigen site;
WP 2: Implement the vertically-integrated two-phase flow framework proposed by Jenkins et al 2019 to simulate two-phase injection into a single aquifer layer of uniform thickness;
WP 3: Extend the model to consider two-phase injection into a single aquifer layer of variable thickness, hydraulic and elastic properties.Test this model using parameters from the Gronnigen site.
WP 4: Incorporate the new model into the seismicity forecasting framework at GMG (Smieth et al. 2022).

Publications:

Mateo Acosta, Thomas Ledevin, Guillaume Salha, Charles Forestier, Lucie Michelin, Xiaojing Fu, Jean-Philippe Avouac (2025). Flow2Quake, an integrated multiphase flow, geomechanical and seismicity model for efficient forecasting of injection and extraction induced earthquakes. International Journal of Greenhouse Gas Control. Volume 145. https://doi.org/10.1016/j.ijggc.2025.104388

GMG-EP-1 (2019-2020) (funded by Total): Evaluation of the effect of pore pressure diffusion and poro-elastic stress on seismicity induced by fluid injections.

Experimental plan:

WP1: Application of machine learning algorithms to detect and located induced earthquakes, using in particular sites in West Texas. Estimate stress variations due to pore pressure diffusion and poroelastic effect and assess the relationship to seismicity.

Publications:

Li, B., Avouac, J-P., Ross, Z., Du, J., Rebel, E., (2020) Induced seismicity in the Dallas-Fort Worth Basin: Enhanced seismic catalogue and evaluation of fault slip potential, SEG Technical Program Expanded Abstracts 2020. September 2020, 1304-1308. https://library.seg.org/doi/10.1190/segam2020-3428222.1 *GMGPUB1