Currently Active Research Projects
GMG-1 (2018) - Infrastructure system resiliency via InSAR ground deformation monitoring
- 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.
GMG-2 (2018) - Seismicity due to hydraulic stimulation for geothermal energy production.
- 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)
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
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
GMG-3 (2018) - Relating ground subsidence, seismicity and reservoir operations at Groningen
- 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-4 (2018) - Understanding conditions for stable/unstable fault slip induced by fluid injections
- Use the existing codes to model a field experiment on fluid injection.
- Develop codes for coupling between evolving compaction/dilation of the fault gouge and fluid flow.
GMG-6 (2018) - Experimental investigation of the interaction between fluids and failure of rock faults in shear
- Conduct controlled and highly instrumented laboratory experiments with fluid injection into a pre-existing fault to study evolution in friction/pore pressure and triggering of fast/slow slip under various conditions
- Measure slip, slip rate, and shear stress evolution along the fault during the injection process.
- Compare measurements with existing theories on the stability of fault slip.
GMG-7 & 8 (2018) - Microseismic Monitoring with Deep Learning
- Adapt the method for vertical only data. Apply to SAF and SBB arrays, and the geothermal data.
GMG-9 (2018) - Application of DAS in monitoring microseismicity and subsurface structure changes
- Use the DAS instrument contributed by OptaSense through GMG to collect data in the Pasadena area.
- Analyze the DAS data and develop new methods in microseismicity detection, and structure monitoring.
- Optimize the data collection and processing procedures to improve the monitoring accuracy and efficiency.
GMG-10 (2020) - Characterizing geothermal tremor
- 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
- 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)
Currently Active Enhancement Projects
GMG-EP-2 (2020-2022) (funded by Shell): Stress-based seismicity forecasting for CO2 storage.
- WP1:Development of a modeling framework to estimate pore pressure, reservoir deformation, and stress variations with uncertainties quantification. Estimate seismicity rate with account for the nucleation process represented using the rate&state formalism.
- WP2: Evaluation of the forecasting performance using the Groningen test case. This task involves the production of a seismicity catalog produced with Machine Learning techniques.
GMG-5 (2018-2019) - Modeling and simulation of hydraulic fracturing processes, microseismicity, and environmental impact
- 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-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.
- 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.