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Currently Active Research Projects

GMG-1 (2018) - 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.

GMG-2 (2018) - 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:

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

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-4 (2018) - Understanding conditions for stable/unstable fault slip induced by fluid injections

Experimental plan:

  • 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.
Publications:
Larochelle, S., Lapusta, N., Ampuero, J.-P., & Cappa, F. (2021). Constraining fault friction and stability with fluid-injection field experiments. Geophysical Research Letters, 48, e2020GL091188. https://doi.org/10.1029/2020GL091188. [PDF] *GMGPUB2

GMG-6 (2018) - Experimental investigation of the interaction between fluids and failure of rock faults in shear

Experimental plan:

  • 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

Experimental plan:

  • 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

Experimental plan:

  • 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

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
  • 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.
Experimental plan:
  • 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.

Past Projects

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-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.