| Title | Seismoelectric Effects for Geothermal Resources Assessment and Monitoring: Overview and Preliminary Results |
|---|---|
| Authors | Christina MORENCY, Eric MATZEL, Niels GROBBE, Daniel BRITO, Clarisse BORDES, Natael BERNARDO, Helene BARUCQ, Julien DIAZ, Arjeta HETA, Mathieu BELLANGER, Mathieu AUXIETRE, Kirsti MIDTTOMME, Walter WHEELER, Roman BERENBLYUM, Bjarte FAGERAS |
| Year | 2022 |
| Conference | Stanford Geothermal Workshop |
| Keywords | seismoelectric effects, numerical modeling, laboratory experiment, field deployment, monitoring, Geothermica |
| Abstract | Geothermal power plant operations circulate large amounts of fluid through the subsurface, but during the exploration phase, we typically have poor understanding of subsurface fluid transportation dynamics at reservoir depths. Being able to identify pre-existing water-filled fracture networks greatly helps to assess geothermal resources and targets. Mapping newly activated fracture networks can also help inform on and monitor stimulation successes and risk mitigation. Monitoring of geothermal resources rely predominantly on seismic techniques, which alone do not capture fluid-phase properties, while on the other hand, electromagnetic (EM) measurements add constraints to the fluid-phase properties, such as resistivity and permeability, but with little sensitivity to the rock structure. Here we are introducing the use of seismoelectric effects (SEE). These are pore-scale phenomena relying on electric charge separation created by streaming currents generated by pressure gradients, which occur when a seismic wave propagates. The SEE technique provides the benefits of both EM and seismic technologies, with estimated field survey costs that are similar to data acquisition of only a single data type, keeping operations affordable. This project relies on a fully integrated approach to assess the potential of SEE for the exploration and development of geothermal systems, based on numerical simulations, and experimental and field analysis. In the following, we validate the numerical implementation of SEE by showing agreement with the theory describing the existence of three types of SEE signals. We also show preliminary results for the laboratory and field experiments. |