| Title | Next Generation Reservoir Modeling for Geothermal Energy and Lithium Recovery |
|---|---|
| Authors | Colleen BARTON, William PETTITT, Tim SALTER, Elena MEYER, Christopher HARPER, Ehsaan NASIR, Amir MORADI, Danny SIMS, William OSBORN, Robert MOORE |
| Year | 2025 |
| Conference | Stanford Geothermal Workshop |
| Keywords | Salton Sea Geothermal Field, Lithium, Reservoir Simulation, Discrete Fracture Networks |
| Abstract | The geothermal resource potential of the Hell’s Kitchen area of the Salton Sea Geothermal Field (SSGF) was evaluated through geological assessment, well modeling, and reservoir simulation to deliver a natural state matched and dynamic reservoir model for estimating geothermal power potential and lithium production. An 8km x 8.5km 3D geomodel centered around the Hell’s Kitchen development area was constructed from ground level down to a base depth that equals a nominal 370C isotherm. The temperature model distinguishes the high geothermal gradient thermal cap from the near isothermal reservoir that is clearly demonstrated in most wells. A review of geochemical properties for the resource defined the key inputs to flow simulation of lithium rich and lithium depleted brines. The main reservoir faults define linear trends likely to host enhanced permeability or upflow of fluid from the base of the reservoir. A Discrete Fracture Network (DFN) model was developed to provide the fracture and fault derived permeability to the dynamic flow model. The DFN model comprises large-scale faults that are described deterministically and smaller scale structures that are described stochastically. Stress-permeability coupling is dynamically computed during DFN model development. To model flow and transport on the regional scale over time, the properties of the network of discrete fractures were upscaled to the geomodel grid. The static model was imported into a commercial reservoir modelling package for dynamic simulation. Modeled pressure distribution at the natural state condition matched measured pressure and salinity data and provided an excellent match to a large spatial distribution of well temperature data. Forecast scenarios, designed to evaluate optimal initial stage production, were simulated for a 30-year forecast of enthalpy and lithium production. Sensitivities to production forecasts were tested for permeability magnitude, well location, and permeability distribution. These sensitivities illuminate the additional data and analyses required to reduce uncertainty in reservoir model forecasting. Results across multiple stages of development, combined with the permeability scenario tests, highlight the importance of gaining greater insight and robust field analyses for the in situ permeability field. The highly robust fit of the model relative to observed data gives a high level of confidence that the integrated geological framework of porosity, fracture and fault permeability, and reservoir flow regimes are being reasonably described. The next-generation techniques used in the modeling process also yielded a model that fits industry experience of the SSGF. |