| Title | An Inverse Model for Predicting Reservoir Structure and Thermal Lifetime Using Inert and Adsorbing Tracers |
|---|---|
| Authors | Adam J. HAWKINS, Don FOX, Matthew M. BECKER, and Jefferson W. TESTER |
| Year | 2017 |
| Conference | Stanford Geothermal Workshop |
| Keywords | tracers, field studies, inverse methods, thermal breakthrough |
| Abstract | The focus of this research is the development and field testing of an inverse model for predicting the thermal hydraulic performance of fracture-dominated geothermal reservoirs with spatially-varying permeability. The inverse model utilizes Principal Component Analysis (PCA) and a Genetic Algorithm (GA) to identify a representative permeability distribution. Field testing was conducted at a meso-scale field site, referred to as the “Altona field site,” which serves as a geothermal analog. The inverse model identifies a two-dimensional, spatially correlated permeability field by minimizing an objective function relating measured and simulated inert and adsorbing tracer RTDs. The resulting permeability distribution was subsequently used to forecast the spatial distribution of heat transport and predict thermal breakthrough at the production well. A two-spot pattern was utilized with an injection to production well separation of 14 m. The wells are connected by a sub-horizontal fracture at 7.6 m below ground surface. Preliminary results suggest that the inverse model successfully predicts early thermal breakthrough resulting from the continuous circulation of hot water (74 °C) through the relatively cold formation, initially at 11 °C. The identified permeability field suggests that a narrow flow channel (~1-2 m) was responsible for the occurrence of rapid thermal breakthrough. The results are corroborated by Ground Penetrating Radar (GPR) imaging of the target fracture and tracer transport as well as measurements of the spatial distribution of fracture/matrix heat exchange. |