Desarrollo de un workflow integrado entre softwares de modelización de reservorios (MRST) y de simulación técnico-económica (GEOPHIRES) para la evaluación de sistemas geotérmicos con análisis de sensibilidad. Estudio sobre el modelo geotermal en 3D de la Fossa del Camp

Abstract

The open-source evaluation of deep geothermal projects with industrial applications faces a structural gap between subsurface reservoir conditions and its surface financial analysis, which has traditionally been bridged through manual and inefficient tool coupling. This work develops, implements, and validates an automated workflow for the coupling of computational tools, orchestrated via Python. The workflow integrates the 3D thermo-hydraulic reservoir simulation of the MRST (MATLAB Reservoir Simulation Toolbox) software with the techno-economic evaluation engine provided by GEOPHIRES-X. This eliminates human intervention in data integration, transforming simulations into auditable, traceable, and reproducible numerical processes. The architecture of the developed workflow relies on advanced sequential control through on-disk data serialization and synchronous batch-mode calls. It incorporates an algorithmic bypass of GEOPHIRES-X, overriding its native homogeneous subsurface simplifications to enforce the direct assimilation of petrophysical data and CAPEX correction factors calculated in MRST. To validate the workflow and the necessity of this coupling, the pipeline was applied to a case study in the Jurassic aquifer of La Fossa del Camp (Tarragona, Spain), a carbonate basin with an estimated geothermal resource at a depth of 2,000–3,000 meters, with temperatures ranging from 70–90 °C and high permeabilities of up to 2,930 mD. This case evaluates a J-type directional doublet with a 1,200-meter well separation designed to supply industrial heat to the Mas Batller industrial park in Reus over a 30-year operational horizon. The main result is the quantification of the bias introduced by analytical models when applied to heterogeneous basins. The standalone GEOPHIRES analytical model overestimates the NPV by more than tenfold and underestimates the LCOH by 72% relative to the coupled workflow results. This divergence is caused by the software's inability to capture the real confinement of the thermal plume, alongside the petrophysical and geometric characteristics of the system. Consequently, the actual extracted thermal power is reduced by 39%, triggering cascading errors across other financial indicators. This discrepancy shifts the project's classification from highly profitable to marginally viable, a finding evidenced by the implemented parametric sensitivity analysis (OFAT). The analysis demonstrates that the reservoir's high transmissivity renders the local geology a non-limiting variable. This shifts the financial risk toward the operational efficiency of the surface plant, where the production flow rate and reinjection temperature emerge as parameters with the greatest leverage on the evaluated financial indicators. In conclusion, the developed workflow establishes itself as a transferable and open-source methodological contribution, remaining entirely reservoir-agnostic. Its primary value lies in demonstrating that the gap between physical simulation and techno-economic evaluation using open-source tools directly distorts the financial reliability of geothermal projects, mitigating risks in capital allocation.