| Abstract |
The Cisolok-Cisukarame geothermal area in Indonesia presents a promising prospect with an estimated power generation potential of 45 MWe. Extensive exploration data, including geological, physical, and chemical properties, as well as results from initial exploration wells, have been accumulated for this area. To facilitate resource development in Cisolok-Cisukarame, it is crucial to systematically identify the most favorable areas for optimal placement of production and reinjection wells, thereby minimizing exploration risk. This study demonstrates a robust approach to well targeting by integrating Play Fairway Analysis (PFA) with Monte Carlo simulation. This combined methodology enables comprehensive data integration, rigorous uncertainty quantification, and a significant reduction in expert subjectivity during the weighting process. In the PFA workflow, essential play elements: heat source, fault location, temperature, reservoir characteristics, fluid pathways, and geophysical data were selected and then, Composite Risk Segment (CRS) maps were generated to delineate favorable areas for each individual parameter. To derive a Common Composite Risk Segment (CCRS) map, representing the final favorable target zones, Monte Carlo simulation was employed for parameter weighting instead of conventional expert judgment. This integrated methodology succeeds in producing probabilistically defined targets, offering a more nuanced and objective understanding of risk than traditional deterministic methods. Finally, three probability maps: pessimistic, most-likely, and optimistic are generated, which consistently specify the Cisukarame area as the most favorable zone for well targeting. |