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Sedimentary petroleum basins are increasingly targeted for brownfield geothermal development due to existing infrastructure and subsurface data availability. However, basin-scale screening commonly relies on deterministic temperature corrections and assumed production rates, potentially overestimating electrical feasibility. This study develops a probabilistic thermal-hydraulic framework that treats bottom-hole temperature (BHT) correction method as an explicit epistemic uncertainty and propagates thermal and petrophysical variability through Monte Carlo simulation into geothermal gradient, heat-flow, volumetric heat-in-place, and Organic Rankine Cycle (ORC) power distributions. The framework is applied to 69 wells in the Cambay Basin, India. While ∼96% of wells meet the minimum thermal lift required for binary-cycle operation, Darcy-constrained flow modeling reveals that hydraulic deliverability fundamentally limits power generation. Under matrix permeability conditions typical of Cambay sandstones (permeability of 0.5–3 mD), basin-wide mean electrical output collapses to ∼7.5 kW per well, and no wells exhibit >50% probability of exceeding 500 kW. Inverted modeling indicates that 500 kW generation requires a mean permeability of ∼400 mD and sustained mass-flow rates of ∼25 kg/s, exceeding matrix permeability by one to two orders of magnitude. Variance-based sensitivity analysis demonstrates that permeability-controlled mass flow dominates ORC power uncertainty (| ρ | ≈ 0.83), surpassing correction-scheme variability (| ρ | ≈ 0.42). These findings show that thermal sufficiency does not imply commercial feasibility in millidarcy-scale sedimentary reservoirs. Uncertainty-aware, transmissivity-constrained assessment provides a transferable framework for realistic brownfield geothermal evaluation.
Monmohan Gogoi (Fri,) studied this question.