Extended Decline Models Improve Geothermal Temperature Forecasting
Mina Khalaf et al. (submitted Jan 2, 2026) propose physics-consistent extended Arps decline curves and equation-informed surrogates to forecast temperatures in Enhanced Geothermal Systems. They validate the equilibrium-temperature-augmented decline family against Utah FORGE measurements and THM simulations, then train an equation-informed neural network, Gaussian Process surrogate, and XGBoost baseline; GP achieves RMSE 3.39°C and MAE 2.34°C across 3–60 month horizons. Implication: provides calibrated, efficient multi-horizon forecasting tools for EGS design and operations.
Scoring Rationale
Strong methodological novelty and practical surrogates for geothermal forecasting, limited by single-source preprint and narrow domain focus.
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