Paper presented at the SPE Europe Energy Conference and Exhibition, Istanbul, Turkey, June 2026. Paper Number:SPE-233334-MS

Accurate knowledge of the subsurface geothermal gradient is critical to geothermal and high-pressure/high-temperature (HPHT) drilling operations, directly affecting downhole equipment reliability, wellbore integrity, and production optimization. Traditional methods for estimating this gradient rely on dedicated temperature logging runs, adding cost and operational complexity to well construction programs.

This work introduces a hybrid framework that estimates the geothermal gradient in real time using data already generated during routine drilling operations. By combining pump rate, surface mud inlet and return temperatures, and/or bottomhole circulating temperature (BHCT) with well contextual inputs such as drillstring configuration, casing and cement program, and fluid and formation properties, the method drives a physics-based finite-volume thermal model. An iterative optimization routine continuously refines the gradient estimate as drilling progresses and the well deepens.

The framework was validated against open-source datasets from the Utah FORGE site and additional European geothermal fields, showing reliable performance across gradients from 16.5 to 43.9 °F/kft (30 to 80 °C/km), covering most geothermal and HPHT scenarios encountered in practice. It also proved robust to missing or degraded temperature data and ran 10 to 100 times faster than real time, making it well suited for real-time rig-site deployment and operational decision support.