| Title | Utilizing Downhole Drilling Dynamic Data to Characterize Geomechanics of Enhanced Geothermal Reservoirs |
|---|---|
| Authors | Hamed Soroush |
| Year | 2026 |
| Conference | World Geothermal Congress |
| Keywords | drilling, geomechanics. egs |
| Abstract | Here is your revised version, trimmed to **250 words**: --- Enhanced Geothermal System (EGS) development requires detailed subsurface understanding, particularly accurate estimates of geomechanical properties like rock characteristics and in-situ stresses. Traditional methods, relying on well logs or seismic data, often fall short due to limited availability, oversimplified assumptions, and low spatial resolution. To address these limitations, we introduce **Drilling Dynamic Geomechanics (DDG)**—a technique that uses downhole drilling dynamics to generate continuous 1-D stress profiles. DDG leverages standard measurements, including bit vibration and Electronic Drilling Recorder (EDR) data collected during drilling. It is low-cost, requires no extra data acquisition time, and provides high-resolution stress estimates along the entire wellbore, outperforming conventional approaches. The DDG workflow employs a supervised machine learning model grounded in physics and enhanced by signal processing techniques to extract in-situ stress profiles from drilling data. This enables real-time wellbore stability analysis and development of detailed geomechanical models—without relying on traditional logs. Outputs include rock property and stress profiles from surface to total depth, supporting optimized stimulation, completion design, and mitigation of casing deformation. DDG was applied to FORGE Wells 16A(78)-32, 16B(78)-32, and 78B-32 to test its performance in high-temperature geothermal environments. The method achieved \~90% accuracy in predicting rock properties and stresses. Notably, high-temperature effects were reflected in the vibration data, validating DDG’s applicability to geothermal settings. In summary, DDG provides a powerful, real-time tool for characterizing the complex fracture networks critical to efficient EGS development and operation. |