We are excited to announce that our team, Fracwave from the University of Houston, together with collaborators from VERTEX group at the Colorado School of Mines, will present three breakthrough studies at the upcoming SPE Annual Technical Conference and Exhibition (ATCE 2025) in The Woodlands, Texas. Collectively, these contributions showcase how wavelet analysis, deep learning, and real-time drilling intelligence are transforming fracture diagnostics for both unconventional reservoirs and next-generation geothermal systems.
Unlocking SRV with Wavelets and Deep Learning
Tuesday, October 21 (15:15 – 15:45, Station 5 – ePosters)
Calibration of Stimulated Reservoir Volume (SRV) Estimation Using Continuous Wavelet Transform (CWT) and Advanced Deep Learning With Rate Transient Analysis (RTA): A Case Study From The Marcellus Shale (SPE-228059).
We demonstrate how the humble treating pressure signal can be elevated into a powerful diagnostic tool. By marrying wavelet transforms with deep learning, we deliver SRV predictions that align with RTA – without relying on costly microseismic surveys. This scalable, pressure-only workflow pushes shale reservoir diagnostics into the digital age.
Expanding the Frontier with Real-Time Fracture Detection
Monday, October 20 (14:50 – 15:15, Room 342BE)
Real-time Automated Fracture Detection in Geothermal Wells Using Low-cost Drilling Data (SPE-227991).
Presented by VERTEX research group from Colorado School of Mines in collaboration with the University of Houston, this study introduces a novel approach that combines CWT with machine learning to extract fracture signatures directly from low-cost drilling data such as ROP, MSE, and torque. Achieving over 95% predictive accuracy, the workflow enables real-time fracture detection that reduces drilling risks, lowers costs, and accelerates geothermal well construction.
Bringing New Clarity to Utah FORGE Geothermal Stimulation
Wednesday, October 22 (08:55 – 09:20, Room 342BE)
Advanced Fracture Diagnostics in Utah FORGE Enhanced Geothermal Systems (EGS): Integrating Continuous Wavelet Transform (CWT), Microseismic, and Fiber-Optic Data for Enhanced Stimulation Insights (SPE-228063).
Here, we integrate pressure-derived wavelet diagnostics with fiber-optic strain sensing and microseismic catalogs into a holistic framework. This approach provides unprecedented clarity on fracture propagation in high-temperature granite and offers a real-time decision-making lens for one of the world’s most advanced geothermal laboratories.
Why It Matters
Across shale gas and geothermal frontiers, our mission remains the same: turning complex signals into actionable insights. From boosting SRV prediction in the Marcellus to unraveling fracture dynamics in Utah FORGE and enabling real-time drilling intelligence, we are laying the data-driven foundation for smarter, cleaner, and more efficient subsurface energy systems.
We look forward to sharing these advances – and the vision driving them – at ATCE 2025.