This research integrates continuous wavelet transform and microseismic data, improving fracture propagation understanding in enhanced geothermal systems.
The primary objective of this study is to enhance the understanding of hydraulic fracture propagation in Enhanced Geothermal Systems (EGS) by integrating advanced diagnostic techniques. The study evaluates closure pressure, analyzes dynamic fracture propagation using a moving reference point and normalized continuous wavelet transform scalogram, and examines water hammer damping. Additionally, it characterizes fracture geometry propagation through microseismic monitoring and fiber-optic strain sensing. This research focuses on the UTAH FORGE EGS project, leveraging its well-characterized reservoir and advanced monitoring capabilities to address challenges in fracture diagnostics and stimulation design. A full integrated data-driven framework is employed to investigate fracture dynamics in the UTAH FORGE EGS reservoir. Continuous wavelet transform (CWT) is applied to pumping data to enhance the identification of closure pressure and fracture propagation dynamics, particularly in noisy or complex pressure data. Microseismic data is analyzed to map the spatial and temporal distribution of fracture events, alongside advanced treating pressure analysis, providing insights into fracture connectivity and activated reservoir volume (ARV). Fiber-optic distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) capture high-resolution strain and temperature variations along the wellbore, enabling real-time monitoring of fracture interactions within the geological framework. Additionally, water hammer effects, identified through CWT, serve as diagnostic tools for assessing fracture complexity and propagation modes. The integration of these datasets offers a comprehensive understanding of fracture behavior and its impact on EGS reservoir performance. The holistic CWT-based analysis introduces a generalized approach for geothermal fracture diagnostics, encompassing the detection of closure pressure, fracture dynamics, and induced fracture complexity. These findings are validated through independent physical measurements, including microseismic data and fiber-optic sensing. Water hammer damping analysis serves as a diagnostic tool for evaluating fracture complexity and propagation behavior, further confirmed by discrete fracture network (DFN) modeling. This integrated approach provides actionable insights for optimizing fracture designs. The results demonstrate how combining these diagnostic techniques enhances the understanding of fracture propagation and its impact on reservoir performance, offering a practical framework for refining stimulation strategies in EGS applications. This study introduces a novel, data-driven holistic methodology for fracture diagnostics in geothermal reservoirs. The application of CWT for enhanced fracture characterization provides improved resolution in identifying closure pressure and dynamic fracture responses. The integration of microseismic and fiber-optic data with treating pressure data creates a robust framework for understanding fracture geometry and propagation in naturally fractured reservoirs. Additionally, the use of water hammer effects as induced fracture complexity diagnostic tools offers new insights into stimulation efficiency, advancing the understanding of fracture complexity in EGS applications. These innovations contribute to the development of optimized fracturing strategies and improved long-term reservoir performance, supporting the sustainable development of geothermal energy resources.
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Gabry et al. (2025) studied this question.
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