A Dynamic Continuum Phase-Field Framework for Electro-Hydraulic Pulse-Power Fracturing

Abstract

The global transition to sustainable energy demands innovative technologies that enhance the efficiency and scalability of renewable resource utilization. Subsurface stimulation offers a promising pathway to accelerate heat exchange in geothermal reservoirs. However, conventional hydraulic fracturing technology remains constrained by packer leakage, flow short-circuiting, and limited fracture surface area. To address these challenges, dynamic fracturing using pulsed power has been proposed to enable more efficient, controllable, and sustainable stimulation of subsurface resource extraction. Pulsed power fracturing experiments have been reported in the literature, but the conversion efficiency of electrical energy into mechanical energy that drives rock fracture, especially in multiple pulses scenarios, remains insufficiently understood due to the dynamic nature of the process in microseconds. Moreover, because rocks are naturally fluid-infiltrated, the coupled interaction between fracture propagation and fluid flow has yet to be systematically analyzed and compared with pure solid descrption. To address these challenges, this study introduces a three-dimensional dynamic continuum modeling framework that fully couples the phase-field fracture method with fluid flow and evolving hydro-mechanical properties. Using empirical relationships extracted from existing literature, we capture the fracturing dynamics on the microsecond timescale, representing the pulse power as a time-dependent, depth-varying mechanical pressure applied on the borehole boundary. The implementation is validated against laboratory experiments on both dry and fluid-saturated rock samples. Finally, we evaluate the governing factors controlling fracture surface enhancement and energy conversion efficiency. We assess the complete energy budget under multiple pulsing conditions. The findings provide insights into the fundamentals of pulsed power fracturing, reveal energy partitioning mechanisms, and identify key factors to improve efficiency and scalability to field applications.