Field implementation shows improved fracturing outcomes by integrating microseismic data in tight reservoirs, indicating digital transformation benefits.
Hydraulic fracturing remains the primary technology enabling the economic development of unconventional shale and tight reservoirs. However, operational challenges—including sand blockages, fracture hits, casing deformation, and the lack of integrated real-time diagnostics—continue to limit efficiency and reliability, particularly in deep and geologically complex reservoirs such as those of the Sichuan Basin in China. To address these challenges, the Testing and Fracturing Operation Center (TFOC) platform has been developed as a modular, cloud-native system that integrates real-time hydraulic fracture simulation, AI-driven automatic calibration, and advanced visualization capabilities. The platform provides minute-level fracture propagation updates, automated parameter calibration against live pumping curves, and interactive visualization that combines geological models, discrete fracture networks, and field monitoring data. Field deployment in the Sichuan Basin demonstrated the platform's ability to handle high-resolution geomechanical models (>8 million grid cells), integrate real-time pumping and microseismic data, and quantify fracture geometry and conductivity with improved accuracy. Case studies show how the system captured stress shadow effects, fracture–natural fracture interactions, and stage-by-stage fracture calibration results, thereby reducing parameter uncertainty and enhancing operational decision-making. The TFOC platform represents a step toward predictive, data-driven fracturing operations, supporting improved efficiency, reliability, and alignment with the industry's broader objectives for digital transformation and sustainable resource development.
No takes yet. Share an insight, caveat, or question.
Wu et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: