The development of unconventional reservoirs has transformed the global energy landscape, primarily driven by advancements in hydraulic fracturing technologies. However, achieving optimal production performance in these complex, ultra-low-permeability formations requires more than conventional stimulation—it demands an integrated approach encompassing candidate selection, fracture treatment design, execution efficiency, and advanced production forecasting. This review synthesizes recent developments in hydraulic fracturing optimization, drawing on field case studies, numerical simulations, and emerging technological innovations. The paper examines best practices for candidate well selection using productivity index (PI) and skin factor analysis, the evolution of fracture design from geometric to geo-engineered completions, and the influence of material selection—such as high-drag proppants and energized fluid systems—on fracture conductivity and proppant transport efficiency. Execution challenges, including limited cluster contribution and non-uniform proppant placement, are addressed through technologies such as under-displacement plugs, diversion agents, and real-time adaptive fracturing strategies. Furthermore, advancements in production forecasting are discussed, with a particular focus on machine learning models, including Auto Regressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, which demonstrate superior predictive performance compared to traditional decline curve analysis. Finally, the review highlights innovations such as Fishbone Drilling to enhance reservoir stimulation and contact area in tight formations. Overall, this study emphasizes the integration of engineered materials, adaptive execution technologies, and data-driven forecasting models as the foundation for intelligent and efficient hydraulic fracturing optimization in unconventional reservoirs.
Hydraulic fracturing unconventional reservoirs fracture design completion efficiency proppants forecasting
| Primary Language | English |
|---|---|
| Subjects | Geological Sciences and Engineering (Other) |
| Journal Section | Review |
| Authors | |
| Publication Date | April 30, 2025 |
| Submission Date | March 30, 2025 |
| Acceptance Date | April 28, 2025 |
| Published in Issue | Year 2025 Volume: 7 Issue: 1 |