Lab-Supported Hypothesis and Mathematical Modeling of Crack Development in the Fluid-Soaking Process of Multi-Fractured Horizontal Wells in Shale Gas Reservoirs

Energies

Rashid Shaibu¹  Boyun Guo¹  Zhiyong Huang² 

[1] Department of Petroleum Engineering, University of Louisiana at Lafayette, Lafayette, LA 70504, USA;School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China;

关键词: shale;    gas;    fracture;    shut-in;    soaking;    modeling;   

DOI  :  10.3390/en13051035

来源: DOAJ

【 摘 要 】

The objective of this study is to develop a technique to identify the optimum water-soaking time for maximizing productivity of shale gas and oil wells. Based on the lab observation of cracks formed in shale core samples under simulated water-soaking conditions, shale cracking was found to dominate the water-soaking process in multi-fractured gas/oil wells. An analytical model was derived from the principle of capillary-viscous force balance to describe the dynamic process of crack propagation in shale gas formations during water-soaking. Result of model analysis shows that the formation of cracks contributes to improving well inflow performance, while the cracks also draw fracturing fluid from the hydraulic fractures and reduce fracture width, and consequently lower well inflow performance. The tradeoff between the crack development and fracture closure allows for an optimum water-soaking time, which will maximize well productivity. Reducing viscosity of fracturing fluid will speed up the optimum water-soaking time, while lowering the water-shale interfacial tension will delay the optimum water-soaking time. It is recommended that real-time shut-in pressure data are measured and shale core samples are tested to predict the density of cracks under fluid-soaking conditions before using the crack propagation model. This work provides a shut-in pressure data-driven method for water-soaking time optimization in shale gas wells for maximizing well productivity and gas recovery factor.

【 授权许可】

Unknown