With the continuous development of conventional oil and gas resources, the strategic transformation of energy structure is imminent. Shale condensate gas reservoir has high development value because of its abundant reserves. However, due to the multi-scale flow of shale gas, adsorption and desorption, the strong stress sensitivity of matrix and fractures, the abnormal condensation phase transition mechanism, high-speed non-Darcy seepage in artificial fractures, and heterogeneity of reservoir and multiphase flows, the multi-scale nonlinear seepage mechanisms are extremely complicated in shale condensate gas reservoirs. A certain theoretical basis for the engineering development can be provided by mastering the percolation law of shale condensate gas reservoirs, such as improvement of productivity prediction and recovery efficiency. The productivity evaluation method of shale condensate gas wells based on empirical method is simple in calculation but poor in reliability. The characteristic curve analysis method has strong reliability but a great dependence on the selection of the seepage model. The artificial intelligence method can deal with complex data and has a high prediction accuracy. Establishing an efficient shale condensate gas reservoir development simulation technology and accurately predicting the production performance of production wells will help to rationally formulate a stable and high-yield mining scheme, so as to obtain better economic benefits.
Multi-stage fractured horizontal wells are extensively used in unconventional reservoir; hence, optimizing the spacing between these hydraulic fractures is essential. Fracture spacing is an important factor that influences the production efficiency and costs. In this study, maximum fracture spacing in low-permeability liquid reservoirs is studied by building an integrated flow model incorporating key petrophysical characteristics. First, a kinematic equation for non-Darcy seepage flow is constructed using the fractal theory to consider the non-homogeneous characteristics of the stimulated rock volume area (StRV) and its stress sensitivity (SS). Then, the kinematic equation is used to build an integrated mathematical model of one-dimensional steady-state flow within the StRV to analytically determine the pressure distribution in StRV. The resultant pressure distribution is utilized to propose an optimal value for the maximum fracture spacing. Finally, the effects of fractal index, initial matrix permeability, depletion, and stress sensitivity coefficient on the limit disturbed distance and pressure distribution are studied. This study not only enriches the fundamental theory of nonlinear seepage flow mechanics but also provides some technical guidance for choosing appropriate fracture spacing in horizontal wells.
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