1 College of Petroleum Engineering, China University of Petroleum-Beijing, Beijing 102249, China 2 Petroleum Exploration & Production Research Institute, SINOPEC, Beijing 100083, China
Deep shale formations are so tight and low permeable that large-scale hydraulic fracturing technology is used to increase production to achieve economic development, and the inversion method of fracture network parameters is an important means of evaluation of hydraulic fracturing performance and gas well productivity analysis. The existing fracture network parameter inversion methods do not consider the influence of uneven distribution of proppant in fractures and gas-water two-phase seepage on the development of deep shale gas reservoirs after hydraulic fracturing, resulting in considerable error in parameter inversion, and it is difficult to distinguish the contribution of “near-well propped fractures” and “far-well unpropped fractures” to productivity. To solve this problem, based on the dynamic analysis method, a gas-water two-phase fracture network parameter inversion method is established for deep shale gas reservoirs considering multiple nonlinear flow mechanisms and incompletely propped fractures. In the inversion method of fracture network parameters, based on the assumption of the linear flow model, the complex fracture network formed after hydraulic fracturing is equivalent to four areas: propped artificial fracture, fracture stimulated inner formation, unpropped artificial fracture and fracture stimulated outer formation. Variable substitution, perturbation transformation, and successive substitution are used to deal with the nonlinearity caused by high-pressure gas physical parameters, supercritical adsorption, stress sensitivity, non-Darcy seepage and gas-water two-phase seepage. The reliability of the method is verified by numerical simulation, and four deep shale gas wells in the Sichuan Basin are selected for application analysis. The results show that the parameter inversion method established considers the influence of gas-water co-production on productivity prediction and parameter inversion, and can quantitatively distinguish between propped and unpropped fractures with parameters such as half-length and permeability, providing theoretical guidance for accurate prediction of deep shale gas production and evaluation of fracturing effects.
