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The development of shale-gas reservoirs has been dramatically accelerated with the technical breakthroughs made in the fields of horizontal well drilling and multistage hydraulic fracturing. After being restructured by hydraulic fracturing, the shale reservoir would have a complicated fracture network featuring great randomness. The accurate evaluation of the fracture network structure and the quantitative calculation of the fracturing fluid flowback are keys to the efficient development of shale-gas fields. In this paper, a new fractal seepage model of single fracturing section was established based on the conversion relationship of gas-liquid flow fractal dimension. Then, the sensitivity of model parameters and the flow characteristics of single fracture section were analyzed to determine the reason that gas production “rises first, and then drops down” at the initial production phase. Finally, the mathematical description of the heterogeneity of fracture networks was further proposed based on Fuzzy theory. Case studies in Fuling shale-gas field were performed by means of the Extended Monte Carlo Simulation and the optimal fracturing heterogeneity factors of typical wells are 0.25, 0.10 and 0.15. Compared with the homogeneous model, the accuracies of gas production and water production calculated by heterogeneous model are increased by up to 15% and 20%, respectively.

With the dramatically expanding of the horizontal well drilled and hydraulic fracturing technology, the exploitation of shale gas has entered a new phase. The complex fracture network will be formed during the massive hydraulic fracturing, which is difficult to be described precisely in mathematical models. Based on Fractal theory, a new mathematical description of gas and liquid flow in single stage of hydraulic fracture network is proposed and a BHFP superposition model of multistage fracture network is established to describe the fracture development and distribution information. This BHFP superposition model characterizes the reservoir heterogeneity by Fuzzy statistical method and can easily accomplish the historical matching task of production data by genetic algorithm. Our model has achieved good prediction results in the application of typical production wells in Fuling shale gas field.

Shale gas has become one of the most important unconventional energy sources in ultra-low permeability reservoirs which has unique reservoir properties and exists in the form of free and adsorptive state in the reservoir, forming many kinds of flow mechanism. In this paper, we provide a new method for production data analysis of shale gas well based on the flowing material balance theory. This method can accurately and effectively evaluate the productivity of shale gas wells and the dropdown of formation energy. This new model divides SRV into matrix pressure system and hydraulic fracturing pressure system. Only 5 fitting parameters are needed to complete the productivity evaluation of shale gas well, and the pressure data of matrix system and hydraulic fracturing systems can be calculated by this model. Compared with the Hz Multifrac model in RTA, our model achieves better and more stable evaluation results in the application of typical production wells in many large shale gas fields, such as Fuling, Changning, Eagle Ford and Barnet.