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In the development of the Fuling shale gas field, for the first time, Well R9-2 was selected for a test of time-phased staged fracturing and refracturing treatments to study the effectiveness of fracturing at each stage for a novel development approach exploration. This paper introduces the design of the experiments, analyzes the results, and provides a follow-up evaluation of the entire development process. As of 9 August 2020, the well had gone through three phases of development. Phase I: time-phased staged fracturing and development for Stages 1–2, 3–4, 5–6, and co-development for Stages 1–6; Phase II: Stages 1–6 were developed once more after refracturing; Phase III: sealing the sections in Stages 1–6, then fracturing and development of Stages 7–19. Pressure build-up tests were conducted during the development of Stages 1–2 and 3–4, and gas production profile logging and microseismic monitoring were performed during the co-development of Stages 1–6. The results show that the combination of time-phased staged fracturing and refracturing treatments can fracture each stage more effectively. The pressure build-up test can effectively obtain the reservoir parameters of developed shale gas wells. The potential of refracturing treatment in a developed well can be identified from the gas production profile logging and microseismic monitoring. The findings are of this study productive for enhanced shale gas recovery; the combined pattern of time-phased staged fracturing and refracturing acts as a direct guideline to future shale gas production.

The simulation of various rock properties based on three-dimensional digital cores plays an increasingly important role in oil and gas exploration and development. The accuracy of 3D digital core reconstruction is important for determining rock properties. In this paper, existing 3D digital core-reconstruction methods are divided into two categories: 3D digital cores based on physical experiments and 3D digital core stochastic reconstructions based on two-dimensional (2D) slices. Additionally, 2D slice-based digital core stochastic reconstruction techniques are classified into four types: a stochastic reconstruction method based on 2D slice mathematical-feature statistical constraints, a stochastic reconstruction method based on statistical constraints that are related to 2D slice morphological characteristics, a physics process-based stochastic reconstruction method, and a hybrid stochastic reconstruction method. The progress related to these various stochastic reconstruction methods, the characteristics of constructed 3D digital cores, and the potential of these methods are analysed and discussed in detail. Finally, reasonable prospects are presented based on the current state of this research area. Currently, studies on digital core reconstruction, especially for the 3D digital core stochastic reconstruction method based on 2D slices, are still very rough, and much room for improvement remains. In particular, we emphasize the importance of evaluating functions, multiscale 3D digital cores, multicomponent 3D digital cores, and disciplinary intersection methods in the 3D construction of digital cores. These four directions should provide focus, alongside challenges, for this research area in the future. This review provides important insights into 3D digital core reconstruction.

Permeability is a critical parameter that reflects the nature of reservoir, playing a crucial role in the development of oil field. It is difficult to accurately calculate the permeability parameter in reservoir evaluation. Capillary pressure curve represents pore-throat size and distribution of reservoir rocks, and as for the porous sandstone, absolute permeability of rock depends primarily on the pore throat distribution. This paper has improved the estimation model for permeability established by Swanson, adding porosity factor, and has successfully established the absolute permeability estimation model for sandstone using Capillary-Parachor parameters. The permeability of 30 rock samples is estimated by using the above-described two kinds of model respectively. The result shows that the permeability estimated by the improved model is in good agreement with the value of permeability of core testing, and has made some improvement in the precision when compared to the permeability estimation model established by Swanson.