A large proportion of shale gas is in adsorbed state. However, in the process of shale gas development, adsorbed gas in the shale pores will gradually desorb, which results in the permeability change of shale. This study aims to find out the adsorption and desorption characteristics of shale and whether there exists certain impact of desorption effects on shale permeability by experiments. Isothermal adsorption and desorption curves of shale gas are not coincident and the desorption curves are in hysteresis. Langmuir equation can be used to calculate the shale isothermal adsorption curve and desorption equation can be used to calculate the shale gas isothermal desorption curve. The permeability of shale was measured, respectively, under low pressure and high pressure, with methane and helium as experimental gas. Then, the comparison was made between the results of shale and the similar experiment results of tight gas sandstone. The results are showed as follows: adsorption effects will break the linear relationship between the shale permeability and the reciprocal of average pore pressure under low pressure; under high pressure, when gas desorption enhances, shale permeability significantly increases. Therefore, adsorption effects can impact the shale permeability under low pressure as well as under high pressure, which should be taken into consideration in the shale gas development.

Three-dimensional (3D) geological property modeling is used to quantitatively characterize various geological attributes in 3D space based on geostatistics with the help of computer visualization technology, and the results are often stored in grid data. The 3D geological property modeling includes two main components, grid model generation and property interpolation. In this review article, the existing grid generation methods are systematically investigated, and both traditional and multiple-point geostatistical algorithms involved in interpolation methods are comprehensively analyzed. It is shown that considering the numerical simulation of oil reservoirs, the orthogonal hexahedral grid remains the most suitable grid model for simulations in petroleum exploration and development. For the interpolation methods aspect, most geological phenomena are nonstationary, to simulate various types of reservoirs; the main development trends are increasing geological constraints and reducing the limitation of stationarity. Both methods have certain constraints, and the multiscale problem of multiple-point geostatistics poses a main challenge to the field. In addition, the deep-learning based method is a new trend in geological property modeling.

As an important type of unconventional hydrocarbon, tight sandstone oil has great present and future resource potential. Reservoir quality evaluation is the basis of tight sandstone oil development. A comprehensive evaluation approach based on the gray correlation algorithm is established to effectively assess tight sandstone reservoir quality. Seven tight sandstone samples from the Chang 6 reservoir in the W area of the AS oilfield in the Ordos Basin are employed. First, the petrological and physical characteristics of the study area reservoir are briefly discussed through thin section observations, electron microscopy analysis, core physical property tests, and whole-rock and clay mineral content experiments. Second, the pore type, throat type and pore and throat combination characteristics are described from casting thin sections and scanning electron microscopy. Third, high-pressure mercury injection and nitrogen adsorption experiments are optimized to evaluate the characteristic parameters of pore throat distribution, micro- and nanopore throat frequency, permeability contribution and volume continuous distribution characteristics to quantitatively characterize the reservoir micro- and nanopores and throats. Then, the effective pore throat frequency specific gravity parameter of movable oil and the irreducible oil pore throat volume specific gravity parameter are introduced and combined with the reservoir physical properties, multipoint Brunauer-Emmett-Teller (BET) specific surface area, displacement pressure, maximum mercury saturation and mercury withdrawal efficiency parameters as the basic parameters for evaluation of tight sandstone reservoir quality. Finally, the weight coefficient of each parameter is calculated by the gray correlation method, and a reservoir comprehensive evaluation indicator (RCEI) is designed. The results show that the study area is dominated by types II and III tight sandstone reservoirs. In addition, the research method in this paper can be further extended to the evaluation of shale gas and other unconventional reservoirs after appropriate modification.

As an emerging unconventional energy resource, shale gas has great resource potential and developmental prospects. The effective evaluation of geological sweet spots (GSS), engineering sweet spots (ESS) and comprehensive sweet spots (CSS) is one of the main factors for a high-yield scale and economic production of shale gas. Sweet spot evaluation involves a comprehensive analysis based on multiple parameters. Conventional evaluation methods consider relatively simple or single factors. Although the main influencing factors are understood, the influence of different factors is as of yet unknown, and a comprehensive consideration may strongly affect the evaluation results. In this paper, the fuzzy mathematics method is introduced for shale gas sweet spot evaluation. With the help of fuzzy mathematics tools, such as membership function, the objective of comprehensive sweet spots evaluation based on multiple parameters is realized. Additionally, the reliability of the evaluation of sweet spots is improved. Firstly, previous research results are used for reference, and the evaluation factor system of geological and engineering sweet spots of shale gas is systematically analyzed and established. Then, the basic principle of the fuzzy comprehensive evaluation method is briefly introduced, and a geological engineering integrated shale gas sweet spots evaluation method, based on the fuzzy comprehensive evaluation method, is designed and implemented. Finally, the data from HB blocks in the Z shale gas field in China are adopted. According to the evaluation results, the modified method is tested. The results show that the method proposed in this paper can synthesize a number of evaluation indices, quickly and effectively evaluate the GSS, ESS and CSS in the target area, and the results have high rationality and accuracy, which can effectively assist in well-pattern deployment and fracture design.

The estimated ultimate recovery (EUR) of shale gas is an important index for evaluating the production capacity of horizontal wells. The Weiyuan shale gas field has wells with considerable EUR differentiation, which hinders the prediction of the production capacity of new wells. Accordingly, 121 wells with highly differentiated production are used for analysis. First, the main control factors of well production are identified via single-factor and multi-factor analyses, with the EUR set as the production capacity index. Subsequently, the key factors are selected to perform the multiple linear regression of EUR, accompanied by the developed method for well production prediction. The thickness and drilled length of Long 1₁¹ (Substratum 1 of Long 1 submember, Lower Silurian Longmaxi Formation) are demonstrated to have the uttermost effects on the well production, while several other factors also play important roles, including the fractured horizontal wellbore length, gas saturation, brittle mineral content, fracturing stage quantity, and proppant injection intensity. The multiple linear regression method can help accurately predict EUR, with errors of no more than 10%, in wells that have smooth production curves and are free of artificial interference, such as casing deformation, frac hit, and sudden change in production schemes. The results of this study are expected to provide certain guiding significances for shale gas development.

Low-permeability reservoirs are important to the future growth of oil and gas reserves and production in China. Predicting the effective stress, σ_e, in reservoirs is vitally important due to its considerable impact on reservoir development through hydraulic fracturing. This paper presents methods for predicting the σ_e field in ultralow-permeability reservoirs through reservoir–geomechanics coupling, which involve the simulation and coupling of the tectonic stress σ and pore pressure P_p fields based on three-dimensional (3D) geological models. First, 3D geological models were constructed based on basic data for the oilfield where the reservoir of interest is located. Then, finite element and finite difference simulations were performed to construct the σ and P_p fields, respectively, in the reservoir. Different types of initial σ_e were coupled based on 3D geological models. Subsequently, a dynamic σ_e field in the reservoir was established based on oilfield production data in conjunction with the transformation, optimization, and coupling of specific grid property parameters obtained from different numerical methods. Finally, the proposed methods were tested on real-world data acquired from well area X in an oilfield in Shaanxi Province, China. The results show that the proposed methods can be used to establish the σ and P_p fields in a reservoir based on 3D geological models combined with different numerical methods, and subsequently predict the σ_e value in the reservoir.