With the increasing energy demands of current modern society, underground gas storage (UGS) in gas fields is the most popular type of UGS used to meet the seasonal variation of gas consumption. However, compared with gas fields, UGS in gas fields has the characteristics of periodic high-speed injection and production of exploitation modes and operation rules, which causes the rules of gas-water seepage and utilization of reserves to be more particular and complicated. In this paper, based on Wen 23 gas storage, the rules of multicycle injection and production flow and the utilization of UGS pore volume were investigated. The experimental results showed that variation in porosity and permeability caused by injection and production pressure changes in Wen 23 gas storage can be neglected. The pore volume of gas storage and the degree of gas recovery increased gradually in the pre-UGS gas zone, which was higher than that of reservoirs. In the initial stage of UGS operation, the pore volume of gas storage and the degree of gas recovery were low in the gas-drive-water gas zone as a result of water invasion during the process of reservoir exploitation. During operation of multicycle high-speed injection and production, the seepage conditions in the gas-drive-water gas zone gradually improved. The higher the reservoir permeability, the greater increases in pore volume and degree of gas recovery. In the gas-water transition zone, gas and water were reciprocated and displaced with the multicycle injection-production of UGS, resulting in the gradual deterioration of pore volume and gas recovery, which remained stable at a low value. The negative effects of reservoir heterogeneity on the effective utilization of UGS occurred in the gas-water transition zone. These findings may contribute to a better understanding of the rules of multicycle injection and production flow and utilization of UGS to optimize the injection-production efficiency of Wen 23 gas storage.

The influence of geological and engineering factors results in the complex production characteristics of shale gas wells. The productivity evaluation method is effective to analyze the production decline law and estimate the ultimate recovery in the shale gas reservoir. This paper reviews the production decline method, analytical method, numerical simulation method, and machine learning method. which analyzes the applicable conditions, basic principles, characteristics, and limitations of different methods. The research found that the production decline method can mainly account for the gas well production and pressure data by fitting type curve analysis. The analytical method is able to couple multiple transport mechanisms and quantify the impact of different mechanisms on shale gas well productivity. Numerical simulation builds multiple pore media in shale gas reservoirs and performs production dynamics as well as capacity prediction visually. Machine learning methods are a nascent approach that can efficiently use available production data from shale gas wells to predict productivity. Finally, the research discusses the future directions and challenges of shale gas well productivity evaluation methods.

The movable water saturation of tight sandstone reservoirs is an important parameter in characterizing water production capacity, and there is a great need to understand the relationship between movable water saturation and water production characteristics. However, movable water behavior in this context remains unclear. In this study, four groups of tight sandstone cores from the Sulige gas field are measured to understand the movable water saturation characteristics. Then, the effects such as reservoir micropore throat, clay mineral and physical properties on movable water saturation are analyzed, and the movable water saturation and water production characteristics are discussed. The results show that higher movable water saturation will result in a greater amount of water in the gas drive. There is a critical pressure difference of the gas drive, and a large amount of movable water will flow out. Movable water saturation is independent of the porosity, permeability and initial water saturation, while it is closely related to the reservoir micropore throat and clay mineral content. Movable water is mainly distributed in the medium and large pores; the larger the proportion of such pores, the higher the degree of movable water saturation. A lower mineral content will lead to higher movable water saturation in tight sandstone gas reservoirs. These results provide clues for identifying gas–water bearing reservoirs and evaluating and predicting the water production characteristics in gas wells in tight sandstone gas reservoirs.

Shale reservoir heterogeneity is strong, which seriously affects shale gas reservoir evaluation and reserves estimation. The Longmaxi Formation shale of the Luzhou block in southern Sichuan was taken as an example to characterize the pore distribution of shale over the full scale using micro-computed tomography (CT), focusing on ion beam scanning electron microscopy (FIB-SEM) and small-angle neutron scattering (SANS); further, the heterogeneity of the shale pore distribution over the full scale was explored quantitatively within different scales. The results show that shale micropores are dominated by microfractures that are mainly developed along the bedding direction and associated with organic matter, contributing 1.24% of porosity. Shale nanopores are more developed, contributing 3.57–4.72% porosity and have strong heterogeneity locally at the microscale, but the pore distribution characteristics show lateral homogeneity and vertical heterogeneity at the macroscale. In the same layer, the porosity difference is only 0.1% for the sheet samples with 2 cm adjacent to each other. Therefore, in shale core experiments in which parallel samples are needed for comparison, parallel samples should be in the same bedding position. This paper explores the extent of heterogeneity over the full scale of pore distribution from macro to micro, which has important significance for accurately characterizing the pore distribution of shale and further carrying out reservoir evaluation and estimation of reserves.

Taking the Longmaxi deep-marine shale gas reservoir in Zigong region as the research target, this paper aimed to characterize the nano-scale pore structure and investigate the reservoirs’ heterogeneity based on fractal theory. By conducting a series of experimental studies, mainly including TOC, XRD, gas adsorption (N₂ and CH₄), we were able to clarify the main controlling factors for the heterogeneity of deep shale pore structure. Our results indicated that the deep marine shale possessed a significant amount of organic matter, as the average TOC value is 3.68%. The XRD analysis results show that quartz and clay were the main mineral types, and the total content of these two minerals averaged 77.5%. Positive correlations were observed between TOC and quartz, while TOC decreases as the clay mineral increases, this discovery indicating that quartz is biogenic. Based on FHH (Frenkele-Halseye-Hill) method, by using the LTNA adsorption isotherms, we took relative pressure P/P₀=0.5 as the boundary, then two separate fractal dimension were deduced, D₁ and D₂ represent the fractal characteristics of small and large pores, respectively. Our study revealed that both D₁ and D₂ demonstrated positive correlations with N₂ adsorption pore volume and adsorption specific surface area, while negatively correlated with the adsorption average pore diameter. Moreover, the two fractal dimensions showed positive associations with TOC and quartz and negative associations with clay. Additionally, D₁ and D₂ also demonstrated a positive correlation with Langmuir volume. The presence of micropores was found to significantly influence the formation of an irregular pore structure in shale. As the pore size decreased, the adsorption specific surface area increased, resulting in a more intricate pore structure, and the fractal dimension of the pores elevated, ultimately. This intricate structure is beneficial for the accumulation of shale gas. These research findings offer valuable insights for the comprehensive assessment of deep shale gas, and enrich our knowledge of enrichment mechanisms in deep shale gas reservoirs.

Unconventional reservoirs have unique characteristics such as low porosity, low permeability, complex pore structure, and strong heterogeneity. Conventional gas–water relative permeability curve determination methods no longer apply to unconventional reservoirs. Therefore, this paper clarifies the necessity of accurately obtaining the gas–water relative permeability curve, investigates a variety of direct measurement and indirect calculation methods suitable for unconventional reservoirs proposed by scholars, concludes the advantages, disadvantages and applicability of various methods, and prospects for the future research direction of the gas–water relative permeability curve determination method. The research results show: (1) The gas–water relative permeability curve has broad applications, and its precise measurement is essential for the efficient and economical development of gas reservoirs. (2) Current research on the unsteady-state method in unconventional reservoir applications generally focuses on improving the experimental method by combining the NMR, CT, and DPT techniques or optimizing the JBN method by considering the threshold pressure gradient, stress sensitivity, and gas slippage effect. (3) When experimenting with relative permeability curves in ultra-low permeability core samples is difficult or impossible, the indirect calculation can be used as an alternative to quickly obtaining numerous relative permeability curves. However, most of the relative permeability determination methods proposed by scholars remain at the laboratory stage, and how to apply them to the field is a significant challenge for current research. Future research should accelerate the development and release of standards for determining relative permeability curves in unconventional reservoirs, continuously improve the reliability verification scheme for relative permeability curve indirect calculation methods in unconventional reservoirs, and actively explore the gas–water relative permeability curve determination method based on machine learning.