Deep coal-rocks in China are widely distributed and characterized by greater thickness, and coal-rock methane (CRM) resource potentials have been suggested to be huge. In recent years, the exploration and development of deep CRM have achieved major breakthroughs, attracting widespread attention. Based on recently published data, this paper systematically summarizes the exploration and development history, geological and distribution characteristics of the coal-rocks, and the main controlling factors of deep CRM enrichment in China. Deep CRM is mainly widely distributed in the northern and southwestern areas of China and primarily developed in three sets of strata: the Carboniferous, Permian, and Jurassic systems. Deep coal-rocks exhibit high total organic carbon contents, with organic matter types mainly classified as types II₂ and III, generally in the mature to highly mature stages, demonstrating strong gas generation capacity. The maceral composition is dominated by vitrinite, and the industrial composition is primarily fixed carbon, which is classified as high-quality coal. The distribution of sedimentary facies, high thermal evolution degree, development of pores and microfractures, and favorable preservation conditions are significant factors contributing to the high CRM content. The primary occurrence states of deep CRM consist of adsorbed and free states. Under geological conditions, the adsorbed CRM content is mainly controlled by temperature, showing a clear negative correlation, while the reservoir pressure has a lesser impact on CRM content. Based on the analysis of the controlling factors for the enrichment and high production of deep CRM in China, it is concluded that CRM reservoirs can be classified into two accumulation models: self-sourcing and self-reservoiring and endogenous sourcing with external reservoiring.

The western Sulige gas field is a new and key reserve area for the rolling development of the Sulige gas field in China. However, due to the complex gas–water relationship and the difficulty in identifying gas and water formation, the scale and benefit deployment of the gas field are seriously restricted. In particular, almost all of the wells in the area produce water, and no water measurements have been carried out for any single well, which leads to an unclear understanding of the dynamic characteristics of the production wells, thus affecting the productivity calculations of the gas wells and the overall regional productivity evaluation. Based on the testing data for a gas well, the impacts of the reservoir property parameters on the gas and water production were analyzed by combining the production performance and static geological characteristics. It was determined that the physical parameters K, Kh, and φS_g had good positive correlations with gas production but not with water production; thus, effective prediction cannot be obtained for water production in gas well testing. After the analysis of the liquid-loading law, the gas wells were classified into three types: continuous liquid-carrying production, slight liquid-loading, and liquid-loading wells. In general, up to 96% of the gas wells were liquid-loaded. According to the different production performances exhibited in the different stages of the gas wells, five types of methods for diagnosing water production wells were proposed (gas testing, pilot production, gas–liquid two-phase measurement testing, liquid level detection, and production performance analysis), as well as the diagnostic criteria and corresponding solutions. To obtain real-time water production data for each well and investigate the change in the water–gas ratio (WGR) during the whole production process, a water production splitting method for gas wells based on three-dimensional geological modeling and numerical simulation combined with the constraints of the total water production of gas gathering stations was explored and established. The splitting results can be used to evaluate the water and gas productivity of gas wells and determine the best deliquification period. The gas well productivity when water production was considered was about 10% lower than that when water production was not considered. The best deliquification period was determined to be 125 days for wells with small water production, 20 days for wells with moderate water production, and 3 days for wells with serious water production. The results of this study could provide technical support for the scientific evaluation of gas well production indicators, reduction in development costs, and improvement in oil recovery.

During the development of multi-layer tight sandstone gas reservoirs in Ordos Basin, China, it has not been easy to calculate accurately the production of each individual layer in gas wells. However, production allocation provides a vital basis for evaluating dynamic reserves and drainage areas of gas wells and remaining gas distributions of gas layers. To improve the accuracy and reliability of production allocation of gas wells, a new model was constructed based on the seepage equation, material balance equation, and pipe string pressure equation. In particular, this new model introduced the seepage equation with an elliptical boundary to accurately capture the fluid flow characteristics within a lenticular tight gas reservoir. The new model can accurately calculate the production and reservoir pressure of each individual layer in gas wells. In addition, the new model was validated and applied in the Sulige gas field, Ordos Basin. The following conclusions were drawn: First, The gas production contribution rates of pay zones based on the new model are fairly close to the measurements of the production profile logging, with errors less than 10%. Second, The overall drainage area of a gas well lies among those of each pay zone, and the total dynamic reserves of the well are close to the sum of the dynamic reserves of pay zones. Third, Higher permeability may lead to higher initial gas production of the pay zone, but the ultimate gas production contributions of pay zones are affected jointly by permeability and dynamic reserves. Finally, The new model has been successfully applied to the SZ block of the Sulige gas field, in which the fine evaluation of dynamic reserves, drainage areas, gas production, recovery factors, and remaining gas distributions of different layers was delivered, and the application results provide technical support for the future well placement and enhanced gas recovery of the block.

The western Sulige gas field is a new and key reserve area for the rolling development of the Sulige gas field in China. However, due to the complex gas–water relationship and the difficulty in identifying gas and water formation, the scale and benefit deployment of the gas field are seriously restricted. In particular, almost all of the wells in the area produce water and no water measurement has been carried out for any single well, which leads to an unclear understanding of the dynamic characteristics of the production wells, thus affecting the productivity calculations of the gas wells and the overall regional productivity evaluation. Based on the testing data for a gas well, the impacts of the reservoir property parameters on the gas and water production were analyzed by combining the production performance and static geological characteristics. It was determined that the physical parameters K, Kh, and φSg had good positive correlations with gas production but not with water production; thus, effective prediction cannot be obtained for water production in gas well testing. After the analysis of the liquid loading law, the gas wells were classified into three types: continuous liquid carrying production, slight liquid loading, and liquid loading wells. In general, up to 96% of the gas wells were liquid loaded. According to the different production performances exhibited in the different stages of the gas wells, five types of methods for diagnosing water production wells were proposed (gas testing, pilot production, gas–liquid two-phase measurement testing, liquid level detection, and production performance analysis), as well as the diagnostic criteria and corresponding solutions. To obtain real-time water production data for each well and investigate the change of water-gas ratio (WGR) during the whole production process, a water production splitting method for gas wells based on three-dimensional geological modeling and numerical simulation combined with the constraints of the total water production of gas gathering stations was explored and established. The splitting results can be used to evaluate the water and gas productivity of gas wells and determine the best deliquification period. The gas well productivity when water production was considered was about 10% lower than that when water production was not considered. The best deliquification period was determined to be 125 days for wells with small water production, 20 days for wells with moderate water production, and 3 days for wells with serious water production. The results of this study could provide technical support for the scientific evaluation of gas well production indicators, reduction of development costs, and improvement of oil recovery.

The Lower Cambrian shale gas resources in southern China have huge potential. However, the reservoirs generally contain a relatively high content of nonhydrocarbon gases, which has a significant impact on the exploration and development of shale gas. The source of nonhydrocarbon gases in the Lower Cambrian shales has become a research hotspot. Based on recently published data, this paper systematically summarizes the geological and distribution characteristics, gas-bearing properties, and genesis mechanism of Lower Cambrian shale gas in southern China. The Lower Cambrian shales in southern China are widely distributed in the Yangtze Platform. The overall total organic carbon (TOC) content is relatively high. The kerogen type is mainly type I, and the equivalent vitrinite reflectance (EqRo) value ranges from 2.5 to 6.0%. The mineral components of the Lower Cambrian shales are mainly quartz, clay minerals, and carbonate minerals, and the main lithofacies types are mainly siliceous shale and mixed (siliceous-clay) shale. The gas-in-place (GIP) content of the Lower Cambrian shales varies greatly in different regions. Currently, shale gas, mainly composed of CH₄, has only been discovered in the southwestern Sichuan, western Hubei, northeastern Chongqing, and northern Guizhou areas, while in other Yangtze regions, the GIP content of shales is very low or almost nonexistent. The distribution of δ¹³C₁, δ¹³C₂, and δ¹³C₃ in the Lower Cambrian shale gas shows a significant inversion. Among the nonhydrocarbon gases, N₂ mainly originates from atmospheric and/or pyrolysis, CO₂ is mainly of organic origin, while He exhibits typical shell-source characteristics, which may be from the ancient basement and/or the radioactive decay accumulation of U and Th in the shale. On this basis, an evolution model of the Lower Cambrian shale gas was constructed. Hydrocarbon generation in the Lower Cambrian shales can continue until EqRo = 3.5%, after which N₂ is mainly produced. CO₂ is mainly formed in the low mature stage, and the He content shows continuous generation throughout the shale evolution process.

To address the challenges of characterizing commingled production from multiple channel sand layers with varying boundaries and shapes in tight gas reservoirs, a novel Rate Transient Analysis (RTA) model was established based on the principle of equivalent seepage volume (ESV). This model enables the determination of boundary sizes and permeabilities of individual channel sand layers within commingled tight reservoirs using modern production decline analysis theory. The production decline behavior under different channel sizes, numbers, and configurations was systematically investigated through type curve analysis. The results reveal the existence of five distinct stages in the production decline curves for unequal-width channel sands. The intermediate transient flow stage serves as a diagnostic indicator for identifying boundary disparities among layers. Furthermore, reservoirs with smaller boundary distances, fewer wide channel sand layers, and lower thickness proportions of wider channels exhibit poorer productivity and tend to experience accelerated production decline during early and middle transient flow stages. The proposed method provides an effective approach for characterizing boundary parameters of commingled tight reservoirs and offers a theoretical foundation for evaluating individual layer contributions and productivity.