Natural Gas Industry B最新文献

{"title":"The influence of stress and natural fracture on a stimulated deep shale reservoir using the boundary element method","authors":"Songze Liao ,&nbsp;Ziming Zhang ,&nbsp;Jinghong Hu ,&nbsp;Yuan Zhang","doi":"10.1016/j.ngib.2025.05.004","DOIUrl":"10.1016/j.ngib.2025.05.004","url":null,"abstract":"<div><div>Hydraulic fracturing plays a critical role in enhancing shale gas production in deep shale reservoirs. Conventional hydraulic fracturing simulation methods rely on prefabricated grids, which can be hindered by the challenge of being computationally overpowered. This study proposes an efficient fracturing simulator to analyze fracture morphology during hydraulic fracturing processes in deep shale gas reservoirs. The simulator integrates the boundary element displacement discontinuity method and the finite volume method to model the fluid-solid coupling process by employing a pseudo-3D fracture model to calculate the fracture height. In particular, the Broyden iteration method was introduced to improve the computational efficiency and model robustness; it achieved a 46.6 % reduction in computation time compared to the Newton-Raphson method. The influences of horizontal stress differences, natural fracture density, and natural fracture angle on the modified zone of the reservoir were simulated, and the following results were observed. (1) High stress difference reservoirs have smaller stimulated reservoir area than low stress difference reservoirs. (2) A higher natural fracture angle resulted in larger modification zones at low stress differences, while the effect of a natural fracture angle at high stress differences was not significant. (3) High-density and long natural fracture zones played a significant role in enhancing the stimulated reservoir area. These findings are critical for comprehending the impact of geological parameters on deep shale reservoirs.</div></div>","PeriodicalId":37116,"journal":{"name":"Natural Gas Industry B","volume":"12 3","pages":"Pages 298-315"},"PeriodicalIF":4.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144501781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CO2 flooding effects and breakthrough times in low-permeability reservoirs with injection–production well patterns containing hydraulic fractures","authors":"Nanlin Zhang ,&nbsp;Bin Cao ,&nbsp;Fushen Liu ,&nbsp;Liangliang Jiang ,&nbsp;Zhifeng Luo ,&nbsp;Pingli Liu ,&nbsp;Yusong Chen","doi":"10.1016/j.ngib.2025.05.007","DOIUrl":"10.1016/j.ngib.2025.05.007","url":null,"abstract":"<div><div>Comprehensive studies on CO₂ breakthrough times and flooding effects are crucial for optimizing CO₂ flooding strategies. This study utilized numerical simulations to investigate the effects of hydraulic fractures, permeability, and CO₂ injection rates on CO₂ breakthrough times and cumulative oil production. Nonlinear relationships among the respective variables were established, with Sobol method analysis delineating the dominant control factors. The key findings indicate that although hydraulic fracturing shortens CO₂ breakthrough time, it concurrently enhances cumulative oil production. The orientation of hydraulic fractures emerged as a pivotal factor influencing flooding effectiveness. Furthermore, lower permeability corresponds to lower initial oil production, while higher permeability corresponds to higher initial daily oil production. When reservoir permeability is 1 mD, oil production declines at 1000 days, and at 2 mD, it declines at 700 days. At a surface CO₂ injection rate of 10,000 m³/d, the daily oil production of a single well is approximately 7.5 m³, and this value remains relatively stable over time. The hierarchical order of influence on CO₂ breakthrough and rapid rise times, from highest to lowest, is permeability, well spacing, CO₂ injection rate, porosity, and hydraulic fracture conductivity. Similarly, the order of influence on cumulative oil production, from highest to lowest, is well spacing, porosity, permeability, CO₂ injection rate, and hydraulic fracture conductivity. This paper analyzed the impact of geological and engineering parameters on CO₂ flooding and oil production and provided insights to optimize CO₂ injection strategies for enhanced oil recovery.</div></div>","PeriodicalId":37116,"journal":{"name":"Natural Gas Industry B","volume":"12 3","pages":"Pages 339-355"},"PeriodicalIF":4.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144501785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on influences of geological and gas source conditions on gas-chimney hydrate accumulation using a reservoir numerical simulation method","authors":"Liang Zhang ,&nbsp;Fuyang Li ,&nbsp;Lu Yu ,&nbsp;Songhe Geng ,&nbsp;Chunjie Li ,&nbsp;Yujie Sun","doi":"10.1016/j.ngib.2025.05.003","DOIUrl":"10.1016/j.ngib.2025.05.003","url":null,"abstract":"<div><div>The Shenhu Area in the South China Sea is rich in oil and gas resources and has many vertical gas chimneys, making it an excellent geological environment for hydrate accumulation. This paper examines the geological conditions governing these gas-chimneys. A numerical simulation method based on the partial-equilibrium reaction model of hydrate was applied to simulate the migration of methane gas and the resultant hydrate formation when the gas enters the hydrate stability zone under the seabed through gas-chimneys. The dynamics of this gas-chimney hydrate accumulation were analyzed, and the influences of different factors—namely, the fluid supply time, rate, and temperature—on the formation temperature and ultimate distribution of the hydrate reservoir were evaluated. The simulation results indicate that the accumulation of hydrate via gas-chimneys is significantly affected by the temperature of the gas source, the transfer state of the methane gas, and the number of cycles of alternating gas–water invasion. Hydrate accumulation takes shape in an annular or semi-annular distribution pattern divided by fluid state as follows: a two-phase gas–water zone, a three-phase gas–water–hydrate zone, a two-phase water–hydrate zone, and a phase of water passing from the inside to the outside. Formation inclination and reservoir heterogeneity can greatly affect the distribution shape and abundance of the hydrate. A high fluid supply temperature, frequent alternating invasions of gas and water, and long-term pore-water invasion at a high rate can jointly cause a large central hydrate-free zone. In contrast, a long-term supply shutdown during the alternating gas–water invasion process, and a high gas rate with a low water rate in the gas-dominant invasion stage, foster the accumulation of hydrate in great abundance and with considerable thickness. The results of this study can help us understand the accumulation of hydrate through gas chimneys in the Shenhu Area.</div></div>","PeriodicalId":37116,"journal":{"name":"Natural Gas Industry B","volume":"12 3","pages":"Pages 279-297"},"PeriodicalIF":4.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144501780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gas occurrence characteristics in marine-continental transitional shale from Shan23 sub-member shale in the Ordos Basin: Implications for shale gas production","authors":"Guangyin Cai ,&nbsp;Yifan Gu ,&nbsp;Dongjun Song ,&nbsp;Yuqiang Jiang ,&nbsp;Yonghong Fu ,&nbsp;Ying Liu ,&nbsp;Fan Zhang ,&nbsp;Jiaxun Lu ,&nbsp;Zhen Qiu","doi":"10.1016/j.ngib.2025.05.009","DOIUrl":"10.1016/j.ngib.2025.05.009","url":null,"abstract":"<div><div>Pore structure characteristics, gas content, and micro-scale gas occurrence mechanisms were investigated in the Shan₂³ sub-member marine-continental transitional shale of the southeastern margin of the Ordos Basin using scanning electron microscope images, low-temperature N₂/CO₂ adsorption and high-pressure mercury intrusion, methane isothermal adsorption experiments, and CH₄-saturated nuclear magnetic resonance (NMR). Two distinct shale types were identified: organic pore-rich shale (Type OP) and microfracture-rich shale (Type M). The Type OP shale exhibited relatively well-developed organic matter pores, while the Type M shale was primarily characterized by a high degree of microfracture development. An experimental method combining methane isothermal adsorption on crushed samples and CH₄-saturated NMR of plug samples was proposed to determine the adsorbed gas, free gas, and total gas content under high temperature and pressure conditions. There were four main research findings. (1) Marine-continental transitional shale exhibited substantial total gas content in situ, ranging from 2.58 to 5.73 cm³/g, with an average of 4.35 cm³/g. The adsorbed gas primarily resided in organic matter pores through micropore filling and multilayer adsorption, followed by multilayer adsorption in clay pores. (2) The changes in adsorbed and free pore volumes can be divided into four stages. Pores of &lt;5 nm exclusively contain adsorbed gas, while those of 5–20 nm have a high proportion of adsorbed gas alongside free gas. Pores ranging from 20 to 100 nm have a high proportion of free gas and few adsorbed gas, while pores of &gt;100 nm and microfractures are almost predominantly free gas. (3) The proportion of adsorbed gas in Type OP shale exceeds that in Type M, reaching 66 %. (4) Methane adsorbed in Type OP shale demonstrates greater desorption capability, suggesting a potential for enhanced stable production, which finds support in existing production well data. However, it must be emphasized that high-gas-bearing intervals in both types present valuable opportunities for exploration and development. These data may support future model validations and enhance confidence in exploring and developing marine-continental transitional shale gas.</div></div>","PeriodicalId":37116,"journal":{"name":"Natural Gas Industry B","volume":"12 3","pages":"Pages 368-385"},"PeriodicalIF":4.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144501787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated wellbore-surface pressure control production optimization for shale gas wells","authors":"Xingyu Zhou ,&nbsp;Liming Zhang ,&nbsp;Ji Qi ,&nbsp;Yanxing Wang ,&nbsp;Kai Zhang ,&nbsp;Ruijia Zhang ,&nbsp;Yaqi Sun","doi":"10.1016/j.ngib.2025.03.011","DOIUrl":"10.1016/j.ngib.2025.03.011","url":null,"abstract":"<div><div>Shale gas wells often face challenges in maintaining continuous and stable production due to their coexistence with high- and low-pressure wells within the same development block, which leads to issues involving mixed-pressure flows. Traditional pipeline optimization methods used in conventional gas well blocks fail to address the unique needs of shale gas wells, such as the precise planning of airflow paths, pressure distribution, and compression. This study proposes a pressure-controlled production optimization strategy specifically designed for shale gas wells operating under mixed-pressure flow conditions. The strategy aims to improve production stability and optimize system efficiency. The decline in production and pressure for individual wells over time is forecasted using a predictive model that accounts for key factors of system optimization, such as reservoir depletion, wellbore conditions, and equipment performance. Additionally, the model predicts the timing and impact of liquid loading, which can significantly affect production. The optimization process involves analyzing the existing gathering pipeline network to determine the most efficient flow directions and compression strategies based on these predictions, while the strategy involves adjusting compressor settings, optimizing flow rates, and planning pressure distribution across the network to maximize productivity while maintaining system stability. By implementing these strategies, this study significantly improves gas well productivity and enhances the adaptability and efficiency of the gathering and transportation system. The proposed approach provides systematic technical solutions and practical guidance for the efficient development and stable production of shale gas fields, ensuring more robust and sustainable pipeline operations.</div></div>","PeriodicalId":37116,"journal":{"name":"Natural Gas Industry B","volume":"12 2","pages":"Pages 123-134"},"PeriodicalIF":4.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid genetic algorithm for parametric optimization of surface pipeline networks in underground natural gas storage harmonized injection and production conditions","authors":"Jun Zhou ,&nbsp;Zichen Li ,&nbsp;Shitao Liu ,&nbsp;Chengyu Li ,&nbsp;Yunxiang Zhao ,&nbsp;Zonghang Zhou ,&nbsp;Guangchuan Liang","doi":"10.1016/j.ngib.2025.03.009","DOIUrl":"10.1016/j.ngib.2025.03.009","url":null,"abstract":"<div><div>The surface injection and production system (SIPS) is a critical component for effective injection and production processes in underground natural gas storage. As a vital channel, the rational design of the surface injection and production (SIP) pipeline significantly impacts efficiency. This paper focuses on the SIP pipeline and aims to minimize the investment costs of surface projects. An optimization model under harmonized injection and production conditions was constructed to transform the optimization problem of the SIP pipeline design parameters into a detailed analysis of the injection condition model and the production condition model. This paper proposes a hybrid genetic algorithm generalized reduced gradient (HGA-GRG) method, and compares it with the traditional genetic algorithm (GA) in a practical case study. The HGA-GRG demonstrated significant advantages in optimization outcomes, reducing the initial cost by 345.371 × 10⁴ CNY compared to the GA, validating the effectiveness of the model. By adjusting algorithm parameters, the optimal iterative results of the HGA-GRG were obtained, providing new research insights for the optimal design of a SIPS.</div></div>","PeriodicalId":37116,"journal":{"name":"Natural Gas Industry B","volume":"12 2","pages":"Pages 234-250"},"PeriodicalIF":4.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mineral identification in thin sections using a lightweight and attention mechanism","authors":"Xin Zhang ,&nbsp;Wei Dang ,&nbsp;Jun Liu ,&nbsp;Zijuan Yin ,&nbsp;Guichao Du ,&nbsp;Yawen He ,&nbsp;Yankai Xue","doi":"10.1016/j.ngib.2025.03.001","DOIUrl":"10.1016/j.ngib.2025.03.001","url":null,"abstract":"<div><div>Mineral identification is foundational to geological survey research, mineral resource exploration, and mining engineering. Considering the diversity of mineral types and the challenge of achieving high recognition accuracy for similar features, this study introduces a mineral detection method based on YOLOv8-SBI. This work enhances feature extraction by integrating spatial pyramid pooling-fast (SPPF) with the simplified self-attention module (SimAM), significantly improving the precision of mineral feature detection. In the feature fusion network, a weighted bidirectional feature pyramid network is employed for advanced cross-channel feature integration, effectively reducing feature redundancy. Additionally, Inner-Intersection Over Union (InnerIOU) is used as the loss function to improve the average quality localization performance of anchor boxes. Experimental results show that the YOLOv8-SBI model achieves an accuracy of 67.9 %, a recall of 74.3 %, a [email protected] of 75.8 %, and a [email protected]:0.95 of 56.7 %, with a real-time detection speed of 244.2 frames per second. Compared to YOLOv8, YOLOv8-SBI demonstrates a significant improvement with 15.4 % increase in accuracy, 28.5 % increase in recall, and increases of 28.1 % and 20.9 % in [email protected] and [email protected]:0.95, respectively. Furthermore, relative to other models, such as YOLOv3, YOLOv5, YOLOv6, YOLOv8, YOLOv9, and YOLOv10, YOLOv8-SBI has a smaller parameter size of only 3.01 × 10⁶. This highlights the optimal balance between detection accuracy and speed, thereby offering robust technical support for intelligent mineral classification.</div></div>","PeriodicalId":37116,"journal":{"name":"Natural Gas Industry B","volume":"12 2","pages":"Pages 135-146"},"PeriodicalIF":4.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stratified allocation method for water injection based on machine learning: A case study of the Bohai A oil and gas field","authors":"Changlong Liu ,&nbsp;Pingli Liu ,&nbsp;Qiang Wang ,&nbsp;Lu Zhang ,&nbsp;Zechao Huang ,&nbsp;Yuande Xu ,&nbsp;Shaojiu Jiang ,&nbsp;Le Zhang ,&nbsp;Changxiao Cao","doi":"10.1016/j.ngib.2025.03.005","DOIUrl":"10.1016/j.ngib.2025.03.005","url":null,"abstract":"<div><div>The Bohai A oil and gas field is a natural gas and oil coproduction reservoir in the southern Bohai Sea, with an average gas–oil ratio of approximately 65 m³/m³. The oil and gas field has now entered the high water-cut stage, and in it, ineffective water circulation has intensified. Meanwhile, the process of adjusting the injection volume of water injection wells is overly complicated and relies on the experience of reservoir engineers. This paper established an automatic allocation method aimed at optimizing injection strategies based on the reservoir injection allocation scheme and utilizing real-time online data from intelligent layered injection wells by combining numerical simulation with artificial intelligence and machine learning algorithms. First, according to the basic parameters of block B in the Bohai A oil and gas field, a reservoir numerical simulation model was established, and historical fitting was carried out. The calculation found that the natural gas production of the A oil field would increase over time, although its oil production showed a decreasing trend. Using this model, finite group calculations were performed to establish an effective dataset. Second, the training and prediction effects of three machine learning prediction models—support vector machine, BP neural network, and random forest—were compared, and the BP neural network was selected as the machine learning mathematical model for injection allocation optimization. Third, 300 neurons and three hidden layers were used in the optimized neural network. The number of training set samples used was 185, and the number of test set samples was 19. Fourth, the optimized BP neural network model exhibits enhanced prediction accuracy, improved generalization capabilities, and superior dynamic relationship–capturing abilities. It effectively establishes a relatively accurate complex nonlinear relationship between the injected water volume and the production of natural gas and oil, providing valuable guidance for layered allocation in injection wells. The relative error of the calculation results of the optimized neural network prediction model is approximately ±2.3 %. This model can be utilized to simulate the injection allocation of injection wells, potentially increasing natural gas and oil production by over 4 %.</div></div>","PeriodicalId":37116,"journal":{"name":"Natural Gas Industry B","volume":"12 2","pages":"Pages 207-218"},"PeriodicalIF":4.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel surrogate model with deep learning for predicting spacial-temporal pressure in coalbed methane reservoirs","authors":"Yukun Dong ,&nbsp;Xiaodong Zhang ,&nbsp;Jiyuan Zhang ,&nbsp;Kuankuan Wu ,&nbsp;Shuaiwei Liu","doi":"10.1016/j.ngib.2025.03.008","DOIUrl":"10.1016/j.ngib.2025.03.008","url":null,"abstract":"<div><div>Coalbed methane (CBM) is a vital unconventional energy resource, and predicting its spatiotemporal pressure dynamics is crucial for efficient development strategies. This paper proposes a novel deep learning–based data-driven surrogate model, AxialViT-ConvLSTM, which integrates AxialAttention Vision Transformer, ConvLSTM, and an enhanced loss function to predict pressure dynamics in CBM reservoirs. The results showed that the model achieves a mean square error of 0.003, a learned perceptual image patch similarity of 0.037, a structural similarity of 0.979, and an R² of 0.982 between predictions and actual pressures, indicating excellent performance. The model also demonstrates strong robustness and accuracy in capturing spatial–temporal pressure features.</div></div>","PeriodicalId":37116,"journal":{"name":"Natural Gas Industry B","volume":"12 2","pages":"Pages 219-233"},"PeriodicalIF":4.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From data to decisions: AI-Augmented geoscience and engineering in natural gas industry","authors":"Huiwen Pang,&nbsp;Shaoqun Dong,&nbsp;Peng Tan,&nbsp;Hanqing Wang,&nbsp;Jiabao Li","doi":"10.1016/j.ngib.2025.04.001","DOIUrl":"10.1016/j.ngib.2025.04.001","url":null,"abstract":"","PeriodicalId":37116,"journal":{"name":"Natural Gas Industry B","volume":"12 2","pages":"Pages 101-109"},"PeriodicalIF":4.2,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}