Advances in Geo-Energy Research最新文献

Characterization and capillary pressure curve estimation of clayey-silt sediment in gas hydrate reservoirs of the South China Sea 南海天然气水合物储层中粘土质淤泥沉积物的特征和毛细管压力曲线估算

IF 8.2 1区地球科学

Advances in Geo-Energy Research Pub Date : 2023-12-20 DOI: 10.46690/ager.2023.12.06

Yuxuan Xia, Sai Xu, Cheng Lu, Pål Østebø Andersen, Jianchao Cai

引用次数: 0

Enhanced oil recovery in complex reservoirs: Challenges and methods 复杂储层中的强化采油：挑战与方法

IF 8.2 1区地球科学

Advances in Geo-Energy Research Pub Date : 2023-12-16 DOI: 10.46690/ager.2023.12.07

Runnan Wu, Bing Wei, Songyan Li, Yan Zhang, Qiang Luo

引用次数: 0

Feasibility analysis of storing solar energy in heterogeneous deep aquifer by hot water circulation: Insights from coupled hydro-thermo modeling 热水循环在非均质深层蓄水层储存太阳能的可行性分析:来自耦合水热模拟的见解

1区地球科学

Advances in Geo-Energy Research Pub Date : 2023-11-11 DOI: 10.46690/ager.2023.12.03

Yanyong Wang, Kunpeng Zhong, Yihua Gao, Zhenjie Sun, Rencheng Dong, Xiaoguang Wang

{"title":"Feasibility analysis of storing solar energy in heterogeneous deep aquifer by hot water circulation: Insights from coupled hydro-thermo modeling","authors":"Yanyong Wang, Kunpeng Zhong, Yihua Gao, Zhenjie Sun, Rencheng Dong, Xiaoguang Wang","doi":"10.46690/ager.2023.12.03","DOIUrl":"https://doi.org/10.46690/ager.2023.12.03","url":null,"abstract":"Storing solar energy in the subsurface as heat is a promising way for energy storage and conversion, which has a great potential to address the temporal and spatial mismatch between energy demand and supply. Thermal energy storage in deep aquifers can convert intermittent solar energy into stable high temperature geothermal energy. In this study, a new solar energy storage and conversion system is proposed where solar energy is firstly converted into heat using parabolic troughs and then stored in deep aquifers by high temperature hot water circulation. The geostatistical modelling and hydro-thermo coupling simulations are adopted to investigate the feasibility and efficiency of solar energy storage in deep aquifers. Specifically, how rock permeability heterogeneity (in terms of autocorrelation length and global permeability heterogeneity) impacts the temporal and spatial evolution of temperature distribution and storage efficiency is examined. The simulation results indicate that increased horizontal autocorrelation length and global heterogeneity may accelerate thermal breakthrough, deteriorating storage efficiency. High permeability heterogeneity may also lead to high injection pressure. Deep aquifers with small horizontal autocorrelation lengths and low global heterogeneity tend to have higher storage efficiency. These findings may improve our understanding of solar energy storage mechanism in deep aquifers and guide field applications. Document Type: Original article Cited as: Wang, Y., Zhong, K., Gao, Y., Sun, Z., Dong, R., Wang, X. Feasibility analysis of storing solar energy in heterogeneous deep aquifer by hot water circulation: Insights from coupled hydro-thermo modeling. Advances in Geo-Energy Research, 2023, 10(3): 159-173. https://doi.org/10.46690/ager.2023.12.03","PeriodicalId":36335,"journal":{"name":"Advances in Geo-Energy Research","volume":"21 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135086388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Study on the mechanism of surfactant flooding: Effect of betaine structure 表面活性剂驱油机理研究:甜菜碱结构的影响

1区地球科学

Advances in Geo-Energy Research Pub Date : 2023-11-09 DOI: 10.46690/ager.2023.12.02

Weifeng Lv, Zhaohui Zhou, Qun Zhang, Xiaojie Zhang, Lu Zhang

引用次数: 1

Numerical modeling of micro-particle migration in channels 通道中微粒迁移的数值模拟

1区地球科学

Advances in Geo-Energy Research Pub Date : 2023-10-30 DOI: 10.46690/ager.2023.11.06

Dongying Wang, Qin Qian, Anhai Zhong, Mingjing Lu, Zilin Zhang

{"title":"Numerical modeling of micro-particle migration in channels","authors":"Dongying Wang, Qin Qian, Anhai Zhong, Mingjing Lu, Zilin Zhang","doi":"10.46690/ager.2023.11.06","DOIUrl":"https://doi.org/10.46690/ager.2023.11.06","url":null,"abstract":": Physicochemical forces exert non-neligible effects on the migration of micro-particles in channels. Experiments, analytical and non-resolved computational fluid dynamics models have failed to decipher the dynamic behaviors of these particles when carried by fluid flow. In this paper, particle-scale numerical simulation is conducted to study the adhesive micro-particle migration process during duct flow in channels with a large characteristic dimension ratio and those with relatively small such ratio based on the coupled lattice Boltzmann method-discrete element method. The interaction between particle and fluid flow is dealt with by the immersed moving boundary condition. For micro-particle migration in duct flow, the effects of hydrodynamic force, adhesive force and particle concentration on the aggregation of particles are investigated. Based on the concept of hydrodynamic and adhesive force ratio, a stable aggregation distribution map is proposed to help analyze the distribution and size of the formed agglomerates. For micro-particle migration in channels with small characteristic dimension ratio, the general particle migration process is analyzed, which includes single particle retention, followed by particle capture, and the migration of large agglomerates. It is concluded that two factors accelerate single particle retention in a curved channel. Moreover, it is established that higher fluid flow rate facilitates the formation of large and compact agglomerate, and blockage by this can cause severe damage to the conductivity of the channel.","PeriodicalId":36335,"journal":{"name":"Advances in Geo-Energy Research","volume":"92 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136102715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Combination of sonic wave velocity, density and electrical resistivity for joint estimation of gas-hydrate reservoir parameters and their uncertainties 结合声速、密度和电阻率联合估计天然气水合物储层参数及其不确定度

1区地球科学

Advances in Geo-Energy Research Pub Date : 2023-10-28 DOI: 10.46690/ager.2023.11.07

Xin Zhang, Qingping Li, Lixia Li, Qi Fan, Jianhua Geng

{"title":"Combination of sonic wave velocity, density and electrical resistivity for joint estimation of gas-hydrate reservoir parameters and their uncertainties","authors":"Xin Zhang, Qingping Li, Lixia Li, Qi Fan, Jianhua Geng","doi":"10.46690/ager.2023.11.07","DOIUrl":"https://doi.org/10.46690/ager.2023.11.07","url":null,"abstract":"Gas-hydrate saturation and porosity are the most crucial reservoir parameters for gas-hydrate resource assessment. Numerous academics have put forward elastic and electrical petrophysical models for calculating the saturation and porosity of gas-hydrate. However, owing to the limitations of a single petrophysical model, the estimation of gas-hydrate saturation and porosity using single elastic or electrical measurement data appears to be inconsistent and uncertain. In this study, the sonic wave velocity, density and resistivity well log data are combined with a Bayesian linear inversion method for the simultaneous estimation of gas-hydrate saturation and porosity. The sonic wave velocity, density and resistivity data of the Shenhu area in the South China Sea are used to estimate the gas-hydrate saturation and porosity. To validate the accuracy of this method, the estimation results are compared with the saturation obtained from pore water chemistry and porosity obtained from density logs. The well log data examples show that the joint estimation method not only provides a rapid estimation of the gas-hydrate reservoir parameters but also improves the accuracy of results and determines their uncertainty. Document Type: Original article Cited as: Zhang, X., Li, Q., Li, L., Fan, Q., Geng, J. Combination of sonic wave velocity, density and electrical resistivity for joint estimation of gas-hydrate reservoir parameters and their uncertainties. Advances in Geo-Energy Research, 2023, 10(2): 133-140. https://doi.org/10.46690/ager.2023.11.07","PeriodicalId":36335,"journal":{"name":"Advances in Geo-Energy Research","volume":"28 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136233662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Impact of key parameters on far-field temporary plugging and diverting fracturing in fractured reservoirs: A 2D finite element study 裂缝性储层远场临时堵转压裂关键参数影响的二维有限元研究

1区地球科学

Advances in Geo-Energy Research Pub Date : 2023-10-25 DOI: 10.46690/ager.2023.11.05

Pingli Liu, Fengcheng Lou, Juan Du, Xiang Chen, Jinming Liu, Muming Wang

引用次数: 0

Numerical well test model of oil-water two-phase flow in fractured and vuggy carbonate reservoir 缝洞型碳酸盐岩油藏油水两相流数值试井模型

1区地球科学

Advances in Geo-Energy Research Pub Date : 2023-10-24 DOI: 10.46690/ager.2023.11.04

Guohan Xu, Hongjun Yin, Daiyan Zhang, Jing Fu, Cuiqiao Xing

{"title":"Numerical well test model of oil-water two-phase flow in fractured and vuggy carbonate reservoir","authors":"Guohan Xu, Hongjun Yin, Daiyan Zhang, Jing Fu, Cuiqiao Xing","doi":"10.46690/ager.2023.11.04","DOIUrl":"https://doi.org/10.46690/ager.2023.11.04","url":null,"abstract":"Fractured and vuggy carbonate reservoirs present a complex storage space with irregularly distributed fractures and caves. Furthermore, these reservoirs typically feature the presence of a substantial bottom aquifer, further complicating the fluid flow dynamics. At present, most well test models for this reservoir are based on discrete media primarily address single-phase flow scenarios, typically considering caves as equipotential bodies. This approach cannot accurately represent the complexities of such reservoirs. In this paper, a three-dimensional numerical well test model for two-phase oil-water flow within fractured and vuggy carbonate reservoirs is introduced. Randomly generated natural fractures are embedded within the reservoir, and the Hagen-Poiseuille law is utilized to describe fluid flow within cave spaces, effectively coupling flow interactions across fractures, caves and the porous rock matrix. The computational domain is discretized by a perpendicular bisection grid, and the finite volume method is used to solve the model, allowing for the calculation of the pressure and saturation fields at each time step. Subsequently, well test type curves are constructed and analyzed, flow regimes are segmented, and sensitivity analysis of model parameters is conducted. The pressure buildup data from well A are interpreted, and the results demonstrate a remarkable agreement between the well test curve and actual data, confirming the capability of the model to capture reservoir characteristics and complex fluid flow phenomena. The findings lay the foundation for the development of numerical well test models tailored to fractured and vuggy carbonate reservoirs. Document Type: Original article Cited as: Xu, G., Yin, H., Zhang, D., Fu, J., Xing, C. Numerical well test model of oil-water two-phase flow in fractured and vuggy carbonate reservoir. Advances in Geo-Energy Research, 2023, 10(2): 91-103. https://doi.org/10.46690/ager.2023.11.04","PeriodicalId":36335,"journal":{"name":"Advances in Geo-Energy Research","volume":"EM-13 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135321070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Artificial intelligence methods for oil and gas reservoir development: Current progresses and perspectives 油气田开发中的人工智能方法:进展与展望

1区地球科学

Advances in Geo-Energy Research Pub Date : 2023-10-23 DOI: 10.46690/ager.2023.10.07

Liang Xue, Daolun Li, Hongen Dou

{"title":"Artificial intelligence methods for oil and gas reservoir development: Current progresses and perspectives","authors":"Liang Xue, Daolun Li, Hongen Dou","doi":"10.46690/ager.2023.10.07","DOIUrl":"https://doi.org/10.46690/ager.2023.10.07","url":null,"abstract":"Artificial neural networks have been widely applied in reservoir engineering. As a powerful tool, it changes the way to find solutions in reservoir simulation profoundly. Deep learning networks exhibit robust learning capabilities, enabling them not only to detect patterns in data, but also uncover underlying physical principles, incorporate prior knowledge of physics, and solve complex partial differential equations. This work presents the latest research advancements in the field of petroleum reservoir engineering, covering three key research directions based on artificial neural networks: data-driven methods, physics driven artificial neural network partial differential equation solver, and data and physics jointly driven methods. In addition, a wide range of neural network architectures are reviewed, including fully connected neural networks, convolutional neural networks, recurrent neural networks, and so on. The basic principles of these methods and their limitations in practical applications are also outlined. The future trends of artificial intelligence methods for oil and gas reservoir development are further discussed. The large language models are the most advanced neural networks so far, it is expected to be applied in reservoir simulation to predict the development performance. Document Type: Perspective Cited as: Xue, L., Li, D., Dou, H. Artificial intelligence methods for oil and gas reservoir development: Current progresses and perspectives. Advances in Geo-Energy Research, 2023, 10(1): 65-70. https://doi.org/10.46690/ager.2023.10.07","PeriodicalId":36335,"journal":{"name":"Advances in Geo-Energy Research","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135459842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recent research advances in enhanced CO2 mineralization and geologic CO2 storage 强化CO2矿化与地质CO2封存研究进展

1区地球科学

Advances in Geo-Energy Research Pub Date : 2023-10-20 DOI: 10.46690/ager.2023.12.01

Chi Zhang, Yuhang Wang, Zuhao Kou, Liwei Zhang

{"title":"Recent research advances in enhanced CO2 mineralization and geologic CO2 storage","authors":"Chi Zhang, Yuhang Wang, Zuhao Kou, Liwei Zhang","doi":"10.46690/ager.2023.12.01","DOIUrl":"https://doi.org/10.46690/ager.2023.12.01","url":null,"abstract":"Enhanced CO2 mineralization and geologic CO2 storage have received increasing attention as two prominent approaches in combating climate change and fostering sustainable development of human society. This paper aims to explore three emerging areas of research within the realm of enhanced CO2 mineralization and geologic CO2 storage, including enhanced rock weathering, numerical modeling and validation of CO2 storage accounting for the interplay of various trapping mechanisms, and the examination of how reservoir heterogeneity influences the migration of CO2-brine multiphase flow. Discussions highlight the effectiveness of the spectrum induced polarization for monitoring changes in petrophysical and geochemical properties of rocks during enhanced rock weathering. Additionally, the multi-scale heterogeneity of geological formations needs to be carefully characterized, due to the fact that it plays a vital role in CO2 migration. Further research is required to achieve accurate and reliable simulations of convective mixing for field-scale applications. Document Type: Perspective Cited as: Zhang, C., Wang, Y., Kou, Z., Zhang, L. Recent research advances in enhanced CO2 mineralization and geologic CO2 storage. Advances in Geo-Energy Research, 2023, 10(3): 141-145. https://doi.org/10.46690/ager.2023.12.01","PeriodicalId":36335,"journal":{"name":"Advances in Geo-Energy Research","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135619897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0