检索结果-南通市图书馆

Pore-scale study of the effects of DTPA chelating agent flooding on oil recovery utilizing a clay-coated micromodel

petroleum Research 2024年第2期9卷 228-237页

作者： Hojjat Mohammadzadeh Jamshid Moghadasi Khalil Shahbazi Shahin Kord department of petroleum Engineering Ahwaz Faculty of Petroleum EngineeringPetroleum University of TechnologyAhwazIran

The use of diethylenetriaminepentaacetic acid(DTPA)chelating agent has shown promising results for enhanced oil recovery(EOR)in prior *** mechanisms,mainly resulting from rock-fluid interaction,have been proposed for chelating agent flooding;however,little attention has been paid to fluid-fluid interaction thus *** assessment of these mechanisms has primarily relied on macroscopic techniques such as core *** paper aims to investigate the injection of DTPA brine and its dominant mechanisms at the pore scale using a clay-coated *** micromodel tests were performed under oil-wet and water-wet *** a more precise examination of fluid/fluid interactions,the dynamic interfacial tension(IFT)and Zeta potential were *** was observed that the injection of DTPA brine in water-wet state changed the saturation distribution and increased oil *** on visual inspections,this change in saturation distribution could potentially be linked to the formation of micro-dispersions and viscoelastic interfacial ***-dispersions facilitate flow to unswept areas,and viscoelastic interface formation reshapes the interface between oil and brine,causing disconnected oil droplets to coalesce and thus increase *** the oil-wet state,the micro-dispersion formation and wettability alteration can be the dominant mechanisms,and the amount of recovered oil was higher than that observed in the water-wet ***,Zeta potential measurements at the interface between brine and oil showed a more negative value for DTPA brine,which is effective in wettability alteration and micro-dispersions *** results indicate that IFT reduction was not significant enough to be considered the dominant mechanism,although it assists in DTPA brine penetration into the crude oil and subsequent micro-dispersion formation.

关键词： Enhanced oil recovery technique Chelating agent Micromodel Fluid/fluid interaction Micro-dispersions Viscoelastic interface

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Multi-Dimensional QoS Evaluation and Optimization of Mobile Edge Computing for IoT:A Survey

引用

Chinese Journal of Electronics 2024年第4期33卷 859-874页

作者： Jiwei HUANG Fangzheng LIU Jianbing ZHANG Beijing Key Laboratory of petroleum Data Mining China University of Petroleum department of Computer Science and technology China University of Petroleum

With the evolvement of the Internet of things(IoT), mobile edge computing(MEC) has emerged as a promising computing paradigm to support IoT data analysis and processing. In MEC for IoT, the differentiated requirements on quality of service(QoS) have been growing rapidly, making QoS a multi-dimensional concept including several attributes, such as performance, dependability, energy efficiency, and economic factors. To guarantee the QoS of IoT applications, theories and techniques of multi-dimensional QoS evaluation and optimization have become important theoretical foundations and supporting technologies for the research and application of MEC for IoT,which have attracted significant attention from both academia and industry. This paper aims to survey the existing studies on multi-dimensional QoS evaluation and optimization of MEC for IoT, and provide insights and guidance for future research in this field. This paper summarizes the multi-dimensional and multi-attribute QoS metrics in Io T scenarios, and then several QoS evaluation methods are presented. For QoS optimization, the main research problems in this field are summarized, and optimization models as well as their corresponding solutions are elaborated. We take notice of the booming of edge intelligence in artificial intelligence-empowered Io T scenarios, and illustrate the new research topics and the state-of-the-art approaches related to QoS evaluation and optimization. We discuss the challenges and future research directions.

关键词： Internet of things Mobile edge computing Quality of service Quality of service evaluation Quality of service optimization PERFORMANCE EVALUATION RESOURCE-ALLOCATION SERVICE MIGRATION DELAY CLOUD DEPENDABILITY MECHANISM INTERNET SYSTEM THINGS

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Studying the effect of surfactant assisted low-salinity water flooding on clay-rich sandstones

引用

petroleum 2024年第2期10卷 306-318页

作者： Saeed Khezerloo-ye Aghdam Alireza Kazemi Mohammad Ahmadi department of petroleum Engineering Amirkabir University of Technology (AUT) department of petroleum and Chemical Engineering College of Engineering Sultan Qaboos University

Sandstone reservoirs often contain clay particles that can cause damage and reduce permeability during low-salinity water flooding. In this study, the effect of surfactants on fine migration in clay-rich sandstones and its impact on oil recovery was ***, the impact of surfactants on interparticle forces in fine-matrix, fine-fine, and oil-matrix systems was modeled. The results showed that both CTAB(cetyltrimethyl ammonium bromide) and QS(quillaja saponin) cause EDL compaction, weakening the repulsive forces. However, SDS(sodium dodecyl sulfate)and TX(triton X-100) do not affect the EDL. Next, the effect of surfactants on IFT reduction and wettability alteration was experimentally investigated. All surfactants reduced IFT due to the surface excessive concentration mechanism. The wettability alteration experiment illustrated that although QS and CTAB compact EDL around oil and matrix particles leading to attraction force augmentation, they both alter wettability through adsorption on matrix and carboxylic groups present in crude oil, *** aqueous solutions were then injected into various clay-rich sandstone sanpacks, which resulted in increased oil recovery. However, the mechanisms leading to enhanced oil recovery variedby surfactant type. CTAB increased recovery by 10% through IFT reduction and wettability alteration, while SDS and TX increased recovery by 12% and 9%, respectively, through wettability alteration and extreme fine migration. In contrast, partial fine migration in the QS flooding experiment reached a recovery increase of 18%. Permeability trends through experiments were also recorded. During CTAB injection,permeability did not reduce, while QS aqueous solution reduced rock permeability to 5 m D. SDS and TX reduced the magnitude of permeability to 2 m *** conclusion, this study demonstrates that surfactants can effectively improve oil recovery in clay-rich sandstones by altering the interparticle forces, reducing IFT, a

关键词： Surfactant flooding Smart water Fine migration Recovery factor

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Predicting density log from well log using machine learning techniques and heuristic optimization algorithm:A comparative study

引用

petroleum Research 2024年第2期9卷 176-192页

作者： Mehdi Rahmati Ghasem Zargar Abbas Ayatizadeh Tanha National Iranian Drilling Company Well Logging DepartmentAhwazIran Faculty Member of petroleum University of technology Iran department of petroleum Engineering Tarbiat Modares UniversityTehranIran

In the petroleum industry,the analysis of petrophysical parameters is critical for efficient reservoir management,production optimization,development strategies,and accurate hydrocarbon reserve *** recent years,the integration of machine learning methodologies has revolutionized the field,addressing challenges in geology,geophysics,and petroleum engineering,even when confronted with limited or imperfect *** study focuses on the prediction of density logs,a pivotal factor in evaluating reservoir hydrocarbon *** is important to note that during well logging operations,log data for specific depths of interest may be missing or incorrect,presenting a significant *** tackle this issue,we employed the Adaptive Neuro-Fuzzy Inference System(ANFIS)and Artificial Neural Networks(ANN)in combination with advanced optimization algorithms,including Particle Swarm Optimization(PSO),Imperialist Competitive Algorithms(ICA),and Genetic Algorithms(GA).These methods exhibit promising performance in predicting density logs from gamma-ray,neutron,sonic,and photoelectric log ***,our results highlight that the Genetic Algorithms-based Artificial Neural Network(GA-ANN)approach outperforms all other methods,achieving an impressive Mean Squared Error(MSE)of *** comparison,ANFIS records an MSE of 0.0015,ICA-ANN 0.0090,PSO-ANN 0.0093,and ANN 0.0183.

关键词： Density log Machine learning approaches Artificial neural networks(ANN) Adaptive neuro-fuzzy inference system(ANFIS) Optimization algorithm

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Online Pareto optimal control of mean-field stochastic multi-player systems using policy iteration

引用

Science China(Information Sciences) 2024年第4期67卷 21-37页

作者： Xiushan JIANG Yanshuang WANG Dongya ZHAO Ling SHI College of New Energy China University of Petroleum(East China) department of Electronic and Computer Engineering Hong Kong University of Science and Technology

In this study, the Pareto optimal strategy problem was investigated for multi-player mean-field stochastic systems governed by It? differential equations using the reinforcement learning(RL) method.A partially model-free solution for Pareto-optimal control was derived. First, by applying the convexity of cost functions, the Pareto optimal control problem was solved using a weighted-sum optimal control problem. Subsequently, using on-policy RL, we present a novel policy iteration(PI) algorithm based on the Hrepresentation technique. In particular, by alternating between the policy evaluation and policy update steps,the Pareto optimal control policy is obtained when no further improvement occurs in system performance,which eliminates directly solving complicated cross-coupled generalized algebraic Riccati equations(GAREs).Practical numerical examples are presented to demonstrate the effectiveness of the proposed algorithm.

关键词： mean-field stochastic systems Pareto optimal control policy iteration scheme $\mathcal{H}$-representation

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Intelligent solubility estimation of gaseous hydrocarbons in ionic liquids

引用

petroleum 2024年第1期10卷 109-123页

作者： Behnaz Basirat Fariborz Shaahmadi Seyed Sorosh Mirfasihi Abolfazl Jomekian Bahamin Bazooyar Ahvaz Faculty of petroleum Engineering Petroleum University of Technology (PUT) School of Engineering & Physical Sciences Heriot Watt University department of Fluids & Environment The University of Manchester department of Engineering Chemical Engineering Group Esfarayen University of Technology Mechanical and Aerospace Engineering Brunel University London

The research focuses on evaluating how well new solvents attract light hydrocarbons, such as propane,methane, and ethane, in natural gas sweetening units. It is important to accurately determine the solubility of hydrocarbons in these solvents to effectively manage the sweetening process. To address this challenge, the study proposes using advanced empirical models based on artificial intelligence techniques like Multi-Layer Artificial Neural Network(ML-ANN), Support Vector Machines(SVM), and Least Square Support Vector Machine(LSSVM). The parameters for the SVM and LSSVM models are estimated using optimization methods like Genetic Algorithm(GA), Particle Swarm Optimization(PSO), and Shuffled Complex Evolution(SCE). Data on the solubility of propane, methane, and ethane in various ionic liquids are collected from reliable literature sources to create a comprehensive database. The proposed artificial intelligence models show great accuracy in predicting hydrocarbon solubility in ionic liquids. Among these, the hybrid SVM models perform exceptionally well, with the PSO-SVM hybrid model being particularly efficient computationally. To ensure a comprehensive analysis, different examples of hydrocarbons and their order are included. Additionally, a comparative analysis is conducted to compare the AI models with the thermodynamic COSMO-RS model for solubility analysis. The results demonstrate the superiority of the AI models, as they outperform traditional thermodynamic models across a wide range of data. In conclusion, this study introduces advanced artificial intelligence algorithms such as ML-ANN, SVM, and LSSVM in accurately estimating the solubility of hydrocarbons in ionic liquids. The incorporation of optimization techniques and variations in hydrocarbon examples improves the accuracy, precision, and reliability of these intelligent models. These findings highlight the significant potential of AI-based approaches in solubility analysis and emphasize their superiori

关键词： Solubility Gaseous hydrocarbon Intelligent models Ionic liquids

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

S^(2)ANet:Combining local spectral and spatial point grouping for point cloud processing

引用

虚拟现实与智能硬件（中英文） 2024年第4期6卷 267-279页

作者： Yujie LIU Xiaorui SUN Wenbin SHAO Yafu YUAN College department of Computer Science and technology China University of Petroleum(East China)Qingdao 266580China

Background Despite the recent progress in 3D point cloud processing using deep convolutional neural networks,the inability to extract local features remains a challenging *** addition,existing methods consider only the spatial domain in the feature extraction *** In this paper,we propose a spectral and spatial aggregation convolutional network(S^(2)ANet),which combines spectral and spatial features for point cloud ***,we calculate the local frequency of the point cloud in the spectral ***,we use the local frequency to group points and provide a spectral aggregation convolution module to extract the features of the points grouped by the local *** simultaneously extract the local features in the spatial domain to supplement the final *** S^(2)ANet was applied in several point cloud analysis tasks;it achieved stateof-the-art classification accuracies of 93.8%,88.0%,and 83.1%on the ModelNet40,ShapeNetCore,and ScanObjectNN datasets,*** indoor scene segmentation,training and testing were performed on the S3DIS dataset,and the mean intersection over union was 62.4%.Conclusions The proposed S^(2)ANet can effectively capture the local geometric information of point clouds,thereby improving accuracy on various tasks.

关键词： Local frequency Spectral and spatial aggregation convolution Spectral group convolution Point cloud representation learning Graph convolutional network

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Interpretation and characterization of rate of penetration intelligent prediction model

引用

petroleum Science 2024年第1期21卷 582-596页

作者： Zhi-Jun Pei Xian-Zhi Song Hai-Tao Wang Yi-Qi Shi Shou-Ceng Tian Gen-Sheng Li College of petroleum Engineering China University of Petroleum(Beijing)Beijing102249China State Key Laboratory of petroleum Resources and Prospecting Beijing102249China Kunlun Digital technology Co. Ltd.Beijing102206China

Accurate prediction of the rate of penetration(ROP)is significant for drilling *** the intelligent ROP prediction model based on fully connected neural networks(FNN)outperforms traditional ROP equations and machine learning algorithms,its lack of interpretability undermines its *** study proposes a novel interpretation and characterization method for the FNN ROP prediction model using the Rectified Linear Unit(ReLU)activation *** leveraging the derivative of the ReLU function,the FNN function calculation process is transformed into vector *** FNN model is linearly characterized through further simplification,enabling its interpretation and *** proposed method is applied in ROP prediction scenarios using drilling data from three vertical wells in the Tarim *** results demonstrate that the FNN ROP prediction model with ReLU as the activation function performs exceptionally *** relative activation frequency curve of hidden layer neurons aids in analyzing the overfitting of the FNN ROP model and determining drilling data *** the well sections with similar drilling data,averaging the weight parameters enables linear characterization of the FNN ROP prediction model,leading to the establishment of a corresponding linear representation ***,the quantitative analysis of each feature's influence on ROP facilitates the proposal of drilling parameter optimization schemes for the current well *** established linear characterization equation exhibits high precision,strong stability,and adaptability through the application and validation across multiple well sections.

关键词： Fully connected neural network Explainable artificial intelligence Rate of penetration ReLU active function Deep learning Machine learning

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Application status and prospect of ionic liquids in oilfield chemistry

引用

petroleum 2024年第1期10卷 11-18页

作者： Jinsheng Sun Zhuoyang Xiu Li Li Kaihe Lv Xianfa Zhang Zonglun Wang Zhiwen Dai Zhe Xu Ning Huang Jingping Liu School of petroleum Engineering China University of Petroleum (East China) CNPC Engineering technology R&D Company Limited Oil & Gas technology Research Institute of Changqing Oilfield Company

The ionic liquid, as a new treatment agent, has been increasingly applied in oil fields due to its strong temperature resistance, good solubility and high surface activity. In this paper, we systematically discuss the action mechanism and application effect of ionic liquids in oilfield chemistry. Ionic liquids can inhibit shale hydration expansion and reduce fluid loss through adsorption and intercalation, inhibit the formation of natural gas hydrate through imidazole five-membered ring structure as a space barrier, reduce viscosity of heavy oil by breaking chemical bonds of heavy oil macromolecules and charge transfer,improve oil displacement efficiency by forming ions pairs with carboxyl groups in crude oil, demulsify by forming channels between dispersed water droplets, acidify the formation by reacting with water to produce acid, interacts with organic material through weak hydrogen bonds and extracts it from oilfield wastewater, desulphurize by inserting sulfide molecules into the “stack” structure and form liquid inclusion complex, inhibit corrosion by forming a protective film on the metal surface. Based on the above aspects, the development direction of ionic liquids is proposed. The application of ionic liquids in oilfield chemistry is still in its infancy. It is urgent to fully explore the application performance of ionic liquids in oilfield chemistry, which also provides theoretical and technical supports for efficient reservoir development.

关键词： Ionic liquids Oilfield chemistry Shale inhibitor Drilling fluid

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Collision-free parking recommendation based on multi-agent reinforcement learning in vehicular crowdsensing

引用

Digital Communications and Networks 2024年第3期10卷 609-619页

作者： Xin Li Xinghua Lei Xiuwen Liu Hang Xiao College of Computer Science and technology China University of Petroleum(East China)QingDao266580China

The recent proliferation of Fifth-Generation(5G)networks and Sixth-Generation(6G)networks has given rise to Vehicular Crowd Sensing(VCS)systems which solve parking collisions by effectively incentivizing vehicle ***,instead of being an isolated module,the incentive mechanism usually interacts with other *** on this,we capture this synergy and propose a Collision-free Parking Recommendation(CPR),a novel VCS system framework that integrates an incentive mechanism,a non-cooperative VCS game,and a multi-agent reinforcement learning algorithm,to derive an optimal parking strategy in real ***,we utilize an LSTM method to predict parking areas roughly for recommendations *** incentive mechanism is designed to motivate vehicle participation by considering dynamically priced parking tasks and social network *** order to cope with stochastic parking collisions,its non-cooperative VCS game further analyzes the uncertain interactions between vehicles in parking *** its multi-agent reinforcement learning algorithm models the VCS campaign as a multi-agent Markov decision process that not only derives the optimal collision-free parking strategy for each vehicle independently,but also proves that the optimal parking strategy for each vehicle is ***,numerical results demonstrate that CPR can accomplish parking tasks at a 99.7%accuracy compared with other baselines,efficiently recommending parking spaces.

关键词： Incentive mechanism Non-cooperative VCS game Multi-agent reinforcement learning Collision-free parking strategy Vehicular crowdsensing

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：