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Mechanism of proppant transport and deposition in rough intersecting fractures after offshore fracturing

Petroleum Science 2025年第3期22卷 1270-1288页

作者： Biao Yin Yi-Shan Lou Shan-Yong Liu Yan Zhang School of Petroleum Engineering Yangtze UniversityWuhan430113HubeiChina National Engineering Research Center for Oil&Gas Drilling and Completion Technology Yangtze UniversityWuhan430100HubeiChina Institute of Mud Logging Technology and Engineering Yangtze UniversityJingzhou434023HubeiChina

To accurately analyze proppant transport in rough intersecting fractures and elucidate the interaction mechanisms among liquid,particles,and rough walls,this study reconstructed a numerical model of fractures in inhomogeneous reservoirs with varying brittleness index(BI).Various auto-correlation Gaussian rough fracture models were created using Matlab to assess roughness through the fractal dimension *** research innovatively combined Boolean operations to establish three-dimensional rough fracture models,incorporating(Computational Fluid Dynamics)CFD-DEM(Discrete Element Method)with a bidirectional method for *** proppant transport in fractures was categorized into three zones based on the difference in the turbulent kinetic *** induced fracture roughness increases fluid retention and turbulence,causing plugging effects and limiting proppant flow into branch ***,compared with the superior deposition and significant support effects of the spherical proppant,the low-sphericity proppant traveled farther under fracturing fluid,inducing more pronounced plugging near curved fracture intersections;the variation in fracture intersection angles primarily impacted the wall shear stress within the flow field,indicating smaller angles led to higher shear energy at the *** with the intersection angle of 30°,the height and area deposited in the 90 branch fracture increased by 52.25%and 65.33%,respectively:notably,injecting proppant from smaller to larger particles(S:M:L)and a low velocity effectively ensured fracture conductivity near the wellbore at joint roughness coefficient(JRC)≥46 while achieving satis-factory placement in the branch fracture,making it a recommended approach.

关键词： Hydraulic fracturing Intersecting fracture Proppant Turbulent kinetic energy CFD-DEM Sphericity Joint roughness coefficient

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Architectural Model of a Dryland Gravel Braided River,based on 3D UAV Oblique Photogrammetric Data:A Case Study of West Dalongkou River in Eastern Xinjiang,China

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Acta Geologica Sinica(English Edition) 2023年第1期97卷 269-285页

作者： YIN Senlin ZHU Baiyu GUO Haiping XU Zhenhua LI Xiaoshan WU Xiaojun CHEN Yukun JIANG Zhibin Institute of Mud-Logging Technology and Engineering Yangtze UniversityJingzhouHubei 434023China Research Institute of Exploration and Development PetroChina Xinjiang Oilfield CompanyKaramayXinjiang 834000China School of GeoSciences Yangtze UniversityWuhan 430100China

Three-dimensional unmanned aerial vehicle(UAV)oblique photogrammetric data were used to infer mountainous gravel braided river lithofacies,lithofacies associations and architectural *** architecture and lithofacies associations with detailed lithofacies characterizations were comprehensively described to document the architectural model,architectural element scale and gravel particle scale.(1)Nine lithofacies(i.e.,Gmm,Gcm,Gcc,Gci,Gcl,Ss,Sm,Fsm and Fl)were identified and classified as gravel,sand and fine matrix *** are typical depositional features of a mountainous dryland gravel-braided river.(2)Three architectural elements were identified,including channel(CH),gravel bar(GB)and overbank(OB).CH can be further divided into flow channel and abandoned channel,while GB consists of Central Gravel bar(CGB)and Margin Gravel bar(MGB).(3)The gravel bar is the key architectural element of the gravel braided river,with its geological *** dimensions of GBs and their particles are various,but exhibit good relationships with each *** grain size of GB decreases downstream,but the dimensions of GB do *** bank erosion affects the GB dimensions,whereas channel incision and water flow velocity influence the grain size of *** conclusions can be applied to the dryland gravel braided river studies in tectonically active areas.

关键词： three-dimensional UAV oblique photogrammetry gravel braided river architecture modern deposits West Dalongkou River

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Reservoir Facies Modeling Based on Generative Adversarial Network

Reservoir Facies Modeling Based on Generative Adversarial Ne...

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2024 International Conference on New Trends in Computational Intelligence, NTCI 2024

作者： Lin, Shaolin Yin, Senlin Zhang, Yaowei Liu, Juanxia Tao, Chao Institute of Mud Logging Technology and Engineering Yangtze University Hubei China School of Computer Science Yangtze University Hubei China China-France Bohai Geoservices Co. Ltd. Tianjin China No.1 Mud logging Company Bohai Drilling Engineering Co. Ltd. Tianjin China

ISBN: (纸本)9798331517021

Three-dimensional geological modeling of reservoirs is of great significance for developing oil and gas resources, groundwater resources, and carbon dioxide geological storage. Geological facies models are the basis for accurately predicting underground oil reservoirs, geological carbon dioxide storage potential, and groundwater resources. Traditional geostatistical modeling methods can be consistent with geological models to some extent, but there are obvious shortcomings when the characteristics of geological models become complex. Therefore, this paper takes the braided river deltaic diversion channel and estuarine dam phase of the Hanjiang Formation in the Epping Depression of the Pearl River Estuary Basin as the research objective. Based on the geological background of the workings, 3D seismic data and seven logging wells, a conditionally bounded phase simulation based on an improved GAN model is proposed. The research results show that the phase model generated by modeling well facies data matches the input well facies data. The generated phase model has good diversity, and the trained generator can generate high-quality phase models with 100%. accuracy in reproducing well facies. © 2024 IEEE.

关键词： Underground reservoirs

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Artificial Intelligence Algorithm with Geological Constraints Establishes Element Porosity Relationship

Artificial Intelligence Algorithm with Geological Constraint...

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2024 International Conference on New Trends in Computational Intelligence, NTCI 2024

作者： Zhang, Wenxin Yin, Senlin Liu, Yonghua Zhang, Zhipeng Deng, Yuwei Liu, Juanxia Yangtze University Institute of Mud Logging Technology and Engineering Hubei China China France Bohai Geoservices Co. Ltd China Yangtze University College of geophysics and petroleum resources Hubei China

ISBN: (纸本)9798331517021

This article focuses on the application of artificial intelligence algorithms with geological constraints to establish a high-precision relationship model between geological elements and porosity. This algorithm integrates geological theory and artificial intelligence techniques, incorporating geological constraints into data analysis and model construction. The predicted porosity obtained through this multiple regression model fits well with the measured porosity, and the geological interpretation is reasonable and consistent with reservoir characteristics. Overall, it is believed that artificial intelligence algorithms with geological constraints can accurately predict the size of reservoir porosity, especially in the study of low resistance reservoir performance, which has certain advantages. This innovative method not only improves the efficiency of geological data analysis but also ensures the geological rationality and practical application value of research results, which has certain significance for promoting the intelligent development of oil and gas exploration and development. © 2024 IEEE.

关键词： Petroleum prospecting

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Lithology Identification of Improved Model based on DeepLabv3 + Deep Convolutional Neural Network

Lithology Identification of Improved Model based on DeepLabv...

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2024 International Conference on New Trends in Computational Intelligence, NTCI 2024

作者： Wang, Ju Yin, Senlin Hu, Zhangming Bai, Kai College of Computer Science and Technology Yangtze University Hubei China Research Institute of Mud Logging Technology and Engineering Yangtze University Hubei China Hubei Provincial Key Laboratory of Southern Complex Shale Oil and Gas Geology and Development Hubei Province Wuhan China Xibu Drilling Engineering Company Limited Engineering and Technology Division of CNPC China

ISBN: (纸本)9798331517021

Aiming at the complexity of outcrop lithology identification, an improved outcrop lithology identification algorithm based on DeepLabv3 + is proposed. We use the Xception network replaced by the MobileNetV2 module to enhance the ability to extract lithologic features and make the model more lightweight. In order to segment pixels more accurately, the CA (Coordinate attention) attention mechanism is introduced, so that the improved backbone network can extract lithologic features more accurately in complex environments. The experimental results show that compared with the traditional DeepLabv3 +, the accuracy of the improved algorithm is increased by 1.08 percentage points, the MP A is increased by 2.4 percentage points, and the average classification accuracy is 94.86 %. Compared with other mainstream semantic segmentation models, all aspects of performance are more prominent. © 2024 IEEE.

关键词： Semantic Segmentation

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Identification of Rock Cracks in Outcrop Areas Based on Improved DeepLab V3+

Identification of Rock Cracks in Outcrop Areas Based on Impr...

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2024 International Conference on New Trends in Computational Intelligence, NTCI 2024

作者： Zhang, Yaowei Yin, Senlin Hu, Zhangming Bai, Kai Xiong, Ting College of Computer Science and Technology Yangtze University Hubei Jingzhou China Hubei Provincial Key Laboratory of Southern Complex Shale Oil and Gas Geology and Development Hubei Province Wuhan China Research Institute of Mud Logging Technology and Engineering Yangtze University Hubei Jingzhou China CNPC Xibu Drilling Engineering Company Limited Engineering and Technology Division Xinjiang Urumqi China Co. Ltd. Shenzhen China

ISBN: (纸本)9798331517021

The study of reservoir fractures has always been a key focus in oil and gas exploration and development, and the most intuitive method is to observe rock fractures in outcrop areas. Manual surveying has low efficiency and strong subjectivity, so identifying rock fractures in outcrop areas has always been a difficult task. In response to this difficulty, this article utilizes drone oblique photography technology to significantly improve surveying efficiency, and proposes an improved DeepLabv3+ semantic segmentation model to achieve accurate segmentation of rock fractures. The experimental results showed that the MAP (Mean Average Precision) of the improved DeepLabv3+ model reached 83.77%, which was 12.44% higher than the original DeepLabv3+ model;MIoU (Mean Intersection over Union) has increased from 68.21 % to 78.84%;The accuracy has increased from 74.83% to 91.66%;The parameter count is only 15.14M. The experimental results show that the improved DeepLabv3+ model in this paper exhibits superior segmentation performance in rock fracture segmentation tasks in field outcrop areas, and has good mobile deployment performance. © 2024 IEEE.

关键词： Drones

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Digital Outcrop Visualization Characterization and Application System Based on WebGL:A Case Study of UAV-based Tilt Photography in Yiqikelike Section

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Science technology and engineering 2024年第11期24卷 4633-4642页

作者： Dong, Zhi-Cheng Chen, Gong-Yang Yin, Sen-Lin Zhu, Bai-Yu Institute of Mud Logging Technology and Engineering Yangtze University Jingzhou43400 China

In order to meet the requirements of geological prospectors for outcrop characterization data analysis, the existing software has shortcomings in 3D visualization, cross-device, cross-platform and easy operation. Based on WebGL, a 3D digital outcrop visualization platform was developed. Firstly, the development framework and implementation route of the platform were designed. Based on the visualization rendering of Cesium, data acquisition was carried out by tilt photography of UAV. Combined with the transformation of the world space coordinate system, a cross-platform and cross-device visualization data analysis platform was established. Secondly, through the function functions of front-end JS, the design and implementation of target measurement, marking, publishing and browsing functions. Finally, the effectiveness of developing a 3D digital outcrop visualization platform was verified by an example. The visualization platform will greatly improve the analysis efficiency and usability of outcrop characterization in the field, and has a high application value for accelerating the construction of digital China and intelligent geology. © 2024 Beijing Kexue Jishu yu Gongcheng Zazhishe. All rights reserved.

关键词： Volume rendering

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Petroleum geological features and hydrocarbon enrichment of Linhe Depression in Hetao Basin, NW China

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Petroleum Exploration and Development 2023年第4期50卷 798-811页

作者： ZHANG Ruifeng HE Haiqing ZHU Qingzhong CHEN Shuguang LIU Xiheng DAN Weining HU Yanxu SHI Yulei ZHANG Yufei YU Haijun ZHANG Ximeng PetroChina Huabei Oilfield Company Renqiu 062552China PetroChina Oil&Gas and New Energy Company Beijing 100007China Logging Technology Research Institute of CNPC Logging Company Beijing 100007China No.2 Mud Logging Company CNPC Bohai Drilling Engineering Company LimitedRenqiu 062552China

Based on paleogeomorphology, drilling and seismic data, this paper systematically studies the structural and sedimentary evolution, source rock characteristics, reservoir characteristics and formation mechanism, hydrocarbon accumulation model and enrichment law in the Linhe Depression of the Hetao Basin, NW China. The Hetao Basin mainly experienced three stages of evolution, namely, weak extensional fault depression, strong extensional fault depression and strike-slip transformation, giving rise to four positive structural belts(Jilantai, Shabu, Nalinhu and Xinglong), which are favorable areas for oil and gas accumulation. The two main saline lacustrine source rocks, Lower Cretaceous Guyang Formation and Oligocene Linhe Formation, are characterized by high sulfur content, rich algae, early maturity, early expulsion, and wide oil generation window. The large structural transition belt in the intermountain area around the Hetao Basin controls the formation of large-scale braided river delta deposits, which are characterized by high quartz content(50%-76%), long-term shallow burial and weak compaction, low cement content, and good reservoir properties in delta front sandbody. The burial depth of the effective Paleogene reservoirs is predicted to reach 8000 m. Three hydrocarbon accumulation models, nose-uplift near sag, buried hill surrounding sag, fault nose near source rock, are constructed. The law of hydrocarbon accumulation in the Linhe Depression is finally clarified as follows: near-source around the depression is the foundation, high-quality thick reservoir is the premise, good tectonic setting and trap conditions are the key.

关键词： Hetao Basin Linhe Depression Cretaceous Guyang Formation Paleogene Linhe Formation Jilantai Oilfield Bayan Oilfield hydrocarbon enrichment law

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Reservoir Facies Modeling Based on Generative Adversarial Network

Reservoir Facies Modeling Based on Generative Adversarial Ne...

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New Trends in Computational Intelligence (NTCI), International Conference on

作者： Shaolin Lin Senlin Yin Yaowei Zhang Juanxia Liu Chao Tao Institute of Mud Logging Technology and Engineering Yangtze University Hubei China School of Computer Science Yangtze University Hubei China China-France Bohai Geoservices Co. Ltd. Tianjin China No.1 Mud logging Company Bohai Drilling Engineering Co. Ltd. Tianjin China

ISBN: (数字)9798331517021

ISBN: (纸本)9798331517038

关键词： Geology Computational modeling Stochastic processes Predictive models Generative adversarial networks Reservoirs Data models Generators Vectors Synthetic data

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Artificial Intelligence Algorithm with Geological Constraints Establishes Element Porosity Relationship

Artificial Intelligence Algorithm with Geological Constraint...

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New Trends in Computational Intelligence (NTCI), International Conference on

作者： Wenxin Zhang Senlin Yin Yonghua Liu Zhipeng Zhang Yuwei Deng Juanxia Liu Institute of Mud Logging Technology and Engineering Yangtze University Hubei China France Bohai Geoservices Co. Ltd College of geophysics and petroleum resources Yangtze University Hubei China

ISBN: (数字)9798331517021

ISBN: (纸本)9798331517038

关键词： Resistance Data analysis Geology Computational modeling Reservoirs Prediction algorithms Mathematical models Data models Robustness Artificial intelligence

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