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Dynamic interwell connectivity analysis of multi-layer waterflooding reservoirs based on an improved graph neural network

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Petroleum Science 2024年第2期21卷 1062-1080页

作者： Zhao-Qin Huang Zhao-Xu Wang Hui-Fang Hu Shi-Ming Zhang Yong-Xing Liang Qi Guo Jun Yao School of Petroleum Engineering China University of Petroleum(East China)Qingdao266580ShandongChina exploration and development research institute Shengli OilfieldSINOPECDongying257015ShandongChina

The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in China's onshore oilfields generally have the characteristics of thin and many layers, so multi-layer joint production is usually adopted. It remains a challenge to ensure the accuracy of splitting and dynamic connectivity in each layer of the injection-production wells with limited field data. The three-dimensional well pattern of multi-layer reservoir and the relationship between injection-production wells can be equivalent to a directional heterogeneous graph. In this paper, an improved graph neural network is proposed to construct an interacting process mimics the real interwell flow regularity. In detail, this method is used to split injection and production rates by combining permeability, porosity and effective thickness, and to invert the dynamic connectivity in each layer of the injection-production wells by attention *** on the material balance and physical information, the overall connectivity from the injection wells,through the water injection layers to the production layers and the output of final production wells is established. Meanwhile, the change of well pattern caused by perforation, plugging and switching of wells at different times is achieved by updated graph structure in spatial and temporal ways. The effectiveness of the method is verified by a combination of reservoir numerical simulation examples and field example. The method corresponds to the actual situation of the reservoir, has wide adaptability and low cost, has good practical value, and provides a reference for adjusting the injection-production relationship of the reservoir and the development of the remaining oil.

关键词： Graph neural network Dynamic interwell connectivity Production-injection splitting Attention mechanism Multi-layer reservoir

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Production Capacity Prediction Method of Shale oil Based on Machine Learning Combination Model

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Energy Engineering 2024年第8期121卷 2167-2190页

作者： Qin Qian Mingjing Lu Anhai Zhong Feng Yang Wenjun He Min Li Petroleum Engineering Technology research institute of shengli oilfield SINOPECDongying257000China Postdoctoral scientific research Working Station of shengli oilfield SINOPECDongying257000China

The production capacity of shale oil reservoirs after hydraulic fracturing is influenced by a complex interplay involving geological characteristics,engineering quality,and well *** relationships,nonlinear in nature,pose challenges for accurate description through physical *** field data provides insights into real-world effects,its limited volume and quality restrict its *** this,numerical simulation models offer effective *** harness the strengths of both data-driven and model-driven approaches,this study established a shale oil production capacity prediction model based on a machine learning combination *** fracturing development data from 236 wells in the field,a data-driven method employing the random forest algorithm is implemented to identify the main controlling factors for different types of shale oil *** the combination model integrating support vector machine(SVM)algorithm and back propagation neural network(BPNN),a model-driven shale oil production capacity prediction model is developed,capable of swiftly responding to shale oil development performance under varying geological,fluid,and well *** results of numerical experiments show that the proposed method demonstrates a notable enhancement in R2 by 22.5%and 5.8%compared to singular machine learning models like SVM and BPNN,showcasing its superior precision in predicting shale oil production capacity across diverse datasets.

关键词： Shale oil production capacity data-driven model model-driven method machine learning

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Prediction of Porous Media Fluid Flow with Spatial Heterogeneity Using Criss-Cross Physics-Informed Convolutional Neural Networks

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1323-1340页

作者： Jiangxia Han Liang Xue Ying Jia Mpoki Sam Mwasamwasa Felix Nanguka Charles Sangweni Hailong Liu Qian Li State Key Laboratory of Petroleum Resources and Prospecting China University of PetroleumBeijing102249China Department of oil-Gas field development Engineering College of Petroleum EngineeringChina University of PetroleumBeijing102249China exploration Production research institute SinopecBeijing102249China Ministry of Energy Tanzania Petroleum Development CorporationTowerDar es Salaam2774Tanzania Ministry of Energy Building Petroleum Upstream Regulatory Authority in Tanzania(PURA)Dar es Salaam11439Tanzania

Recent advances in deep neural networks have shed new light on physics,engineering,and scientific *** the data-centered viewpoint with physical simulation is one of the research *** physicsinformedneural network(PINN)is currently the most general framework,which is more popular due to theconvenience of constructing NNs and excellent generalization *** automatic differentiation(AD)-basedPINN model is suitable for the homogeneous scientific problem;however,it is unclear how AD can enforce fluxcontinuity across boundaries between cells of different properties where spatial heterogeneity is represented bygrid cells with different physical *** this work,we propose a criss-cross physics-informed convolutionalneural network(CC-PINN)learning architecture,aiming to learn the solution of parametric PDEs with spatialheterogeneity of physical *** achieve the seamless enforcement of flux continuity and integration ofphysicalmeaning into CNN,a predefined 2D convolutional layer is proposed to accurately express transmissibilitybetween adjacent *** efficacy of the proposedmethodwas evaluated through predictions of several petroleumreservoir problems with spatial heterogeneity and compared against state-of-the-art(PINN)through numericalanalysis as a benchmark,which demonstrated the superiority of the proposed method over the PINN.

关键词： Physical-informed neural networks(PINN) flow in porous media convolutional neural networks spatial heterogeneity machine learning

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Better use of experience from other reservoirs for accurate production forecasting by learn-to-learn method

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Petroleum Science 2024年第1期21卷 716-728页

作者： Hao-Chen Wang Kai Zhang Nancy Chen Wen-Sheng Zhou Chen Liu Ji-Fu Wang Li-Ming Zhang Zhi-Gang Yu Shi-Ti Cui Mei-Chun Yang China University of Petroleum(East China) 66 Changjiang West RoadQingdao West Coast New AreaQingdao266580ShandongChina University of Calgary 2500 University Dr NWCalgaryT2N 1N4AlbertaCanada Qingdao University of Technology Qingdao266071ShandongChina State Key Laboratory of Offshore oil Exploitation Beijing100028China CNOOC research institute Ltd. Beijing100028China CNPC Tarim oilfield branch Company Korla841000XinjiangChina National Engineering Laboratory for exploration and development of Low-Permeability oil and Gas fields Xi'an710000ShaanxiChina sinopec Matrix Co. LTDQingdao266000ShandongChina

To assess whether a development strategy will be profitable enough,production forecasting is a crucial and difficult step in the *** development history of other reservoirs in the same class tends to be studied to make predictions ***,the permeability field,well patterns,and development regime must all be similar for two reservoirs to be considered in the same *** results in very few available experiences from other reservoirs even though there is a lot of historical information on numerous reservoirs because it is difficult to find such similar *** paper proposes a learn-to-learn method,which can better utilize a vast amount of historical data from various ***,the proposed method first learns how to learn samples before directly learning rules in ***,by utilizing gradients from networks with independent parameters and copied structure in each class of reservoirs,the proposed network obtains the optimal shared initial parameters which are regarded as transferable information across different *** on that,the network is able to predict future production indices for the target reservoir by only training with very limited samples collected from reservoirs in the same *** cases further demonstrate its superiority in accuracy to other widely-used network methods.

关键词： Production forecasting Multiple patterns Few-shot learning Transfer learning

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Shale pore characteristics of Shahejie Formation: Implication for pore evolution of shale oil reservoirs in Dongying sag, north China

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Petroleum research 2019年第2期4卷 113-124页

作者： Shun Zhang Huimin Liu Min Wang Xinjin Liu Huilai Liu Youshu Bao Weiqing Wang Runze Li Xin Luo Zhengwei Fang research institute of Petroleum exploration and development Sinopec Shengli Oilfield CompanyShandongDongying257022China Postdoctor scientific research Stations Sinopec Shengli Oilfield CompanyShandongDongying257000China Petroleum development Center of shengli oilfield ShandongDongying257022China Petroleum development Center of shengli oilfield Beijing100007China Chongqing Gas field of PetroChina Southwest oil&Gasfield Company Chongqing400021China

The pore characteristics of shale reservoirs in the lower submember of Member 3 to upper submember of Member 4 of Shahejie Formation in Dongying sag are analyzed,influences of mineral content and organic matter content on porosity and pore size are also investigated,and through the diagenetic thermal simulation experiment,the main pore evolution is further *** results show that the pore structure of shale reservoirs is complex,the micron-nanometer pores can storage liquid hydrocarbons,and the free-phase crude oil is mainly distributed in intergranular dissolution pores of calcite,recrystallized intergranular pores,intergranular shrinkage fractures of clay mineral which have large pore *** minerals and organic matter content directly influence porosity and pore size of shale reservoirs,relationship between porosity and content of felsic mineral as well as content of organic matter content is linear and positive,while relationship between content of carbonated mineral is *** the buried depth from 2500 to 3500 m,concentration of organic acid from hydrocarbon generation and expulsion of organic matter,increasing range of pressure coefficient,are well corresponding to highporosity intervals;pore formation in shale oil reservoirs are almost controlled by diagenetic evolution of clay minerals;framework storage spaces formed by carbonate grain crystals as well as intergranular and intergranular dissolution pores of carbonate increases porosity of shale oil reservoirs;local increase of porosity at the depth of 3500e3800 m is mainly caused by coupling of hydrocarbon-generating overpressure and dissolution,and size,distribution and connectivity of pores are enhanced obviously.

关键词： Shale oil Pore and fracture Diagenesis Clay mineral transformation Dissolution Recrystallization Hydrocarbon-generation and acid expulsion Paleogene Dongying sag

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Flow characteristics of silicon oil in nanochannels

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Journal of Hydrodynamics 2021年第6期33卷 1282-1290页

作者： Yong Wang Fu-quan Song Kai Ji Ye-heng Sun Wei-yao Zhu Xiao-hong Wang School of Engineering Science University of Science and Technology of ChinaHefei 230026China School of Petrochemical and Energy Engineering Zhejiang Ocean UniversityZhoushan 316022China exploration and development scientific research institute of shengli oil field branch of sinopec Dongying 257015China Civil and Resource Engineering School University of Science and Technology BeijingBeijing 100083China

The nonlinear flow of liquids through nanoscale channels play an important role in the separation and purification properties of porous membranes,the manufacture of biofilm ionic channels and microfluidic chips,the production of micro electro-mechanical *** oil flow experiments were conducted through anodic alumina films with pore sizes of 26,67,89,and 124 nm,in which flow mechanism and characteristics of the oil through the nanoscale channels were *** nanoflow features are revealed:(1)The experimental flow rate is less than the theoretical flow rate through nanochannels,as solid-liquid interaction increasing flow resistance.(2)At small shear rate,the boundary layer is one,indicating existence of a threshold pressure of oil flow through nanochannels.(3)The boundary layer decreases with the increasing of shear rate,and it rapidly decreases as shear rate increases when the value of shear rate is small.(4)The drag coefficient decreases nonlinearly with increasing shear rate,decreasing more slowly when value of shear rate is big,and trending towards 1 in the case of large shear *** is shown that the non-linearity of flow is induced by great solid-liquid interaction in nano and microscale,and increasing the driving force can raise the efficiency at the nanometer scale.

关键词： Nano and microflow nanofluid threshold pressure the boundary layer tight reservoir

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Numerical simulation on proppant migration and placement within the rough and complex fractures

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Petroleum Science 2022年第5期19卷 2268-2283页

作者： Tian-Kui Guo Zhi-Lin Luo Jin Zhou Yuan-Zhi Gong Cai-Li Dai Jin Tang Yang Yu Bing Xiao Bao-Lun Niu Ji-Jiang Ge College of Petroleum Engineering China University of Petroleum(Huadong)Qingdao266580ShandongChina Southwest oil and Gas field Company PetroChinaChengdu610051SichuanChina exploration Division Tarim Oilfield CompanyPetroChinaKorla841000XinjiangChina Dongxin oil Production Plant Shengli Oil Field BranchSinopecDongying257100ShandongChina research institute of Petroleum exploration and development PetroChinaBeijing100083China Zhongyuan Petroleum Engineering Company SinopecPuyang457001HenanChina Zhongyuan oilfield Company SinopecPuyang457001HenanChina

Hydraulic fracturing is a key technology for the development of unconventional hydrocarbon *** proppant placement morphology determines the fracture conductivity,thus affecting the reservoir stimulation *** this paper,the proppant migration and placement within complex fractures was studied by considering the fracture wall roughness through computational fluid mechanics-discrete element method(CFD-DEM)in numerical simulation,which is a key approach to study the proppant migration and *** results show that the proppant placement non-uniformity,proppant migration capacity,and proppant volume filled in the far-end and the secondary branched fracture are enhanced within the rough fracture compared with those within smooth *** proppant migration capacity is increased within the fracture at low inclination angles(branched *** injection location mainly affects the proppant filling degree within the near-wellbore *** with the upper injection,the middle and lower injection is not beneficial to filling of proppants within the near-wellbore fracture.

关键词： Hydraulic fracturing Proppant migration and placement Rough fracture wall Complex fracture CFD-DEM coupling

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Experimental characterization and mechanism of hydraulic pulsation waves driving microscopic residual oil

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Petroleum exploration and development 2022年第6期49卷 1411-1422页

作者： WU Feipeng LI Na YANG Wei CHEN Jiahao DING Bujie XIA Lei LIU Jing WANG Cong WANG Lushan China University of Petroleum(East China) Qingdao 266000China research institute of exploration and development Yanchang Oil Field CompanyYan’an 716000China sinopec research institute of Petroleum Engineering Co. LtdDongying 257000China shengli oilfield branch of China Petroleum&Chemical Corporation Dongying 257000China

To clarify microscopic mechanisms of residual oil displacement by hydraulic pulsation wave,microscopic visualization experiments of hydraulic pulsation wave driving residual oil were carried out by using the microscopic visualization device of pulsating water *** the four types of residual oil left in the reservoir after water flooding,***,column,cluster,and blind end residual oils,hydraulic pulsation waves broke the micro-equilibrium of the interface by disturbing the oil-water interface,so that the injected water invaded into and contacted with the remaining oil in small pores and blind holes,and the remaining oil was pushed or stripped to the mainstream channel by deformation superposition effect and then carried out by the injected *** the displacement,the pulsation frequency mainly affected the cluster and blind end remaining oil,and the hydraulic pulsation wave with a frequency of about 1 Hz had the best effect in improving the *** pulsation amplitude value mainly affected the membrane and column residual oil,and the larger the amplitude value,the more remaining oil the hydraulic pulsation wave would *** presence of low intensity continuous flow pressure and holding pressure end pressure promoted the concentration of pulsating energy and greatly improve the recovery of cluster residual *** rise in temperature made the hydraulic pulsation wave work better in displacing remaining oil,improving the efficiency of oil flooding.

关键词： hydraulic pulsation wave microscopic remaining oil oil displacement mechanism disturbance of oil-water interface enhanced oil recovery

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Reservoir space of the Es_3~3–Es_4~1shale in Dongying sag

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International Journal of Mining Science and Technology 2014年第4期24卷 425-431页

作者： Hao Yunqing Chen Fukun Zhu Jingquan Zhang Shoupeng institute of Geology and Geophysics Chinese Academy of Sciences Geological scientific research institute Shengli Oil Field Company Sinopec School of Earth and Space Sciences University of Science and Technology of China

The Es3/3-Es1/4 shales in Dongying sag are source rocks with large reserves of shale oil and gas. For the iden- tification of development characteristics and geological significance of the reservoir space, FM1 logging, core observation, thin section analysis, X-ray diffraction, fluorescence microscopy, scanning electron microscopy, mercury porosimetry, low-temperature nitrogen adsorption, atomic force microscopy, and conventional physical property testing were used to study the petrology and reservoir space of the Es3/3-Es1/4 shale in Dongying sag. The results suggest that the shale is rich in carbonate minerals. Phanero- crystalline stratiform and lamellar argillaceous limestone and calcareous claystone are the oil- and gas-bearing lithofacies. The oil in the micropores is mainly present as membranes and clots. The shale reservoir space has a network structure with veins, carbonate and clay minerals, and micropores among pyrite and the matrix. The results provide the geological framework for future shale oil and gas explora- tion in Dongying sag.

关键词： Shale oil Gas Reservoir space Dongying sag

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research on the direction of secondary migration of oil by making use of nitrogen compounds as tracers in the No. 6 area of the Melut Basin

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Chinese Journal Of Geochemistry 2006年第2期25卷 182-183页

作者：唐友军文志刚窦立荣徐佑德 Key Laboratory of exploration Technologies for oil and Gas Resources Ministry of Education Department of Geochemistry Yangtze University Jingzhou 434023 China China National oil and Gas exploration and development Corporation Beijing 100034 China Geological scientific research institute of shengli oilfield Company SINOPEC China

This paper discussed the direction of secondary migration of oil in the No. 6 area of the Melut Basin by making use of nitrogen compounds as secondary oil migration tracers. From the results, we have found that the occurrence and compositional characteristics of isomeric-nitrogen compounds in crude oil precisely manifest the fractionation effect of oil migration: with increasing secondary migration distance, the absolute concentrations tend to decrease, and the ratio of nitrogen-shielded isomers to nitrogen-exposed isomers tends to increase. It is considered that the main direction of oil migration in the No. 6 area of the Melut Basin is from north to south.

关键词：氮石油地质条件混合物地球化学

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