基于油田多源数据分析的油藏管理研究
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摘要
随着全球市场对石油需求量的逐年增长,各个油田都在努力提高采收率。同时,面对石油资源的不可再生及开采难度和开采成本的增加,如何避免资源的浪费及节约成本是摆在油藏管理者面前的一大难题。将先进的管理理念同先进的信息技术手段相结合,建立先进的油藏管理模式及油藏管理系统,对提高工作效率、降低成本、寻找剩余油、实现油藏的定量化研究等具有非常重要的意义和作用。
     本文以先进的管理理念为指导,着重研究了以油藏数据为基础,以信息技术为手段,建立适合我国油藏管理的新模式。信息技术随着全球化、数字化的快速发展,也在快速地推进与创新。目前,信息技术代表了当代最先进的生产力和先进生产力的发展方向。论文通过多源数据分析与各种数据模型的建立,展现了油藏管理、数据与信息技术三者之间的关系,并在这个基础上应用数字油田三维可视化的先进技术,实现与完成了三维空间的现代油藏管理模式建设。
     本文以柳沟油田为例,根据油藏管理的需要建立了各类数据模型,完善了数据库建设,实现数据审核、专业库向中心库加载、项目库与知识库的数据加载、项目库向中心库返回成果加载功能,并根据数字油田技术采用采用C/S、B/S模式,构建了一个基于多源数据的油藏管理平台。本次论文研究的主要内容与成果有:
     1、基于油田多源数据的分析和研究,并以延长油田柳沟地区为定例,对柳沟油田地质基础做了较为详尽的研究。柳沟油田地处鄂尔多斯盆地中心,油藏管理的地质基础是以侏罗系的延安组和三叠系延长组为主要研究对象,在延安组以延10油层组为主要对象,如延10属河流沉积体系中曲流河亚相沉积,最主要的砂体是边滩砂(或称点坝),延103砂岩体(油砂体)厚度大、分布面积广。隶属印支期形成的柳沟鼻褶群上的构造——岩性油藏。三叠系延长组以长6为主要研究对象,长6主要为三角洲沉积体系,属岩性油藏。
     2、在充分了解研究区地质背景的基础上,采用数字高程模型(DEM)进行确定性建模,建立研究区的地形、地貌三维模型。实现地面三维可视化,并将地面工程中的基本建筑物、油井抽油机等建成模型植入三维可视化地形的原有位置上,可实现地面工程的三维可视化管理。
     3、通过对油井数据的分析、挖掘与建模,将柳沟油田多源离散数据体,应用国际领先的三维可视化软件平台进行了展现,使得在油田开发过程中,更多的数据得到了利用和挖掘。本次利用研究区274口井的井位、高程、测井、测井解释结果,特别是井斜、分层等数据,应用Amira软件完成柳沟地区的三维数字高程模型(DEM)的数据处理和可视化,部分油井的三维空间轨迹的数据处理和可视化,三维地层模型的数据处理和可视化以及柳沟区的三维有限元地层模型的网格制作,完成数字油田的地下油藏的三维可视化建模与开发。
     4、应用多源数据和信息技术的手段表现了地下地层的三维结构和油井空间轨迹的信息,同时完成了网格剖分的前处理工作,为以后进一步开展油藏数值模拟可视化提供了基础条件。该研究过程完成了基本数据处理和数值计算需要的程序编制工作,建立了数据库和数据分析挖掘程序集,实现了三维立体沉浸式显示,这些工作都为以后开展其它研究区的可视化研究提供了必要的软件保障和示范性作用.
     5、利用三维可视化技术完成了柳沟油田的18个地层三维空间模型建立,通过将油田实际数据用可视化软件的处理,我们得到了初步的可视化结果和示范性可视化工作流程,并将所有地层实现三维可视化展示。三维可视化的实现有利于油田管理者和工程技术人员更加直观地了解地下地层的三维构造地层走向,以及层与层之间接触关系及其规律,可直观地发现油田布井中存在的问题、可能的剩余油分布位置和有利油区的储油构造,并十分有利于指导未来油田勘探、开发工作中的重大决策,如补孔布钻,注水二次开发等,可为提高采收率提供技术支持。
With the increasing demand of global market for oil year after year, each oil field striveto improve oil recovery ratio, at the same time, we face the characteristic of non-renewable ofoil, as well as the augmentation of the difficulty of exploitation and mining costs, therefore,how to avoid waste of resources and cost saving is a vital problem for reservoir managers.Combination of advanced management conception and sophisticated information technologymethod, establishment of forward-looking reservoir management model and direction system,both of them have a significant meaning to improve work efficiency, reduce costs, findremaining oil and achieve a quantitative research of oil reservoir.
     The paper establishes a new reservoir management model based on advancedmanagement conception and abundant reservoir data and sophisticated IT method. With therapid development of globalization and digitization, information technology progresses andinnovates quickly. At present, information technology represents the most advancedproductive forces and its development direction. Through the establishment of the originaldata analysis and a variety of data models, the paper shows the relationship among reservoirmanagement, data and information technology. To make use of this relationship and digital oilfield of3D visualization, the construction of modern reservoir management model inthree-dimensional space has been realized and achieved.
     This paper takes Liugou oil field as example, according to needs of reservoirmanagement; it set up various types of data models, perfected database construction,accomplished functions as: data audits, loading from professional library to central repository,loading of project database and knowledge database, loading of feedback from projectdatabase to central repository. It built as well a reservoir management platform withmulti-source data in using C/S and B/S mode. The main contents and results of this thesis areas following:
     1. A detailed research in geological background of Liugou oil field is located in thecenter of Ordos Basin; the geological basis of reservoir management is aimed to studyJurassic Yan'an Formation and Triassic Yanchang Formation. In Yan'an Formation, yan tenreservoir group is considered as the main object of study, because the yan ten belongs to riverdeposition system meandering river sub-facies, the principal sand body is beach sand (or pointbar), the yan103sandstone (oil sand body) has a big thickness and is widely distributed. Alsothere is a lithology reservoir-a structure which was formed under the Indosinian period andwas taken shape on fold group of Liugou nose. Triassic Yanchang group is aimed to studylong six, the long six is mainly deltaic depositional system, consisting of lithologic reservoirs.
     2. On the basis of full understanding of the geological background of the study area, thispaper uses the digital elevation model (DEM) to precede uncertainty modeling and builds upthe study area topography and geomorphology three-dimensional model. All these researchesare designed to complete ground three-dimensional visualization, to implant the basic building and ground engineering and oil well pumping unit into the original position of the3D terrain model, and to realize the management of three-dimensional visualization of theground works.
     3. Multi-source discrete data of Liugou oil field is presented by the world's leading3Dvisualization software platform, through Well analysis of the data mining and modeling,thanks to this method, more and more data is investigated and used. Taking advantage of welllocation, elevation, logging and log interpretation results of274wells of study area,particularly with well inclined and layered data, etc, data processing and visualization of theLiugou region3D digital elevation model (DEM) is completed in utilizing Amira software.Data processing and visualization of three-dimensional trajectory of some of the wells, as wellas data processing and visualization of three-dimensional stratigraphic model andthree-dimensional finite element Liugou District stratigraphic model grid are accomplished atthe same time. The target is to complete three-dimensional visual modeling and developmentof underground reservoir of the digital oil field.
     4. Three-dimensional structures of the subsurface and well space trajectory informationare displayed by quantitative data and visual manner. Completion of the pre-treatment of themeshing of work provides the basic conditions for future further development of numericalreservoir simulation visualization. The study process completes basic data processing andnumerical calculation programming, builds up database and data mining assembly, realizeimmersed manifestation of three-dimensional. All of those work offered necessary softwareprotection and exemplary role for visualization research of other study area.
     5. Making use of3D visualization technology,18Strata3D space model of Liugou oilfield is established. We get a preliminary visualization results and the demonstration videoworkflow by combination of actual oil field data and the visualization software.3Dvisualization display of all strata helps oil field managers, engineers and technicians tounderstand more direct viewing the three-dimensional structure of the underground strata andthe relationship between formation direction and layers. We can find out more directlyproblems of oilfield cloth well, remaining oil distribution location and favorable oiloil-bearing structure, which is very conducive to guide future oil field exploration and to giveimportant decisions during development period, such as fill the hole cloth drill, injection ofsecondary development, etc. This Provides technical support for enhanced oil recovery.
引文
[1] Abbott, L., et al., Breaking Education and Research Barriers with3-D VisualizationCAVE Technology, in NSF-Academic Research Infrastructure White Paper.1996, TheVirginia Tech Research Division
    [2] Al-Bazzaz, W.H.; Al-Mehanna, Y.W.; Gupta, A. Permeability modeling usingneural-network approach for complex Mauddud-Burgan carbonate reservoir[C]. SPE15th Middle East Oil and Gas Show and Conference, v2, p892-906,200
    [3] Aktas, M., et al., iSERVO: Implementing the International Solid Earth Research VirtualObservatory by Integrating Computational Grid and Geographical Information WebServices. Pure and Applied Geophysics,2006.163(11-12): p.2281-2296
    [4] Allcock, B., et al., Data management and transfer in high-performance computationalgrid environments. Parallel Computing,2002.28(5): p.749-771
    [5] Amira, Amira Homepage:3-D Data Visualization.2006, http://www.amiravis.com/
    [6] Bollig, E.F., et al., VLAB: Web Services, Portlets, and Workflows for EnablingCyberinfrastructures in Computational Mineral Physics. Physics of the Earth andPlanetary Interiors,2007.163(1-4): p.333-346
    [7] Bryan, F., Establishing a Petascale Collaboratory for the Geosciences.2005,http://www.geoprose.com/
    [8] Buyya, R., The Virtual Laboratory Project.2001, IEEE Distributed Systems Online
    [9] Callahan, S., et al., Hardware-Assisted Visibility Ordering for Unstructured VolumeRendering. IEEE Transactions on Visualization and Computer Graphics,2005.11(3): p.285-295
    [10] Chin-Purcell, K., Bob: Brick of bytes.1992, AHPCgC, Minnesota SuperComputerCenter.
    [11] Clyne, J. and J. Dennis. Interactive Direct Volume Rendering of Time-Varying Data. inProceedings from Eurographics Data Visualization99Conference.1999
    [12] Cohen, R.E., High-performance computing requirements for the computational solidearth sciences.2005, http://www.geo-prose.com/computational_SES.html
    [13] Cook, R., et al., Image-space visibility ordering for cell projection volume rendering ofunstructured data. Ieee Transactions on Visualization and Computer Graphics,2004.10(6): p.695-707.
    [14] Damon, M., et al., Interactive Visualization of3-D Mantle Convection.2007,University of Minnesota Supercomputing Institute Research Report UMSI p.113
    [15] Dongarra, J.K., K. and A. White, Sourcebook of Parallel Computing. The Sourcebookof Parallel Computing.2003, San Francisco: Morgan Kaufmann Publishers
    [16] Erlebacher, G., D.A. Yuen, and F. Dubuffet, Current Trends and Demands inVisualization in the Geosciences, in Visual Geosciences.2001. p.1610-2924
    [17] Foster, I., Globus Toolkit Version4: Software for Service-Oriented Systems, in IFIPInternational Conference on Network and Parallel Computing.2006, Springer-VerlagLNCS,3779,2-13
    [18] Gara, A., et al., Overview of the Blue Gene/L System Architecture. IBM Journal ofResearch and Development,2005.49(2-3): p.195-212
    [19] Goyette, S., et al., Increasing the Usability and Accessibility of Geodynamic ModellingTools to the Geoscience Community: UnderworldGUI. Visual Geosciences,2007
    [20] Habata, S., M. Yokokawa, and S. Kitawaki, The Earth Simulator System.2007,http://www.owlnet.rice.edu/~elec526/handouts/papers/earthsim-nec.pdf
    [21] Hanyk, L., et al., Visualization of timedependent dynamics of postglacial rebound.Visual Geosciences,2007
    [22] Jordan, K.E., et al., Parallel interactive visualization of3-D mantle convection.Computational Science and Engineering, IEEE,1996.3(4): p.29-37
    [23] Kadlec, B.J., D.A. Yuen, and G. Erlebacher, Visualization and Analysis of MultiterabyteGeophysical Datasets in an Interactive Setting with Remote Webcam Capabilities. Pureand Applied Geophysics,2006.163(11-12): p.2455-2465
    [24] Kameyama, M.C., ACuTEMan: A multigrid-based mantle convection simulation codeand its optimization to the Earth Simulator. Journal of the Earth Simulator,2005.4: p.2-10.
    [25] Kaufman, A. and K. Mueller, Overview of Volume Rendering., in The VisualizationHandbook, C.D. Hasen and C.R. Johnson, Editors.2005, Butterworth-Heinemann:Massachusetts. p.127-124
    [26] Loddoch, A. and J. Schmalzl, Variable quality compression of fluid dynamical data setsusing a3-D DCT technique. Geochemistry Geophysics Geosystems,2006.7(1): p.1-13.
    [27] Ohno, N. and A. Kageyama, Scientific Visualization of Geophysical Simulation Databy the CAVE VR System with Volume Rendering. Physics of Earth and PlanetaryInteriors,2007.163(2007): p.305-312
    [28] Porter, D., Volume Visualization of High Resolution Data Using PC-Clusters.2006,http://www.lcse.umn.edu/hvr/pc_vol_rend_L.pdf
    [29] Schroeder, W.J. and K.M. Martin, Overview of Visualization, in The VisualizationHandbook, C.D. Hasen and C.R. Johnson, Editors.2005, Butterworth-Heinemann:Massachusetts. p.3-35
    [30] Stegman, D.R., et al., gLucifer: Nextgeneration visualization framework forhigh-performance computational geodynamic models, in Eos Trans AGU Fall MeetSuppl.2005
    [31] Wang, S.M., M. Damon, and D.A. Yuen, Visualization in the Earth Sciences: ADiscussion on Various Visualization Methods using amira, in Proceedings of IEEEVisualization Conference.2005: Minneapolis, MN
    [32] Weiskopf, D. and G. Erlebacher, Overview of Flow Visualization, in The VisualizationHandbook, C.D. Hasen and C.R. Johnson, Editors.2005, Butterworth-HeinemannElsevier: Massachusetts
    [33] Xia, F., et al., Research on storage area network in high performance storage system.Computer Engineering and Design,2005.26(7): p.1740-1743
    [34] Yanagawa, T. and K. Suehiro, Software system of the earth simulator. ParallelComputing,2004.30(12): p.1315-1327
    [35] Zia, R., et al., An Approach to a Visual Language for Convective Fluid Flows:Visualization of Geophysical Simulations. Visual Geosciences,1998.3(1): p.1-19
    [36]李海生.矢量场可视化的研究现状与发展趋势.计算机应用研究,2001.8
    [37]晁会霞,基于油田多源数据分析与挖掘的白豹地区储层特征研究[D].长安大学学位论文,2008
    [38]唐泽圣,三维数据场可视化.1999,北京:清华大学出版社.
    [39]柴贺军,黄地龙,黄润秋,等.岩体结构三维可视化及其工程应用研究[J].中国岩土学报,2001,(2)217-220
    [40]长庆油田石油地质志编写组.中国石油地质志(卷十二)[M].北京:石油工业出版社,1992:62-78,133-148
    [41] Chapman P, Clinton J, Kerber R, et al, CRISP-DM1.0Step-by-step data miningguide[M]. Chicapo:Spss Inc,2000,13~34
    [42] C. Romero and S. Ventura Educational data mining: A survey from1995to2005[J].Expert Systems with Applications.2007,33(1):135-146
    [43]陈昌彦,张菊明,杜永廉,等.边坡工程地质信息的三维可视化及其在三峡船闸边坡工程中的应用[J].岩土工程学报,1998,20(4):1-6
    [44]陈强,王宏琳.数字油田:集成油田的数据、信息、软件和知识[J].石油地球物理勘探,2002,37(1):90-96
    [45]陈述彭.地理信息系统导论[M].北京:科学出版社,1999
    [46]陈述彭.地理信息系统的基础研究—地球信息科学[J].地球信息,1997(3):11-20
    [47]陈文伟,黄金才,赵新昱.数据挖掘技术[M].北京工业大学出版社,2002:11-78
    [48]陈中祥,岳超源.空间数据挖掘的研究与发展[J].计算机工程与应用,2003,39(3):5
    [49]承继成,郭华东,薛勇.数字地球导论[M].北京:科学出版社,2007
    [50]戴启德,纪友亮.油气储层地质学[M].北京:石油大学出版社,1996
    [51] De Jonge Gert J, Stundner Michael. How Routine Reservoir Surveillance with NeuralNetworks and Simplified Reservoir Models can Convert Data intoInformation[J].Proceedings of the European Petroleum Conference,2002,391-403
    [52] Denney Dennis. Data mining for zonal allocation and increased production in Kernriver[J]. JPT, Journal of Petroleum Technology,2004,56(11):69-71
    [53] Desbarats A J,Roussos D.Geostatistical modeling of transmissibility for2D reservoirstudies.SPE Formation Evaluation,1990,437-443
    [54] Elvind D,Tjisen C B,Henning O.A two-stage stochastic model applied to a North Seareservoir.JPT,1992,402-408
    [55] ESRI Inc, Using ArcGIS geostatistical analyst[M]. New York: Environmental SystemResearch Institute Press,1999:125-189
    [56]方海东,刘义怀,施斌,等.三维地质建模及其工程应用[J].水文地质工程地质,2002,3:52-55
    [57]高文玲.石油地质信息系统中的数据挖掘与决策支持方法的研究[D].西安建筑科技大学学位论文,2004
    [58]高志亮.鄂尔多斯盆地吴旗地区中生界油气聚集与勘探[M].西安:西安地图出版社,2001
    [59]龚健雅.地理信息系统原理[M].北京:科学出版社,2001
    [60]苟学敏,陈季高,张华义,等.基于GIS的油气勘探开发数据库建设[J].天然气工业,2002,22:126-129
    [61] G. Pistesky-Shaphiro, An overview of knowledge discovery in databases: recentprogress and challenges, Rouhg Sets, Fuzzy Sets and Knowledge Discovery,1994,1–11
    [62] Grieser B, Shelley B., Johnson B.J.et al,. Data analysis of barnett shalecompletions[J].SPE Production and Operations Symposium, Proceedings, SPEProduction and Operations Symposium2007-Boom Times or a New Reality,2007,23-34
    [63]郭兴凯.数据流挖掘技术的研究[D].黑龙江大学学位论文.2005.6
    [64] Haldorsen H H, Elvind D.Stochastic modeling.JPT,1990,404-412
    [65]韩客松,王永成.文本挖掘、数据挖掘和知识管理—二十一世纪的智能信息处理[J].情报学报,2001,20(1):100
    [66]韩家炜.数据挖掘:概念与技术[M].机械工业出版社,2000:8-26
    [67]何生厚.数字油田的理论、设计与实践[M].北京:科学出版社,2001
    [68]何生厚,韦中亚.“数字油田”的理论与实践[J].地理学与国土研究,2002,(2):5-7
    [69]何鲜,石占中,周宗良,等.难动用储量油藏评价方法[M].石油工业出版社,2005:57-70
    [70]何自新等著.鄂尔多斯盆地演化与油气[M].北京:石油工业出版社,1997
    [71]胡光道.地质数据仓库设计中的几个问题[J].地球科学一中国地质大学学报,1999,24(5):522-524
    [72]胡永刚.数据挖掘中可视化技术综述[J].计算机与现代化,2004(10):32-33
    [73] Huang Ji-Xin, Peng Shi-Mi, Huang Shu-Wang.Study of integrating seismic and loggingdata in fluvial reservoir modeling[J].Journal of China University of Mining andTechnology,2007,36(1):126-131
    [74]黄志澄.数据可视化技术及其应用展望[J],电子展望与决策,1999,6:3-9
    [75]贾爱林.储层地质模型建立步骤[J].地学前缘,1995,2(4):221-225
    [76]焦养泉,朱培民,雷新荣,等.地学空间信息三维建模与可视化—鄂尔多斯盆地及相关领域的实践[M].北京:科学出版社,2006
    [77] Kerong Ben,张彦铎.人工智能[M].北京:清华大学出版社,2006,80-85
    [78] Laurent Ailleres. New gocadr developments in the field of3-dimensional structuralgeophysics [J]. Journal of the Virtual Explorer,2000,1(28):58-64
    [79]雷启鸿,谢启超,何小娟,等.白豹油田长6储层特征及开发对策[J].低渗透油气田,2007,12(3):89-93
    [80]李存贵.低渗透储层三维地质模型和剩余油分布预测[M].北京:石油工业出版社,2003
    [81]李德仁.论空间数据挖掘和知识发现[J].武汉大学学报(信息科学版),2001,26(6):491
    [82]李德仁.论空间数据挖掘和知识发现的理论与方法[J].武汉大学学报(信息科学版),2002,27(3):221
    [83]李德仁,王树良,李德毅.空间数据挖掘理论与应用[M].北京:科学出版社,2006
    [84]李功权,陈恭洋,吴东胜,等.油气储层建模中的空间数据挖掘技术[J].石油天然气学报,2006,28(4):47-49
    [85]李健.三角洲低渗透储层流动单元四维模型及剩余油预测[M].北京:石油工业出版社,2004
    [86]李小涛,杨锋杰,宋小宁.遥感影像三维可视化实现[J].山东科技大学学报,2003,22(4):43-44
    [87]李裕伟. GIS-实现地质工作现代化的工具[J].物探化探计算技术,1995,(2):76-79
    [88]李振华,胡光道,陈建国.地质数据仓库的特点及其数据组织[J].地球科学一中国地质大学学报,1989,24(5):535-538
    [89]李智,陈强.“数字油田”的设计与应用[J].地球信息科学,2002,(4):97-100
    [90]厉青.油气地质异常信息挖掘与定量分析研究-以临清坳陷东部油气勘探应用为例[D].中国地质大学博士学位论文,2002.5
    [91]梁政.油田地面数字化管理系统研究[J].石油规划设计,2005,15(3):11-13
    [92]林承焰,侯加根,侯连华等.油气储层三维定量地质建模方法和配套技术[J].石油大学学报(自然科学版),1996,20(4):20-25
    [93]刘吉余,李艳杰,于润涛.储层综合定量评价系统开发与应用[J].物探化探计算技术,2004,26(1):33-36
    [94]刘宇.空间数据挖掘理论与方法的研究[J].微型电脑应用,2000,16(8):15
    [95]林加恩.油田信息综合应用平台的设计[J].石油工业计算机应用,2006,14(1):15-18
    [96]柳炳祥,田原,徐文元.“数据挖掘技术”带来了什么[J].中国建材,2006,11:99-101
    [97]罗平,应凤祥.储集岩基础实验分析新技术与新方法[M].北京:石油工业出版社,2002
    [98]吕红华,任明达,柳金诚,等. Q型主因子分析与聚类分析在柴达木盆地花土沟油田新近系砂岩储层评价中的应用[J].北京大学学报(自然科学版),2006,42(6):740-745
    [99]马立文,窦齐丰,彭仕宓,等.用Q型聚类分析与判别函数法进行储层评价—以冀东老爷庙油田庙28X1区块东一段为例[J].西北大学学报(自然科学版),2003,33(1):83-86
    [100] Masoud Nikravesh, Roy D. Adams and Raymond A. Levey Soft computing: tools forintelligent reservoir characterization (IRESC) and optimum well placement (OWP)[J].Journal of Petroleum Science and Engineering.2001,29(3-4):239-262
    [101]马志勇,张军海.数据挖掘与地学数据分析相结合的探讨[J].测绘科学,2006,31(6):109-113
    [102]穆龙新,贾爱林.扇三角洲沉积储层模式及预测方法研究[M].北京:石油工业出版社,2003
    [103]彭仕宓,熊琦华,王才经,等.储层综合评价的主成份分析方法[J].石油学报,1994,15(增刊):187
    [104] P.Rodrigues,J.Gama and J.P.Pedroso.Hierarchical time~series clustering for datastreams. In: The1st international workshop on knowledge discovery in data streams inconjunction with the15th European Conference on Machine Learning(ECML04).Pisa:2004,22-31
    [105]裘亦楠,薛叔浩.油气储层评价技术[M].北京:石油工业出版社,1994.157~236
    [106]裘亦楠.储层地质模型[J].石油学报,1941,12(4):55-52
    [107]曲道庆.油田信息数据仓库与数据挖掘[J].油气田地面工程,2007,26(7):45-46
    [108]宋子齐.灰色系统理论精细评价油气储层的分析准则、处理方法及应用[J].系统工程理论与实践,1997,17(3):74-82.
    [109]宋子齐,谭成仟,王建功,等.储层定量评价指标和权系数研究[J].测井技术,1997,21(5):351-355.
    [110]宋志军,潘志,胡海峰,等.神经网络数据挖掘工具用于剩余油分布研究[J].石油大学学报(自然科学版),2003,27(1):105-106
    [111]唐国维,申静波,赵建民.计算机应用知识发现和数据挖掘及其在油田生产辅助决策中的应用[J].自动化技术与应用,2003,22(4):58-60
    [112]田锋,王权.数字油田研究与建设的现状和发展趋势[J].油气田地面工程,2004,23(11):52-53
    [113] Tom Soukup Ian Davidson著,朱建秋,蔡伟杰译.可视化数据挖掘-数据可视化和数据挖掘的技术与工具[M].北京:电子工业出版社,2004
    [114]王宏琳.石油勘探开发信息技术发展态势—数据集成、应用集成和知识集成[J].石油工业计算机应用,2007,15(1):6-13
    [115]王宏威.油田数据挖掘技术的研究与应用[D].大庆石油学院硕士研究生学位论文.2005,3
    [116]王钦军,薛林福.数据挖掘技术及其在地学中的应用[J].世界地质,2000,19(3):235-239
    [117]王树良.基于数据场与云模型的空间数据挖掘和知识发现[D].武汉:武汉大学博士学位论文,2002
    [118]汪忠德,王新海,瞿建华,等.数据挖掘技术在石油勘探与开发中的研究及应用[J].石油工业计算机应用,2007,15(1):17-20
    [119]吴冲龙,刘刚,毛小平,等.地质信息技术导论[M].高等教育出版社,2007,283-305
    [120]吴东胜.隐蔽油气藏勘探等信息集成化研究[D].武汉:中国地质大学博士学位论文,2005.5
    [121]武强,徐华.三维地质建模与可视化方法研究[J].地球科学,2004,34(1):56-60
    [122]武森,高学东,[德]M.巴斯蒂安.数据仓库与数据挖掘[M].冶金工业出版社,2004,148-322
    [123]吴立新.数字地球、数字中国与数字矿区[J].矿山测量,2000,(1):6-9.
    [124]吴立新,殷作如,邓智毅,齐安文,杨可明.论21世纪的矿山—数字矿山[J].煤炭学报,2000,25(4):337-342
    [125]吴良刚,周海涛.一种基于数理统计的数据挖掘方法研究[J].计算机与信息技术,2001,96(9):1-5
    [126]吴树鹏;熊华平.油田开发数据挖掘技术的实现与应用[J].大庆石油地质与开发,2002,21(3):49-51
    [127] Xavier Emery. Simulation of geological domains using the plurigaussian model: Newdevelopments and computer programs [J]. Computers&Geosciences,2007,33(9):1189-1201
    [128]谢邦昌.数据挖掘Clementine应用实务[M].北京:机械工业出版社,2008
    [129]行小帅.数据挖掘的聚类方法[J].电路与系统学报.2003,8(1):59-68
    [130]熊和金,陈德军.基于灰色系统理论的数据挖掘技术[J].系统工程与电子技术,2004,26(2):184-186
    [131]徐凤根,朱兴珊,颜其彬,等.储层定量评价中指标权重的计算途径[J].石油学报,1996,17(2):291
    [132]徐雪琪.基于统计视角的数据挖掘研究[D].浙江工商大学博士学位论文,2007
    [133]杨俊杰.鄂尔多斯盆地构造演化与油气分布规律[M].北京:石油工业出版社,2002
    [134]姚光庆.钱水三角洲分流河道砂体储层特征[J].石油学报,1995,15(1):24-31
    [135]于兴河,李剑峰.油气储层研究所面临的挑战与新动向[J].地学前缘,1995,2(4):213-220
    [136]张金森,胡孝林,张丽焕.三维可视化技术与油气藏综合评价[J].中国海上油气(地质),2001,15(5):356-359
    [137]张萌,黄思静,冯文新,等.巧解砂岩分类三角图[J].成都理工学院学报,2005,32(4):423-429
    [138]张仕强,刘正中,陈晓华等.油气田开发数据信息管理系统研究及应用[J].天然气工业,2002,22(3):64-66
    [139]张雪松,毛云龙,檀竹南.数据挖掘技术的研究应用综述[J].中国石油和化工,2008,12:60-62
    [140]赵红格,刘池洋.物源分析方法及研究进展[J].沉积学报,2003,21(3):415-409
    [141]周海燕.空间数据挖掘技术及其应用[J].测绘通报,2002,37(2):11.
    [142]邹永玲,韩玲,杜子涛,等.鄂尔多斯盆地的三维可视化及其应用[J].盐城工学院学报(自然科学版),2005,18(2):35-37
    [143]数据挖掘入门0.9版: http://datamining.126.com
    [144] Thakur G C. Reservoir management: A synergistic approach[C]. presented at the SPEPermian basin oil and gas recovery conference, Midland, Texas, March8-9, SPE20138,1990.
    [145] Wiggins M L,Startzman R A. An approach to reservoir management [C].ReservoirManagement Panel Discussion, SPE65th Ann Tech Conf&Exhibition, New Orleans,LA, September23-26, SPE20747,1990.
    [146] Haldorsen H H and Van Golf-Racht T. Reservoir Management into the Next Century.Paper NMT890023presented at the1989Centennial Symposium at New Mexco Tech.Socorro. Oct.16-19
    [147]唐世荣,刘宏斌.国外现代油藏管理文集[M].北京:石油工业出版社,1995
    [148]美国石油工程师学会.现代油藏管理[M].赵业卫,崔士斌,译.北京:石油工业出版社,2001.
    [149]刘平良.基层油藏经营管理与创新增效[J].经营管理,2004,5:60-61
    [150] Lue De Raedl, Amo Siebes. Principles of data mining and knowledge discovery[M].湖南文艺出版社,2001
    [151]王晓芳.数据挖掘及其在储层评价中的应用[D].西南石油学院2005
    [152] De Jonge, Gert; Texaco, Chevron; Stundner, Michael; Zangl, Georg. AutomatedReservoir Surveillance through Data Mining Software[C].Offshore Europe Conference-Proceedings, p195-200,2003
    [153]檀朝东,岳晶晶,吴丽烽,檀竹南.数据挖掘技术在油藏挖掘者软件中的应用[J].中国石油和化工.2010(10)
    [154]谭锋奇,李洪奇,孟照旭,郭海峰,李雄炎.数据挖掘方法在石油勘探开发中的应用研究[J].石油地球物理勘探.2010(01)
    [155]石广仁.数据挖掘在石油勘探数据库中的应用前景[J].中国石油勘探.2009(01)
    [156]朱丽萍,李雄炎,李洪奇.基于模型驱动数据挖掘的低阻油层识别方法[J].大庆石油学院学报.2010(04)
    [157]贾爱林.中国储层地质模型20年[J].石油学报.2011(01)
    [158]徐慧,李发荣.油藏管理实时优化[J].国外油田工程.2010(08)
    [159]孙金凤,张在旭.油田公司油藏管理可视化建设与应用研究[J].油气田地面工程.2010(10)
    [160]范玉平.精细油藏管理实现潜山油藏高效开发[J].中国石油和化工标准与质量.2012(13)
    [161]石启新,刘广生.基层采油单位油藏经营管理模式探索[M].北京:石油工业出版社,2001
    [162]张朝琛.面向21世纪的集成化油藏经营[J].世界石油工业,1997,4(13)

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