尕斯地区E_3~2油藏测井综合评价研究
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摘要
为了解决尕斯地区E_3~2储层岩性复杂、物性变化大、非均质严重、有效储层划分、流体性质识别困难的问题,必须开展对E_3~2复杂油气储层的理论与方法的测井综合评价研究。E_3~2地区储层岩性识别困难,岩性不纯,多为泥灰岩或藻灰岩储层,单纯的利用岩心观察,试油资料,物性资料及常规测井资料来判断地层岩性是非常困难的。本文结合斯仑贝谢的FMI和ECS测井新技术,以岩心为标定,在系统观察岩心和裂缝发育规律总结的基础上,首次在该油田解决了岩性识别和灰质含量定量求取的技术。针对藻灰岩是本地区重要的储集岩性,通过测井交会图的方法对藻灰岩进行测井响应分析,厚度统计分析,选取厚度较大的、FMI图像特征典型的井进行横向对比或通过岩心标定、岩石薄片进行井的横向对比。
对储层的主要储集空间进行分析,对裂缝特征(产状,类型),形成机制以及充填机制进行分析,利用地层微电阻率扫描成像测井对裂缝的参数进行定量地计算。针对缝洞孔隙度标定问题,首次采用以全直径岩心渗透率大于0.1,常规岩心分析渗透率小于0.1作为区分岩心有无裂缝的标志,进行了统计研究取得了很好的地质效果。确定岩电参数a,b,m,n,分别计算储层的有效孔隙度,含油饱和度,渗透率,地层水电阻率,应用统计方法中较为直观的饼图、直方图、交会图和测井综合图来研究四性关系。
针对本地区流体性质识别的困难,开展感应侧向比值判别法、核磁共振测井移谱差谱法、横波时差重叠、纵横波速度比法、纵波等效弹性模量差比法、流体声阻抗比值法、弹性模量比差比法、含氢指数重叠法、流体压缩系数法、流体识别综合法等流体性质识别方法研究,并构造了流体识别指数,取得了良好的效果。
应用PETREL软件,采用随机建模的方法对E_3~2油藏储层进行三维地质建模。根据研究区的地质特征,建模过程中的储层类型属于离散变量,选用序贯指示模拟方法;储层参数属于连续变量,则选用序贯高斯模拟方法,对储层分别实现构造建模(单井模型、断层模型和层面模型)和属性建模,在构造模型的基础上建立储层参数的三维分布,通过储层参数的分布的叠合研究,在该油田指明了三个有利油气分布区块。
In order to resolve the problem about complex reservoir lithology, great variation in physical property, seriously heterogeneous, available reservoir delineation, identification of fluid type in Gasi E_3~2 area it is necessary to study the well-logging comprehensive evaluation of complex reservoir. The lithology of the Gasi reservoir is difficult to identify. Most lithology is muddy limestone or algal limestone. It is very difficult to decide the formation lithology just using core observation, oil production testing data, physical property data and conventional logging data. In the thesis we firstly develop a technique. The technology is combined with FMI and ECS from Schlumberger, and calibrated by core. It is based on observing core and the law of fracture development after thorough analysis and calibration. Algal limestone is the important reservoir lithology in this zone. The logging response and thickness statistics of algal limestone are analyzed by logging cross plot. The wells with considerable thickness and typical FMI image characteristics are selected to do lateral comparison. The lateral comparison can also be carried out by core calibration and rock thin section.
We analyze the main storage space of reservoir, the fracture feature (attitude, types), forming and filling mechanism. The fracture parameters are quantitatively calculated by FMI. According to the calibration of fracture porosity, that full diameter cores analysis permeability is greater than 0.1 and that conventional core analysis permeability is smaller than 0.1 are used to decide whether the cores has the fracture. The statistical analysis is performed on those cores. A good geological result was obtained. The rock electric characteristics (a, b, m and n) are determined. The reservoir effective porosity, oil saturation, permeability and formation water resistivity are also obtained. The pie chart, bar chart, cross plot and logging synthetic graph are applied to study the relationship of the four properties’relations.
According to the difficulty of identifying fluid in this area, we apply some methods to identify the fluid type and develop the index of fluid identification. Those methods include induction-lateral ratio method, NMR shift differential spectrum method, S-wave transit time overlap, P-wave and S-wave velocity ratio method, difference-ratio method of P-wave equivalent elastic modulus, ratio method of fluid acoustic impedance, difference-ratio method of elastic modulus ratio, hydrogen index overlap method, fluid compressibility method. A good result was obtained by those methods.
The 3D geological model of the Gasi area is generated using random model based on PETREL software. According to the geological property of the research area, we apply sequence indicator simulation method if the reservoir type is discrete variable. Sequence Gauss simulation method is used if the type of reservoir property is continuous variable. Structural model (single well model, fault model and bedding model) and property model are built. The 3D distributions of reservoir parameters are established based on structural model. Three advantage oil distribution of the oil field are pointed out through overlap of the reservoir parameters distributions.
对储层的主要储集空间进行分析,对裂缝特征(产状,类型),形成机制以及充填机制进行分析,利用地层微电阻率扫描成像测井对裂缝的参数进行定量地计算。针对缝洞孔隙度标定问题,首次采用以全直径岩心渗透率大于0.1,常规岩心分析渗透率小于0.1作为区分岩心有无裂缝的标志,进行了统计研究取得了很好的地质效果。确定岩电参数a,b,m,n,分别计算储层的有效孔隙度,含油饱和度,渗透率,地层水电阻率,应用统计方法中较为直观的饼图、直方图、交会图和测井综合图来研究四性关系。
针对本地区流体性质识别的困难,开展感应侧向比值判别法、核磁共振测井移谱差谱法、横波时差重叠、纵横波速度比法、纵波等效弹性模量差比法、流体声阻抗比值法、弹性模量比差比法、含氢指数重叠法、流体压缩系数法、流体识别综合法等流体性质识别方法研究,并构造了流体识别指数,取得了良好的效果。
应用PETREL软件,采用随机建模的方法对E_3~2油藏储层进行三维地质建模。根据研究区的地质特征,建模过程中的储层类型属于离散变量,选用序贯指示模拟方法;储层参数属于连续变量,则选用序贯高斯模拟方法,对储层分别实现构造建模(单井模型、断层模型和层面模型)和属性建模,在构造模型的基础上建立储层参数的三维分布,通过储层参数的分布的叠合研究,在该油田指明了三个有利油气分布区块。
In order to resolve the problem about complex reservoir lithology, great variation in physical property, seriously heterogeneous, available reservoir delineation, identification of fluid type in Gasi E_3~2 area it is necessary to study the well-logging comprehensive evaluation of complex reservoir. The lithology of the Gasi reservoir is difficult to identify. Most lithology is muddy limestone or algal limestone. It is very difficult to decide the formation lithology just using core observation, oil production testing data, physical property data and conventional logging data. In the thesis we firstly develop a technique. The technology is combined with FMI and ECS from Schlumberger, and calibrated by core. It is based on observing core and the law of fracture development after thorough analysis and calibration. Algal limestone is the important reservoir lithology in this zone. The logging response and thickness statistics of algal limestone are analyzed by logging cross plot. The wells with considerable thickness and typical FMI image characteristics are selected to do lateral comparison. The lateral comparison can also be carried out by core calibration and rock thin section.
We analyze the main storage space of reservoir, the fracture feature (attitude, types), forming and filling mechanism. The fracture parameters are quantitatively calculated by FMI. According to the calibration of fracture porosity, that full diameter cores analysis permeability is greater than 0.1 and that conventional core analysis permeability is smaller than 0.1 are used to decide whether the cores has the fracture. The statistical analysis is performed on those cores. A good geological result was obtained. The rock electric characteristics (a, b, m and n) are determined. The reservoir effective porosity, oil saturation, permeability and formation water resistivity are also obtained. The pie chart, bar chart, cross plot and logging synthetic graph are applied to study the relationship of the four properties’relations.
According to the difficulty of identifying fluid in this area, we apply some methods to identify the fluid type and develop the index of fluid identification. Those methods include induction-lateral ratio method, NMR shift differential spectrum method, S-wave transit time overlap, P-wave and S-wave velocity ratio method, difference-ratio method of P-wave equivalent elastic modulus, ratio method of fluid acoustic impedance, difference-ratio method of elastic modulus ratio, hydrogen index overlap method, fluid compressibility method. A good result was obtained by those methods.
The 3D geological model of the Gasi area is generated using random model based on PETREL software. According to the geological property of the research area, we apply sequence indicator simulation method if the reservoir type is discrete variable. Sequence Gauss simulation method is used if the type of reservoir property is continuous variable. Structural model (single well model, fault model and bedding model) and property model are built. The 3D distributions of reservoir parameters are established based on structural model. Three advantage oil distribution of the oil field are pointed out through overlap of the reservoir parameters distributions.
引文
[1]唐士跃,易德彬,保吉成.测井技术在尕斯油田下干柴沟组上段灰岩储层岩性识别中的应用[J].石油天然气学报,2006,28(4):301-303.
[2] A Poupon ,ME Loy, Tixier MPA. Contribution to Electric Log interpretation in shaly sands[C]. Transactions of the American Institute of Mechanical,1954:34-39.
[3] MH Waxman, LJM Smith. Electrical conductive in oil-bearing shaly sands[C].42nd Annual fall meeting,1967:23-28.
[4] BZ Shang, JG Hamman, HL Chen. A model to correlate permeability with efficient porosity and irreducible water saturation[C]. SPE Annual Technical Conference and Exhibition,2003:44-47.
[5]范宜仁,周灿灿.低矿化度条件下泥质砂岩阿尔奇参数研究[J].测井技术,1997,21(3):200-204.
[6]谢然红,冯启宁.低电阻率油气层物理参数变化机理研究[J].地球物理学报,2002,45(1):139-146.
[7]田中元,闫伟林,秦开明.淡水泥浆侵入条件下储层电阻率的变化研究[J].测井技术,2003,27(2):113-117.
[8]李宁,付有升,杨晓玲等.大庆流纹岩全直径岩心实验数据分析[J].测井技术.2005,29(6):480-483.
[9]曾文冲.低电阻率油气层的类型,成因及评价方法(上)[J].地球物理测井,1991,15(1):6-12.
[10]邵维志,李浩等.大港白头水地区低阻油气气层测井评价[J].测井技术,2001,25(2):127-130.
[11]王谦,莫修文,李舟波等.用常规测井资料评价塔北低阻储层孔隙组分的方法[J].大庆石油地质开发,2004,23(6):78-79,85.
[12]杨斌,匡立春,孙中春等.一种用于测井油气层综合识别的支持向量机方法[J].测井技术,2005,29(6):511-514.
[13]潘和平,樊政军,马勇.低阻油气层识别方法研究[J].天然气工业,2006, 26(2) :66-68.
[14]Harris,D.G. The role of geology in reservoir simulation studies[J]. JPT, 1975,27:625-632.
[15]Matheron G. The Theory of Regionalized Variables and its Applications [M].Occludes Mines, Fontainebleau, France,1971.
[16]Matheron G. The intrinsic random functions and their applictions[J],A dunces in Applied Probability, 1973,(5):439-468.
[17]Journel A G. Geostatistics for conditional simulation of forebodes[J].Economic Geology,2000(69):673-680.
[18]Journel A G, Huijbregts C J. Mining Geostatistics [M]. Washington DC: Academic Press, 1978:12-32.
[19]Allen J R L. Studies in fluviatele sedimentation: an exploratory quantitative model for the architecture of avulsion-controlled alluvial sites[J]. Sedimentary Geology,21: 129-147.
[20] Weber K J, Van Geuns. Framework for Constructing Clastic Reservoir Simulation models[J].SPE.1989,SPE19582.
[21] Haldorsen H H, Lake LW. A new approach to shale management in field scale simulation models[J]. SPE,1984,SPE 10976,1-8.
[22] Dubrul G, Haldorsen H H. A review of stochastic models for petroleum Reservoirs[J]. Geostatistics, 1986, 12: 233-247.
[23] Haldorse H H. Simulator parameter assignment and the problem of scale in reservoir engineering. Reservoir Characterization[M]. London: Academic Press, 1986:19-36.
[24] Weber, Meats. How heterogeneity affects oil recovery [J]. Reservoir characterization, 1986,23: 487-544.
[25] Lasseter T J,Waggoner J R, Lake L W. Reservoir heterogeneities and their influence on ultimate recovery[J], Reservoir characterization, 1986:545-559.
[26] Haldorsen H H. Stochastic Modeling of Underground Reservoir Faceies[J].SPE.1987, SPE 16751.
[27] Begg S H, King P. Modeling the effects of shales on reservoir performance Calculation of effective vertical permeability[J]. SPE.1985, SPE 13529:22-25.
[28] Haldorsen H H, Damsleth E. Stochastic Modeling[C]. JPT.1990:404-412.
[29] Geehan G W. Geological prediction of shale continuity in Prudhoe Bay Field[J], Reservoir characterization.1986: 435-444.
[30] Matheron G, Beucher H, Fouguet C. Conditional Simulation of the geometry of flurideltaic resole[C]. 1987,Dallas, Texas: SPE Annual Conference:591-599.
[31]Journel A G,Posa D. Characteristic behavior and order relations for indicator variograms [J].Math Geology, 1990, 22(81): 685-718.
[32] Journel A G,Isaaks E. Conditional indicator simulation :application to a Saskatchewan uranium deposit[J], Math Geology , 1984,16(7):655-718.
[33]Journel A G, Alabert F G. Focusing on spatial connectivity of extreme- valued attributes: stochastic indicator modes of reservoir heterogeneity [C]. SPE. 1988, SPE1823.
[34] Hewett T A. Fractal distributions of reservoir heterogeneity and their influence on fluid transport[C], SPE.1986,SPE 15386.
[35] Emanuel A S, Alameda G K, Behrens R A. Reservoir Performance prediction method based on fractal geostatistics[J], SPE Journal.1989,SPE:311-318.
[36]Hewett T A, Behrens R A.Conditional simulation of reservoir heterogeneity with fractals[J].SPE.1988,SPE18326.
[37]Heam C L,Ebank W J, Ranganath V. Geological factors influencing reservoir performance of the Hartzog Draw Field[J] .Wyoming.JPT,1984:1335-1344.
[38]Ebank W J. Flow unit concept-integrated approach to reservoir description for engineering projects[C]. 1987,AAPG. Ann.Mtg.,Los Angeles.
[39] Haldorsen H H, Damsleth E. Stochastic Modelling [C].JPT, 1990:404-412.
[40]Galloway W E. Geneitc stratigraphic sequences in basin analysis I: Architecture and flooding-surface bounded depositional units[J]. AAPG Bulletin. 1989:25-142.
[41] Cross T. Quantitative dynamic stratigraphy[M]. New Jersey,Prentice Hall, 1990: 622.
[42] Cross T. Field-scale reservoir characterization[M] .Academe Press, 1991:493-497.
[43] Cross T, Raynolds R G. Illustration of correlation techniques, facies prediction and reservoir compartment identification through genetic stratigraphy, Gallup sandstone and Mesa Verde Group(Cretaceous) [C], Foursomes region, USA, Rocky Mountain Association of Geologists. 1993.
[44]Cross T, Lessenger M A. Sediment volume partitioning: rationle forstratigraphic model evaluation and high-resolution stratigraphic correlation [J],NPF Special Publication 8, 1998:171-195.
[45]Cross T. Stratigraphic controls on reservoir attributes in continental strata[J],Earth science frontiers. 2000,7(4):322-350.
[46]邓宏文.美国层序地层研究中的新学派-高分辨率层序地层学.石油与天然气地质[J],1995,16(2):89-97.
[47]邓宏文,王红亮,李熙哲,层序地层基准面的识别、对比技术及应用[J].石油与天然气地质,1996,16(2):89-97.
[48]邓宏文,王红亮,宁宁,沉积物体积分配原理-高分辨率层序地层学的理论基础[J].地学前缘,1995,7(4):305-313.
[49]Deutsch C. GSLIB:Geostatistical software library and users guide[C], New York :Oxford University Press. 1992:1-59.
[50]Damsleth E, Tjisen C B, More H,etc.A two-stage stochastic model Application to a North Sea reservoir[J].JPT :402-408.
[51]Verl G. Sequential Gaussisn cosimulation: A simulation method integrating several types of information[J], Geostatistics-Troia, Kluwer, Dordrecht, Holland, 1991,(1): 543-554.
[52]Suro-Perez V. Stochastic simulation of lithofacies: an improved sequential indicator approach[C]. European conference on the Maths of oil recovery, Paris. 1990:34-90.
[53]Suro-Perez. Indicator principle kriging[J]. Math Geology,1991,23(5):759-788.
[54]Suro-Perez V. Indicator Kriging and simulation based on principal component Analysis [D] , Stanford:Stanford University,1992.
[55]Deutsch C, Journel A. GSLIB:Geostatistical software library and users guide[C], Second Edition: Oxford University Press.1996:128-150.
[56]White C D, Barton M D. Translating outcrop data to flow models, with application to the Ferron sandstone[J]. Society of Petroleum Engineers Reservoir Evaluation and Engineering , 1999,2(4):341-35.
[57]Stephen K D, Dalrymple M. Reservoir simulations developed from and Outcrop of incised valley fill strata[J], AAPG Bulletin , 2002,86(5):797-82.
[58]文健,裘怿楠.油藏早期评价阶段储层建模技术的发展方向[J].石油勘探与开发,1994,21(5):88-93.
[59]裘择楠,贾爱林.储层地质模型10年[J].石油学报,2000,21(4): 101-104.
[60]查明,张一伟.盆地数值模拟方法研究与发展[J].石油大学学报(自然科学版),1992,16(2):106-114.
[61]陈亮,张一伟,熊琦华.开发后期井间剩余油分布预测[J].国外测井技术,1997,12(2):58-66.
[62]吴胜和,熊琦华等.储层建模中随机模型的地质适用性分析[C].北京:石油上业出版社,1998.47-53
[63]寿建峰,王少依,蒙绍兴等.柴达木盆地西部地区第三系湖相藻灰岩油气藏及勘探潜力[J].沉积储层,2004,9(5):59-66.
[64]张振城,孙建孟,马建海等.利用测井资料自动识别藻灰岩[J].吉林大学学报(自然科学版),2005,35(3):382-387.
[65]陈志勇,霍玉雁,贾英兰等.FMI成像测井在柴达木盆地的应用[J].石油天然气学报(江汉石油学院学报),2005,27(5):602-605.
[66]孙加华,肖洪伟,幺忠文等.声电成像测井在储层裂缝识别中的应用[J].大庆石油地质与开发,2006,25(3):100-102.
[67]程华国,袁祖贵.用地层元素测井(ECS)资料评价复杂地层岩性变化[J].核电子学与探测技术,2005,25(3):233-238.
[68]袁祖贵.地层元素测井(ECS)评价油水层[J].核电子学与探测技术,2004,24(2):126-130.
[69]庞巨丰.地层元素中子俘获伽马能谱测井解释理论和方法[J].测井技术,1998,22(2):116-119.
[70]武玉宏,王慧,高红艳.对三孔隙度交会图法进行测井曲线标准化的改进[J].油气地质与采收率,2005,12(2):38-41.
[61]葛华,郑伟.测井曲线标准化:方法和准则[J].测井技术信息,2005,18(2):44-54.
[72]雍世和,张超谟.测井资料综合处理解释[M].北京:石油工业出版社,1996:20-69.
[73]蒋武明,罗晓兰,刘新美.红柳泉油田四性关系研究[J].青海石油, 2004,22(4):36-40.
[74]孙建孟,王永刚.地球物理资料综合应用[M].东营:石油大学出版社,2001:120-150
[75]黄隆基.自然伽马能谱测井原理及应用[M].北京:石油工业出版社,1995:10-55.
[76]陆大卫等.石油测井新技术适用性典型[M].北京:石油工业出版社,2001:33-67.
[77]肖立志,陆大卫等.核磁共振测井资料解释与应用导论[M].第一版.北京:石油工业出版社,2001.10:5-33.
[78]李凤琴等.复杂岩性裂缝性储层测井评价[J].河南石油,2004,18(3):22-24.
[79]刘兴刚,张旭.测井裂缝参数估算方法研究[J].天然气工业.2003,23(4):31-34.
[80]袁祖贵,楚泽涵,方小东.低电阻率油气层评价技术研究[J].特种油气藏,2003,10(6):1-4.
[81]刘顺生,许长福,刘念周等.储层随机地质建模技术在油田开发中的应用[J].新疆石油学院学报,2001,13(3):30-34.
[82]周红,国梁,杨湖川.大王北油田大48井区储层建模研究[J].新疆石油天然气,2006,2(2):40-44.
[83]裘怿楠等.油藏描述[M].北京:石油工业出版社,1996:33-50.
[84]刘泽荣等.油藏描述原理与方法技术[M].北京:石油工业出版社,1993:62-78.
[2] A Poupon ,ME Loy, Tixier MPA. Contribution to Electric Log interpretation in shaly sands[C]. Transactions of the American Institute of Mechanical,1954:34-39.
[3] MH Waxman, LJM Smith. Electrical conductive in oil-bearing shaly sands[C].42nd Annual fall meeting,1967:23-28.
[4] BZ Shang, JG Hamman, HL Chen. A model to correlate permeability with efficient porosity and irreducible water saturation[C]. SPE Annual Technical Conference and Exhibition,2003:44-47.
[5]范宜仁,周灿灿.低矿化度条件下泥质砂岩阿尔奇参数研究[J].测井技术,1997,21(3):200-204.
[6]谢然红,冯启宁.低电阻率油气层物理参数变化机理研究[J].地球物理学报,2002,45(1):139-146.
[7]田中元,闫伟林,秦开明.淡水泥浆侵入条件下储层电阻率的变化研究[J].测井技术,2003,27(2):113-117.
[8]李宁,付有升,杨晓玲等.大庆流纹岩全直径岩心实验数据分析[J].测井技术.2005,29(6):480-483.
[9]曾文冲.低电阻率油气层的类型,成因及评价方法(上)[J].地球物理测井,1991,15(1):6-12.
[10]邵维志,李浩等.大港白头水地区低阻油气气层测井评价[J].测井技术,2001,25(2):127-130.
[11]王谦,莫修文,李舟波等.用常规测井资料评价塔北低阻储层孔隙组分的方法[J].大庆石油地质开发,2004,23(6):78-79,85.
[12]杨斌,匡立春,孙中春等.一种用于测井油气层综合识别的支持向量机方法[J].测井技术,2005,29(6):511-514.
[13]潘和平,樊政军,马勇.低阻油气层识别方法研究[J].天然气工业,2006, 26(2) :66-68.
[14]Harris,D.G. The role of geology in reservoir simulation studies[J]. JPT, 1975,27:625-632.
[15]Matheron G. The Theory of Regionalized Variables and its Applications [M].Occludes Mines, Fontainebleau, France,1971.
[16]Matheron G. The intrinsic random functions and their applictions[J],A dunces in Applied Probability, 1973,(5):439-468.
[17]Journel A G. Geostatistics for conditional simulation of forebodes[J].Economic Geology,2000(69):673-680.
[18]Journel A G, Huijbregts C J. Mining Geostatistics [M]. Washington DC: Academic Press, 1978:12-32.
[19]Allen J R L. Studies in fluviatele sedimentation: an exploratory quantitative model for the architecture of avulsion-controlled alluvial sites[J]. Sedimentary Geology,21: 129-147.
[20] Weber K J, Van Geuns. Framework for Constructing Clastic Reservoir Simulation models[J].SPE.1989,SPE19582.
[21] Haldorsen H H, Lake LW. A new approach to shale management in field scale simulation models[J]. SPE,1984,SPE 10976,1-8.
[22] Dubrul G, Haldorsen H H. A review of stochastic models for petroleum Reservoirs[J]. Geostatistics, 1986, 12: 233-247.
[23] Haldorse H H. Simulator parameter assignment and the problem of scale in reservoir engineering. Reservoir Characterization[M]. London: Academic Press, 1986:19-36.
[24] Weber, Meats. How heterogeneity affects oil recovery [J]. Reservoir characterization, 1986,23: 487-544.
[25] Lasseter T J,Waggoner J R, Lake L W. Reservoir heterogeneities and their influence on ultimate recovery[J], Reservoir characterization, 1986:545-559.
[26] Haldorsen H H. Stochastic Modeling of Underground Reservoir Faceies[J].SPE.1987, SPE 16751.
[27] Begg S H, King P. Modeling the effects of shales on reservoir performance Calculation of effective vertical permeability[J]. SPE.1985, SPE 13529:22-25.
[28] Haldorsen H H, Damsleth E. Stochastic Modeling[C]. JPT.1990:404-412.
[29] Geehan G W. Geological prediction of shale continuity in Prudhoe Bay Field[J], Reservoir characterization.1986: 435-444.
[30] Matheron G, Beucher H, Fouguet C. Conditional Simulation of the geometry of flurideltaic resole[C]. 1987,Dallas, Texas: SPE Annual Conference:591-599.
[31]Journel A G,Posa D. Characteristic behavior and order relations for indicator variograms [J].Math Geology, 1990, 22(81): 685-718.
[32] Journel A G,Isaaks E. Conditional indicator simulation :application to a Saskatchewan uranium deposit[J], Math Geology , 1984,16(7):655-718.
[33]Journel A G, Alabert F G. Focusing on spatial connectivity of extreme- valued attributes: stochastic indicator modes of reservoir heterogeneity [C]. SPE. 1988, SPE1823.
[34] Hewett T A. Fractal distributions of reservoir heterogeneity and their influence on fluid transport[C], SPE.1986,SPE 15386.
[35] Emanuel A S, Alameda G K, Behrens R A. Reservoir Performance prediction method based on fractal geostatistics[J], SPE Journal.1989,SPE:311-318.
[36]Hewett T A, Behrens R A.Conditional simulation of reservoir heterogeneity with fractals[J].SPE.1988,SPE18326.
[37]Heam C L,Ebank W J, Ranganath V. Geological factors influencing reservoir performance of the Hartzog Draw Field[J] .Wyoming.JPT,1984:1335-1344.
[38]Ebank W J. Flow unit concept-integrated approach to reservoir description for engineering projects[C]. 1987,AAPG. Ann.Mtg.,Los Angeles.
[39] Haldorsen H H, Damsleth E. Stochastic Modelling [C].JPT, 1990:404-412.
[40]Galloway W E. Geneitc stratigraphic sequences in basin analysis I: Architecture and flooding-surface bounded depositional units[J]. AAPG Bulletin. 1989:25-142.
[41] Cross T. Quantitative dynamic stratigraphy[M]. New Jersey,Prentice Hall, 1990: 622.
[42] Cross T. Field-scale reservoir characterization[M] .Academe Press, 1991:493-497.
[43] Cross T, Raynolds R G. Illustration of correlation techniques, facies prediction and reservoir compartment identification through genetic stratigraphy, Gallup sandstone and Mesa Verde Group(Cretaceous) [C], Foursomes region, USA, Rocky Mountain Association of Geologists. 1993.
[44]Cross T, Lessenger M A. Sediment volume partitioning: rationle forstratigraphic model evaluation and high-resolution stratigraphic correlation [J],NPF Special Publication 8, 1998:171-195.
[45]Cross T. Stratigraphic controls on reservoir attributes in continental strata[J],Earth science frontiers. 2000,7(4):322-350.
[46]邓宏文.美国层序地层研究中的新学派-高分辨率层序地层学.石油与天然气地质[J],1995,16(2):89-97.
[47]邓宏文,王红亮,李熙哲,层序地层基准面的识别、对比技术及应用[J].石油与天然气地质,1996,16(2):89-97.
[48]邓宏文,王红亮,宁宁,沉积物体积分配原理-高分辨率层序地层学的理论基础[J].地学前缘,1995,7(4):305-313.
[49]Deutsch C. GSLIB:Geostatistical software library and users guide[C], New York :Oxford University Press. 1992:1-59.
[50]Damsleth E, Tjisen C B, More H,etc.A two-stage stochastic model Application to a North Sea reservoir[J].JPT :402-408.
[51]Verl G. Sequential Gaussisn cosimulation: A simulation method integrating several types of information[J], Geostatistics-Troia, Kluwer, Dordrecht, Holland, 1991,(1): 543-554.
[52]Suro-Perez V. Stochastic simulation of lithofacies: an improved sequential indicator approach[C]. European conference on the Maths of oil recovery, Paris. 1990:34-90.
[53]Suro-Perez. Indicator principle kriging[J]. Math Geology,1991,23(5):759-788.
[54]Suro-Perez V. Indicator Kriging and simulation based on principal component Analysis [D] , Stanford:Stanford University,1992.
[55]Deutsch C, Journel A. GSLIB:Geostatistical software library and users guide[C], Second Edition: Oxford University Press.1996:128-150.
[56]White C D, Barton M D. Translating outcrop data to flow models, with application to the Ferron sandstone[J]. Society of Petroleum Engineers Reservoir Evaluation and Engineering , 1999,2(4):341-35.
[57]Stephen K D, Dalrymple M. Reservoir simulations developed from and Outcrop of incised valley fill strata[J], AAPG Bulletin , 2002,86(5):797-82.
[58]文健,裘怿楠.油藏早期评价阶段储层建模技术的发展方向[J].石油勘探与开发,1994,21(5):88-93.
[59]裘择楠,贾爱林.储层地质模型10年[J].石油学报,2000,21(4): 101-104.
[60]查明,张一伟.盆地数值模拟方法研究与发展[J].石油大学学报(自然科学版),1992,16(2):106-114.
[61]陈亮,张一伟,熊琦华.开发后期井间剩余油分布预测[J].国外测井技术,1997,12(2):58-66.
[62]吴胜和,熊琦华等.储层建模中随机模型的地质适用性分析[C].北京:石油上业出版社,1998.47-53
[63]寿建峰,王少依,蒙绍兴等.柴达木盆地西部地区第三系湖相藻灰岩油气藏及勘探潜力[J].沉积储层,2004,9(5):59-66.
[64]张振城,孙建孟,马建海等.利用测井资料自动识别藻灰岩[J].吉林大学学报(自然科学版),2005,35(3):382-387.
[65]陈志勇,霍玉雁,贾英兰等.FMI成像测井在柴达木盆地的应用[J].石油天然气学报(江汉石油学院学报),2005,27(5):602-605.
[66]孙加华,肖洪伟,幺忠文等.声电成像测井在储层裂缝识别中的应用[J].大庆石油地质与开发,2006,25(3):100-102.
[67]程华国,袁祖贵.用地层元素测井(ECS)资料评价复杂地层岩性变化[J].核电子学与探测技术,2005,25(3):233-238.
[68]袁祖贵.地层元素测井(ECS)评价油水层[J].核电子学与探测技术,2004,24(2):126-130.
[69]庞巨丰.地层元素中子俘获伽马能谱测井解释理论和方法[J].测井技术,1998,22(2):116-119.
[70]武玉宏,王慧,高红艳.对三孔隙度交会图法进行测井曲线标准化的改进[J].油气地质与采收率,2005,12(2):38-41.
[61]葛华,郑伟.测井曲线标准化:方法和准则[J].测井技术信息,2005,18(2):44-54.
[72]雍世和,张超谟.测井资料综合处理解释[M].北京:石油工业出版社,1996:20-69.
[73]蒋武明,罗晓兰,刘新美.红柳泉油田四性关系研究[J].青海石油, 2004,22(4):36-40.
[74]孙建孟,王永刚.地球物理资料综合应用[M].东营:石油大学出版社,2001:120-150
[75]黄隆基.自然伽马能谱测井原理及应用[M].北京:石油工业出版社,1995:10-55.
[76]陆大卫等.石油测井新技术适用性典型[M].北京:石油工业出版社,2001:33-67.
[77]肖立志,陆大卫等.核磁共振测井资料解释与应用导论[M].第一版.北京:石油工业出版社,2001.10:5-33.
[78]李凤琴等.复杂岩性裂缝性储层测井评价[J].河南石油,2004,18(3):22-24.
[79]刘兴刚,张旭.测井裂缝参数估算方法研究[J].天然气工业.2003,23(4):31-34.
[80]袁祖贵,楚泽涵,方小东.低电阻率油气层评价技术研究[J].特种油气藏,2003,10(6):1-4.
[81]刘顺生,许长福,刘念周等.储层随机地质建模技术在油田开发中的应用[J].新疆石油学院学报,2001,13(3):30-34.
[82]周红,国梁,杨湖川.大王北油田大48井区储层建模研究[J].新疆石油天然气,2006,2(2):40-44.
[83]裘怿楠等.油藏描述[M].北京:石油工业出版社,1996:33-50.
[84]刘泽荣等.油藏描述原理与方法技术[M].北京:石油工业出版社,1993:62-78.
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