红岗油田高台子油藏动态油藏描述
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摘要
红岗油田高台子油藏已进入开发中后期,由于油藏不同的油组、小层其成藏及控油机理、储层类型及其物性差异、油气水分布复杂多变,导致开发效果差,具体表现为采油速度低,含水上升快,水驱采收率低等特点。为了进一步改善开发效果和提高水驱采收率,需要开展精细油藏描述,其中重要的研究工作就是建立动态储层地质模型和剩余油的分布及规律。
本论文综合应用地质、地震、测井和生产动态资料,以石油地质学、构造地质学、测井地质学、开发地质学等多学科的理论为指导,采用多学科多专业的综合一体化的研究方法。首先进行小层精细划分对比,井震结合,建立高分辨率等时小层格架。然后在详细岩心观察的基础上,进行沉积微相、成岩相和储层特征研究,确立研究区沉积微相的类型和展布特征,成岩相的类型和分布特征。利用petrel建模软件,在沉积相、成岩相的约束控制下,结合生产动态数据,采用随机建模的方法,建立不同开发时期的多级相控属性模型；通过对砂体模型和动态属性模型的精细对比和分析,结合储层流动单元和大孔道研究,建立主要开发阶段相控动态流动单元模型、储层大孔道模型,分析流动单元、大孔道的类型和分布以及发育演化特征,进而预测其演变规律：在上述研究基础上,根据不同时期的油藏开发生产动态资料,建立油藏动态流体模型,查明流体演变规律,落实各层水淹规律和剩余油分布特征及分布状况,寻找剩余油富集区,制定合理的挖潜措施。取得主要创新的成果和认识如下：
(1)采用旋回一厚度对比及高分辨率层序地层划分与对比原理,运用不同成因砂体对比模式及空间接触关系处理方式,结合研究区丰富的地质、测井和生产数据,在标志层和参照层的精确对比的基础上,对全区224口井目的层段进行了划分与对比,将高台子油藏一共划分为3个油层组、10个砂岩组、40个小层、65个单层,编制了全区224口井的小层单元分层数据表,建立了精确的等时小层格架。
(2)在7口取心井岩心观察分析的基础上,根据其岩心沉积学特征、岩石类型、沉积构造、生物特征及岩石相类型综合分析,认为研究区目的层段平面上主要发育三角洲前缘亚相和前三角洲亚相,三角洲前缘亚相可进一步识别出水下分流河道、河口坝、远砂坝、前缘席状砂、分流间湾等5个微相；前三角洲亚相主要发育前三角洲泥。纵向上自下而上总体呈进积演化,建立了沉积微相的空间分布模型。
(3)对目的层储层分析化验资料研究认为,储层以岩屑砂岩为主,同时发育少量的长石质岩屑砂岩、岩屑质石英砂岩及岩屑长石质石英砂岩。成分成熟度偏低,结构成熟度中等偏低,分选好,磨圆度呈次棱角状;胶结类型以孔隙式胶结为主。填隙物主要为粘土矿物,分别为高岭石、伊利石、伊—蒙混层及绿泥石。研究区目的层储层主要孔隙类型有粒间孔、粒内孔、铸模孔和裂隙等,其中以粒间孔和粒内孔为主。喉道类型可划分为孔隙缩小型喉道、断面收缩型喉道、片状或弯片状喉道和管束状喉道四类,孔隙结构主要为中孔细喉-细孔细喉。储层总体为中孔、特低渗储层。
(4)对分析化验资料综合分析表明,目的层储层成岩演化阶段处于晚成岩的A期。储层成岩相可分为溶蚀性成岩相和致密化成岩相两大类,溶蚀性成岩相主要包括粒间溶孔成岩相(Ⅰ)、斑状溶蚀成岩相(Ⅱ),为建设性成岩相；致密化成岩相主要包括碳酸盐致密胶结成岩相(Ⅲ)、致密压实成岩相(Ⅳ),为破坏性成岩相。结合测井曲线,研究了成岩相测井响应特征,建立了测井成岩相模型,首次建立了目的层储层成岩相模型。各微相中水下分流河道砂体主要发育溶蚀成岩相及致密胶结成岩相,河口砂坝砂体主要发育斑状胶结成岩相,席状砂、远砂坝砂体中各类成岩相均有发育,破坏性成岩相比例相对较高,致密压实成岩相主要发育在泥质较多的相带中。
(5)在储层参数分析统计的基础上,建立了储层参数数据库。利用沉积储层研究成果及测井处理成果,应用petrel软件及多级相控建模方法,首次建立了不同开发时期的高台子油藏储层地质三维模型,从动态上对油藏各种特征进行定量表征,预测了储层物性及流体的动态变化,单期水下分流河道砂体为储层物性高值区,为油气有利富集区：多期水下分流河道叠置砂体亦为物性高值区,但其非均质性较强；河口砂坝砂体因其规模较小,砂厚较薄,其物性较水下分流河道差,建设性成岩相发育的砂体可形成油气富集区；席状砂、远砂坝因砂体厚度薄,受成岩作用影响局部可形成较好储层。
(6)根据红岗油田高台子油藏的特征,选取了孔隙度、渗透率、泥质含量、流动分层指数和R35等参数进行聚类分析,将研究区储层分为四类流动单元,对开发初期阶段流动单元三维模型和井网加密阶段流动单元模型对比分析,初期阶段,研究区主要发育Ⅳ类流动单元,Ⅰ类、Ⅱ类流动单元呈斑块状发育,分布范围小,成片性差,Ⅲ类流动单元呈分散状发育；井网加密阶段,Ⅰ类、Ⅲ类流动单元分布范围增加,成片性增强。注水开发造成储层流动单元的类型和分布均发生变化,部分早期较差流动单元变为较好的流动单元,早期较好的流动单元范围进一步扩大,与实际生产吻合,较好的反映了地下流体流动状况。
(7)建立了不同开发阶段主力层段储层大孔道三维综合指数模型,定量预测了大孔道发育程度和分布规律。模型显示,随着注水时间的增加,优势流动单元储层大孔道综合指数增大,较为客观的反映了注水过程中储层大孔道变化情况。为油田水驱油效率研究和注水方案调整提供了地质依据。
(8)根据各种三维模型,结合开发动态,建立了各单层逐年含水率分布模型,预测了各层含水分布特征和水淹规律。水驱规律主要为：1)东西向裂缝是大孔道主要类型之一,是水淹的主要方向；2)构造扭转部位油井各向均有明显见效反应；3)注采关系较好部位与两相相控模型中高渗带及流动单元模型中优质流动单元展布基本一致,与储层大孔道模型中大孔道展布方向相符。沉积微相与注采关系具有一定相关性。
(9)根据各种静态模型及各井组储层注采的强弱动态资料,制定了有效的注水政策。当井组内生产油井数小于或等于2口时,注采关系特强、强的层注采比控制在0.7-0.9,注采关系中等的层注采比控制在1.1左右,注采关系弱的层注采比控制在1.3-1.5；当井组内在生产油井数大于2口时,储层注采以强、特强级别为主,结合井组油井产出及注采方向性实施混调或单层调剖；储层注采以中、弱级别为主,结合油井产出及方向性采取宏观注水调控和小强度短周期、中强度中周期和大强度、长周期周期注水方式相结合。在生产中起得了较好的效果。
(10)应用沉积相、成岩相两相相控技术,分别建立不同开发阶段的储层模型,从动态上描述了油气藏不同时期油气水分布特征及其变化规律,能较好地预测剩余油分布范围,是油藏描述技术中一个新的研究发展方向,对同类油气藏的开发具有重要的借鉴意义。
Being at middle-later stage of development, Gaotaizi reservoir of HongGang oil field faces the difficulty of low oil production speed, water rising too quickly and low water drive recovery. This is because of the differences of petroleum accumulation and control mechanism in different oil groups and small layers, the differences of reservoir types and physical properties, the complexity of oil and gas distribution.
In order to improve the development effect and enhance water drive recovery, it is necessary to carry out fine reservoir description, research on a dynamic model and remaining oil distribution modes is the most important.
Geological modeling, seismic, well-log and production data were combined with Petroleum Geology, Tectonics, Logging Geology and Development Geology by using a research method of multi-discipline and multi-specialty. The research was divided into the following steps; the first step was to establish isochronal formation framework on the base of the fine isochronal stratigraphic division and correlation. The second step was to examine sedimentary microfacies, diagenetic facies and reservoir characteristics based on core observation. All of these were used to determine the type and distribution feature of sedimentary microfacies. Reservoir stochastic modeling was used to set up property models of different development stages under the control of diagenetic facies and sedimentary facies, combined with dynamic data. Based on the fine study on sandstone model and dynamic property model, combined with the reservoir flow unit and large pore research, the flow unit model of main exploitation stages and large pore model were made. This helped to analyse the type and distribution and development and evolution characteristics of flow unit and large pore. Evolution law was finally predicted. Finally, on the basis of previous research, according to dynamic data in different development and production period, dynamic fluid model was made, the evolution law of fluid found out, water-flood law and remaining oil distribution characteristics of each layer were known. It is useful to look for remaining oil enriched area and adopt potential tapping measures. Major results obtained in this study were as follows:
(1) Based on combination of the tradition cycle-thickness correlation method and the high-resolution sequence stratigraphy, taking sandstone correlation model and the contacting of the strata into account, combining of geology, well-log and production data of the study area, and based on the precise correlation of marker beds and reference layer,224wells in the study area were finely divided and correlated. Three sand sets of Gaotaizi reservoir was divided into10oil layers and40small layers and65monolayers, the strata framework between wells were established and accomplished.
(2) Based on analysis of7coring wells, according to its sedimentology characteristics, rock types, sedimentary structure, biometrics and rock facies, it was concluded that delta front subfacies and prodelta subfacies were deposited in the target intervals. On the basis of this, sedimentary microfacies of underwater distributory channel, mouth bar, deltal-fan front sheet sand, inter-distributory bay and prodelta mud were discerned in this area. Finally, the plane distribution maps of sedimentary microfacies of each monolayer as well as its spatial distribution model were given.
(3) Through research on assay data of Qing2and Qing3member, it was showed that:the reservoir rock types were mainly lithic sandstone; few feldspathic lithic sandstone, lithoclastic quartz sandstone and lithic feldspathic sandstone. The compositional maturity was on low side and structural maturity was middle or slightly low; well-sorted; the psephicity was commonly assumed hypo-edge angle, cementation type was mainly pore cementation. Interstitial material was clay mineral which included kaolinite, illite, illite/smectite interstratified and chlorite. The reservoir pore type of target strata in study area was combined first by intergranular pore and intragranular corrosion pore, and next by mould pore and fracture with the reduced-neck, slim, sheet throat and cluster pore throat occurring as the main throat type. The pore structure was mainly medium pore and fine throat to fine pore and fine throat, which belonged to medium pore and lower permeability reservoir.
(4) Based on analysis assay data, the diagenesis phase was divided into early A phase. Dissolved diagenetic facies and densification diagenetic facies were mainly diagenetic facies type of this area. The dissolved diagenetic facies which included intergranular dissolved pore facies were (Ⅰ) porphyritic dissolved diagenetic facies (Ⅱ) constructive diagenetic facies; The densification diagenetic facies which included carbonate dense cementation diagenetic facies (Ⅲ) dense compaction diagenetic facies (Ⅳ) destructive diagenetic facies. The logging response characteristics of diagenetic facies were studied and combined with well-log, and then the diagenetic facies models of the target stratum reservoir were given for the first time. Among the microfacies, underwater distributory channel mainly developed dissolved diagenetic facies and dense cementation diagenetic facies, mouth bar mainly developed porphyritic cementation diagenetic facies, and a variety of diagenetic facies could be found in sheet sand and distal bar. Generally speaking, destructive diagenetic facies had a relatively high proportion; dense compaction diagenetic facies were mainly developed in facies which were rich in mud.
(5) Through analysis, the reservoir parameters database was acquired. Based on the research results of sedimentary reservoir and log data processing, application of petrel software and multifacies-controlled modeling method, the three-dimensional model of Gaotaizi reservoir in different development periods were given for the first time. This enabled quantitative characterization of various reservoir characteristics from the dynamic perspective. Reservoir physical property and dynamic changes of fluid were predicted, and the results shown as follows:single-period underwater distributory channel sand bodies had a high value areas of reservoir physical property, which was a favorable enrichment region of oil and gas; over-riding sand bodies of multi-period underwater distributory channel also had a high value areas of reservoir physical property. However, its heterogeneities were strong; reservoir physical property of mouth bar sand bodies was worse than that of the underwater distributory channel because of small scale and thinness of the sand bodies. The sand bodies which developed in constructive diagenetic facies could form enrichment region of oil and gas; the sand bodies of sheet sand and distal bar were thin, which could form better reservoir influenced by diagenesis.
(6) According to the characteristics of Gaotaizi reservoir of Honggang oil field, selecting porosity, permeability, shale content, flowing interval index and R35as the analysis parameters, the reservoir flow units of this area was divided into4types. At the initial stage, Ⅳ class of flow units were widely distributed, Ⅰ and Ⅱ class of flow units were charact of ferized by a small range of extention, not discontinuous and well developed. However, Ⅲ class of flow units were less developed. At well pattern infilling stage, Ⅳ class of flow units were even more widely distributed, Ⅰ and Ⅲ class of flow units were charact of increased area and continuous distribution. Water flooding could have an effect on the type and distribution of flow unit, the poor quality flow unit of initial stage could change into high quality flow unit, while the high quality flow unit of initial stage distributed more widely. In accordance with the practical production, it reflected the flow status of underground fluid.
(7) Using the method and principle of stochastic modeling, the three-dimensional model of comprehensive index of large pore in major segment of different development periods was given. The development degree and distribution law of large pore were quantitatively predicted. It showed that comprehensive index of large pore in dominant flow units enlarged with the water injection time increased. It objectively reflected the change of reservoir large pore in water injection process. This then provided geological basis for the research on water drive efficiency and water injection program.
(8) According to all kinds of three-dimensional models and dynamic development data, the moisture content distribution model of each monolayer year by year was made. The water distribution characteristics and water flooding laws of each layer were also predicted. The water flooding laws of this area were as follows:1) East-west fracture was the main type of large pore, which was also the major water flooding direction;2) The obvious effective response of oil well in every direction was observed in tectonic reverse parts;3) The injection-production relation was in accordance with the characteristics model of high permeable zone and the flow units model, but the correlation in sedimentary facies and injection-production relation was low.
(9) Depending on strong or weak of injection-production relationship in study area, effective water injection policy was worked out. When the oil wells in well group is less than or equal to2, the injection-production relation was strong, injection to production ratio is0.7-0.9in the strong layer, in the medium layer is1.1, and in the weak layer is1.3-1.5. When the oil wells in well group is more than2, the injection-production relation was mainly strong and extra strong, mix-profile control or monolayer profile control was worked out in combination with output and injection-production directivity. The injection-production relation was mainly medium and weak, macroscopic water injection control was worked out in combination with output. Injection-production directivity and water injection modes such as low intensity short period, moderate intensity moderate period and high intensity high period. This indicated a very good result during production.
(10) According to reservoir models of different development periods which was controlled by sedimentary facies and diagenetic facies, this paper described the characteristics and variation of reservoir from the dynamic perspective. It offered a better prediction for remaining oil distribution range, which is a newly-emerging research direction in reservoir description technology which has an important reference meaning to the development of similar reservoirs.
本论文综合应用地质、地震、测井和生产动态资料,以石油地质学、构造地质学、测井地质学、开发地质学等多学科的理论为指导,采用多学科多专业的综合一体化的研究方法。首先进行小层精细划分对比,井震结合,建立高分辨率等时小层格架。然后在详细岩心观察的基础上,进行沉积微相、成岩相和储层特征研究,确立研究区沉积微相的类型和展布特征,成岩相的类型和分布特征。利用petrel建模软件,在沉积相、成岩相的约束控制下,结合生产动态数据,采用随机建模的方法,建立不同开发时期的多级相控属性模型；通过对砂体模型和动态属性模型的精细对比和分析,结合储层流动单元和大孔道研究,建立主要开发阶段相控动态流动单元模型、储层大孔道模型,分析流动单元、大孔道的类型和分布以及发育演化特征,进而预测其演变规律：在上述研究基础上,根据不同时期的油藏开发生产动态资料,建立油藏动态流体模型,查明流体演变规律,落实各层水淹规律和剩余油分布特征及分布状况,寻找剩余油富集区,制定合理的挖潜措施。取得主要创新的成果和认识如下：
(1)采用旋回一厚度对比及高分辨率层序地层划分与对比原理,运用不同成因砂体对比模式及空间接触关系处理方式,结合研究区丰富的地质、测井和生产数据,在标志层和参照层的精确对比的基础上,对全区224口井目的层段进行了划分与对比,将高台子油藏一共划分为3个油层组、10个砂岩组、40个小层、65个单层,编制了全区224口井的小层单元分层数据表,建立了精确的等时小层格架。
(2)在7口取心井岩心观察分析的基础上,根据其岩心沉积学特征、岩石类型、沉积构造、生物特征及岩石相类型综合分析,认为研究区目的层段平面上主要发育三角洲前缘亚相和前三角洲亚相,三角洲前缘亚相可进一步识别出水下分流河道、河口坝、远砂坝、前缘席状砂、分流间湾等5个微相；前三角洲亚相主要发育前三角洲泥。纵向上自下而上总体呈进积演化,建立了沉积微相的空间分布模型。
(3)对目的层储层分析化验资料研究认为,储层以岩屑砂岩为主,同时发育少量的长石质岩屑砂岩、岩屑质石英砂岩及岩屑长石质石英砂岩。成分成熟度偏低,结构成熟度中等偏低,分选好,磨圆度呈次棱角状;胶结类型以孔隙式胶结为主。填隙物主要为粘土矿物,分别为高岭石、伊利石、伊—蒙混层及绿泥石。研究区目的层储层主要孔隙类型有粒间孔、粒内孔、铸模孔和裂隙等,其中以粒间孔和粒内孔为主。喉道类型可划分为孔隙缩小型喉道、断面收缩型喉道、片状或弯片状喉道和管束状喉道四类,孔隙结构主要为中孔细喉-细孔细喉。储层总体为中孔、特低渗储层。
(4)对分析化验资料综合分析表明,目的层储层成岩演化阶段处于晚成岩的A期。储层成岩相可分为溶蚀性成岩相和致密化成岩相两大类,溶蚀性成岩相主要包括粒间溶孔成岩相(Ⅰ)、斑状溶蚀成岩相(Ⅱ),为建设性成岩相；致密化成岩相主要包括碳酸盐致密胶结成岩相(Ⅲ)、致密压实成岩相(Ⅳ),为破坏性成岩相。结合测井曲线,研究了成岩相测井响应特征,建立了测井成岩相模型,首次建立了目的层储层成岩相模型。各微相中水下分流河道砂体主要发育溶蚀成岩相及致密胶结成岩相,河口砂坝砂体主要发育斑状胶结成岩相,席状砂、远砂坝砂体中各类成岩相均有发育,破坏性成岩相比例相对较高,致密压实成岩相主要发育在泥质较多的相带中。
(5)在储层参数分析统计的基础上,建立了储层参数数据库。利用沉积储层研究成果及测井处理成果,应用petrel软件及多级相控建模方法,首次建立了不同开发时期的高台子油藏储层地质三维模型,从动态上对油藏各种特征进行定量表征,预测了储层物性及流体的动态变化,单期水下分流河道砂体为储层物性高值区,为油气有利富集区：多期水下分流河道叠置砂体亦为物性高值区,但其非均质性较强；河口砂坝砂体因其规模较小,砂厚较薄,其物性较水下分流河道差,建设性成岩相发育的砂体可形成油气富集区；席状砂、远砂坝因砂体厚度薄,受成岩作用影响局部可形成较好储层。
(6)根据红岗油田高台子油藏的特征,选取了孔隙度、渗透率、泥质含量、流动分层指数和R35等参数进行聚类分析,将研究区储层分为四类流动单元,对开发初期阶段流动单元三维模型和井网加密阶段流动单元模型对比分析,初期阶段,研究区主要发育Ⅳ类流动单元,Ⅰ类、Ⅱ类流动单元呈斑块状发育,分布范围小,成片性差,Ⅲ类流动单元呈分散状发育；井网加密阶段,Ⅰ类、Ⅲ类流动单元分布范围增加,成片性增强。注水开发造成储层流动单元的类型和分布均发生变化,部分早期较差流动单元变为较好的流动单元,早期较好的流动单元范围进一步扩大,与实际生产吻合,较好的反映了地下流体流动状况。
(7)建立了不同开发阶段主力层段储层大孔道三维综合指数模型,定量预测了大孔道发育程度和分布规律。模型显示,随着注水时间的增加,优势流动单元储层大孔道综合指数增大,较为客观的反映了注水过程中储层大孔道变化情况。为油田水驱油效率研究和注水方案调整提供了地质依据。
(8)根据各种三维模型,结合开发动态,建立了各单层逐年含水率分布模型,预测了各层含水分布特征和水淹规律。水驱规律主要为：1)东西向裂缝是大孔道主要类型之一,是水淹的主要方向；2)构造扭转部位油井各向均有明显见效反应；3)注采关系较好部位与两相相控模型中高渗带及流动单元模型中优质流动单元展布基本一致,与储层大孔道模型中大孔道展布方向相符。沉积微相与注采关系具有一定相关性。
(9)根据各种静态模型及各井组储层注采的强弱动态资料,制定了有效的注水政策。当井组内生产油井数小于或等于2口时,注采关系特强、强的层注采比控制在0.7-0.9,注采关系中等的层注采比控制在1.1左右,注采关系弱的层注采比控制在1.3-1.5；当井组内在生产油井数大于2口时,储层注采以强、特强级别为主,结合井组油井产出及注采方向性实施混调或单层调剖；储层注采以中、弱级别为主,结合油井产出及方向性采取宏观注水调控和小强度短周期、中强度中周期和大强度、长周期周期注水方式相结合。在生产中起得了较好的效果。
(10)应用沉积相、成岩相两相相控技术,分别建立不同开发阶段的储层模型,从动态上描述了油气藏不同时期油气水分布特征及其变化规律,能较好地预测剩余油分布范围,是油藏描述技术中一个新的研究发展方向,对同类油气藏的开发具有重要的借鉴意义。
Being at middle-later stage of development, Gaotaizi reservoir of HongGang oil field faces the difficulty of low oil production speed, water rising too quickly and low water drive recovery. This is because of the differences of petroleum accumulation and control mechanism in different oil groups and small layers, the differences of reservoir types and physical properties, the complexity of oil and gas distribution.
In order to improve the development effect and enhance water drive recovery, it is necessary to carry out fine reservoir description, research on a dynamic model and remaining oil distribution modes is the most important.
Geological modeling, seismic, well-log and production data were combined with Petroleum Geology, Tectonics, Logging Geology and Development Geology by using a research method of multi-discipline and multi-specialty. The research was divided into the following steps; the first step was to establish isochronal formation framework on the base of the fine isochronal stratigraphic division and correlation. The second step was to examine sedimentary microfacies, diagenetic facies and reservoir characteristics based on core observation. All of these were used to determine the type and distribution feature of sedimentary microfacies. Reservoir stochastic modeling was used to set up property models of different development stages under the control of diagenetic facies and sedimentary facies, combined with dynamic data. Based on the fine study on sandstone model and dynamic property model, combined with the reservoir flow unit and large pore research, the flow unit model of main exploitation stages and large pore model were made. This helped to analyse the type and distribution and development and evolution characteristics of flow unit and large pore. Evolution law was finally predicted. Finally, on the basis of previous research, according to dynamic data in different development and production period, dynamic fluid model was made, the evolution law of fluid found out, water-flood law and remaining oil distribution characteristics of each layer were known. It is useful to look for remaining oil enriched area and adopt potential tapping measures. Major results obtained in this study were as follows:
(1) Based on combination of the tradition cycle-thickness correlation method and the high-resolution sequence stratigraphy, taking sandstone correlation model and the contacting of the strata into account, combining of geology, well-log and production data of the study area, and based on the precise correlation of marker beds and reference layer,224wells in the study area were finely divided and correlated. Three sand sets of Gaotaizi reservoir was divided into10oil layers and40small layers and65monolayers, the strata framework between wells were established and accomplished.
(2) Based on analysis of7coring wells, according to its sedimentology characteristics, rock types, sedimentary structure, biometrics and rock facies, it was concluded that delta front subfacies and prodelta subfacies were deposited in the target intervals. On the basis of this, sedimentary microfacies of underwater distributory channel, mouth bar, deltal-fan front sheet sand, inter-distributory bay and prodelta mud were discerned in this area. Finally, the plane distribution maps of sedimentary microfacies of each monolayer as well as its spatial distribution model were given.
(3) Through research on assay data of Qing2and Qing3member, it was showed that:the reservoir rock types were mainly lithic sandstone; few feldspathic lithic sandstone, lithoclastic quartz sandstone and lithic feldspathic sandstone. The compositional maturity was on low side and structural maturity was middle or slightly low; well-sorted; the psephicity was commonly assumed hypo-edge angle, cementation type was mainly pore cementation. Interstitial material was clay mineral which included kaolinite, illite, illite/smectite interstratified and chlorite. The reservoir pore type of target strata in study area was combined first by intergranular pore and intragranular corrosion pore, and next by mould pore and fracture with the reduced-neck, slim, sheet throat and cluster pore throat occurring as the main throat type. The pore structure was mainly medium pore and fine throat to fine pore and fine throat, which belonged to medium pore and lower permeability reservoir.
(4) Based on analysis assay data, the diagenesis phase was divided into early A phase. Dissolved diagenetic facies and densification diagenetic facies were mainly diagenetic facies type of this area. The dissolved diagenetic facies which included intergranular dissolved pore facies were (Ⅰ) porphyritic dissolved diagenetic facies (Ⅱ) constructive diagenetic facies; The densification diagenetic facies which included carbonate dense cementation diagenetic facies (Ⅲ) dense compaction diagenetic facies (Ⅳ) destructive diagenetic facies. The logging response characteristics of diagenetic facies were studied and combined with well-log, and then the diagenetic facies models of the target stratum reservoir were given for the first time. Among the microfacies, underwater distributory channel mainly developed dissolved diagenetic facies and dense cementation diagenetic facies, mouth bar mainly developed porphyritic cementation diagenetic facies, and a variety of diagenetic facies could be found in sheet sand and distal bar. Generally speaking, destructive diagenetic facies had a relatively high proportion; dense compaction diagenetic facies were mainly developed in facies which were rich in mud.
(5) Through analysis, the reservoir parameters database was acquired. Based on the research results of sedimentary reservoir and log data processing, application of petrel software and multifacies-controlled modeling method, the three-dimensional model of Gaotaizi reservoir in different development periods were given for the first time. This enabled quantitative characterization of various reservoir characteristics from the dynamic perspective. Reservoir physical property and dynamic changes of fluid were predicted, and the results shown as follows:single-period underwater distributory channel sand bodies had a high value areas of reservoir physical property, which was a favorable enrichment region of oil and gas; over-riding sand bodies of multi-period underwater distributory channel also had a high value areas of reservoir physical property. However, its heterogeneities were strong; reservoir physical property of mouth bar sand bodies was worse than that of the underwater distributory channel because of small scale and thinness of the sand bodies. The sand bodies which developed in constructive diagenetic facies could form enrichment region of oil and gas; the sand bodies of sheet sand and distal bar were thin, which could form better reservoir influenced by diagenesis.
(6) According to the characteristics of Gaotaizi reservoir of Honggang oil field, selecting porosity, permeability, shale content, flowing interval index and R35as the analysis parameters, the reservoir flow units of this area was divided into4types. At the initial stage, Ⅳ class of flow units were widely distributed, Ⅰ and Ⅱ class of flow units were charact of ferized by a small range of extention, not discontinuous and well developed. However, Ⅲ class of flow units were less developed. At well pattern infilling stage, Ⅳ class of flow units were even more widely distributed, Ⅰ and Ⅲ class of flow units were charact of increased area and continuous distribution. Water flooding could have an effect on the type and distribution of flow unit, the poor quality flow unit of initial stage could change into high quality flow unit, while the high quality flow unit of initial stage distributed more widely. In accordance with the practical production, it reflected the flow status of underground fluid.
(7) Using the method and principle of stochastic modeling, the three-dimensional model of comprehensive index of large pore in major segment of different development periods was given. The development degree and distribution law of large pore were quantitatively predicted. It showed that comprehensive index of large pore in dominant flow units enlarged with the water injection time increased. It objectively reflected the change of reservoir large pore in water injection process. This then provided geological basis for the research on water drive efficiency and water injection program.
(8) According to all kinds of three-dimensional models and dynamic development data, the moisture content distribution model of each monolayer year by year was made. The water distribution characteristics and water flooding laws of each layer were also predicted. The water flooding laws of this area were as follows:1) East-west fracture was the main type of large pore, which was also the major water flooding direction;2) The obvious effective response of oil well in every direction was observed in tectonic reverse parts;3) The injection-production relation was in accordance with the characteristics model of high permeable zone and the flow units model, but the correlation in sedimentary facies and injection-production relation was low.
(9) Depending on strong or weak of injection-production relationship in study area, effective water injection policy was worked out. When the oil wells in well group is less than or equal to2, the injection-production relation was strong, injection to production ratio is0.7-0.9in the strong layer, in the medium layer is1.1, and in the weak layer is1.3-1.5. When the oil wells in well group is more than2, the injection-production relation was mainly strong and extra strong, mix-profile control or monolayer profile control was worked out in combination with output and injection-production directivity. The injection-production relation was mainly medium and weak, macroscopic water injection control was worked out in combination with output. Injection-production directivity and water injection modes such as low intensity short period, moderate intensity moderate period and high intensity high period. This indicated a very good result during production.
(10) According to reservoir models of different development periods which was controlled by sedimentary facies and diagenetic facies, this paper described the characteristics and variation of reservoir from the dynamic perspective. It offered a better prediction for remaining oil distribution range, which is a newly-emerging research direction in reservoir description technology which has an important reference meaning to the development of similar reservoirs.
引文
[1]胡望水,熊平,谢锐杰等.红岗油田高台子油藏相控随机水淹模型的建立.石油天然气学报.2008,30(6)：15-19
[2]牛世忠,胡望水,熊平.储层非均质性模型在红岗油田高台子油藏中的应用.石油天然气学报.2009,31(4)：31-35
[3]张一伟,熊琦华,王志章等.陆相油藏描述.石油工业出版社,1997：13-18
[4]穆龙新,裘怿楠.不同开发阶段的油藏描述原理.石油工业出版社,1999：1-32
[5]王继贤.油藏描述软件系统及其应用.石油工业出版社,1993：1-40
[6]W. F. Ebanks. Flow Unit Concept-integrated Approach to Reservoir Description for Engineering Projects. AAPG.1987
[7]裘怿楠,陈子琪.油藏描述.石油工业出版社,1996：184-196
[8]师永民,霍进,张玉广等.陆相油田开发中后期油藏精细描述.石油工业出版社,2004：1-18
[9]贾爱林.精细油藏描述与地质建模技术.石油工业出版社,2010：1-22
[10]王端平.复杂断块油田精细油藏描述.石油学报.2000,21(6)：111-116
[11]徐守余.油藏描述方法原理.石油工业出版社,2005：1-41
[12]王志章,石占中.现代油藏描述技术.石油工业出版社,1999：3-275
[13]C. C. Hearn, J. P. Hobson, M. L. Fowler. Reservoir Characteriation for simulation, Reservoir characterization. Acadeuwnc Press,1986
[14]Matheron, G. The theory of regionalied variables and its applications. Occludes Mines.1971
[15]Matheron G. The intrinsic random functions and their applications. A dunces in Applied Probability.1973, (5):439-468
[16]张团峰,王家华.储层表征中的随机模拟算法.西安电子科技大学报,1995,22(5)：89-97
[17]张团峰,王家华.试论克里金估计与随机模拟的本质区别.西安石油院学报.1997,12(2)：89-97
[18]Journel A G. Geostatistics for conditional simulation of forebodes. Economic Geology.1974, (69):673-680
[19]Journel A G and C. J. Huijbregts. Mining Geostatistics. Academic Press,1978
[20]Weber, K. L. C. Van Geuns. Framework for Constructing Clastic Reservoir Simulation Models. SPE.19582,1989:109-118
[21]Van De Graaff, W. J. E and P. J. Ealey. Geological Modeling for Simulation Studies. AAPG Bulletin.1989,73(11):1436-1444
[22]Haldorsen, H. H. and L.W. Lake. A new approach to shale management in field scale simulation models. SPE.10976,1984:1-8
[23]Dubrule G. and H. H. Haldorsen. A review of stochastic models for petroleum reservoirs. Geostatistics.1986,1(2):233-247
[24]Weber K.and B. V. Meats, B.V.choppy.How heterogeneity affects oil recovery. Reservoir characterization.1986:487-544
[25]Lasseter T. J, J.R.Waggoner and L. W. Lake. Reservoir heterogeneities and their in influence on ultimate recovery, in L. W. Lake and H. B. Carroll, eds. Reservoir characterization. Academic Press,1986: 545-559
[26]Matheron G. H. Beucher,C. deFouguet, A. Gall, P. Guerillal C. Conditional Simulation of the geometry of flurideltaic resole. SPE Annual Conference,1987:591-599
[27]Haldorsen H. H. Stochastic Modelling of Underground Reserivoir Faceies. SPE.16751,1987
[28]Begg S. H and P. King. Model ing the effects of shales on reservoir performance:Calculation of effective vertical permeability. SPE 13529,1985:22-25
[29]Geehan G. W. et al. Geological prediction of shale continuity in Prudhoe Bay Field. Reservoir characterization.1986:435-444
[30]Journel A G and F. G. Alabert. New Method for Reservoir Mapping.JPT. 1990, (2):212-218
[31]Journel A G D. POsa. Characteristic behavior and order relations for indicator variograms. Math Geology.1990,22 (81):685-718
[32]Journel A G E. Isaaks. Conditional indicator simulation: application to a Saskatchewan uranium deposit. Math Geology.1984, 16(7):655-718
[33]Journel A G and F.G.Alabert. Focusing on spatial connectivity of extreme-valued attributes:stochastic indicator modes of reservoir heterogeneity. SPE.1823,1988
[34]Hewett T. A. Fractal distributions of reservoir heterogeneity and their influence on fluid transport. SPE.15386,1986
[35]Emanuel A. S, G. K. Alameda, R. A. Behrens and T. A. Hewett. Reservoir performance prediction method based on fractal geostatistics. SPE. 1989, (8):311-318
[36]Hewett T. A, R. A. Behrens. Conditional simulation of reservoir heterogeneity with fractals. SPE.18326,1988:2-53
[37]Hearn C. L, Hobson J, P and FowlerM L. Reservoir characterization for simulation, Hartzog Draw field. Academic Press,1986
[38]Ebank W. J. Flow unit concept--Integrated approach to reservoir description for engineering projects. Amer. Assoc. Petol. Geol. Ann., Mtg, Los Angeles(abs),1987
[39]Kramers W. J. Integrated reservoir characterization:from the well to the numerical model, increased primary recovery.1987:5:5-11
[40]Rodriguez M. S. A. Facies modeling and the flow unit concept as a sedimentological tool in reservoir description:A case study.SPE.18154，1989
[41]穆龙新,周丽清,郑小武等.精细油藏描述及一体化技术.石油工业出版社,2006：1-12
[42]曾祥林,杜志敏.多学科协同化方法在复杂断块油藏开发调整方案中的应用.断块油气田.2002,1(24)：34-38
[43]Deutsch Cand A. Journel. GSLIB:Geostatistical software library and users guide. New York:Oxford Univerity Press,1992
[44]Deutsch C. V, L. Wang. Quantifying object-based stochastic modeling of fluvial reservoirs. Mathematical Geology.1996:827-857
[45]Dimitrakepoulos R. Coniditional simulation of intrinsic random function of order. Math Geology.1990,22 (3)
[46]王家华,张团峰.油气储层随机建模.石油工业出版社,2001：1-52
[47]李少华,尹艳树,张昌民.储层随机建模系列技术.石油工业出版社,2001：3-14
[48]Deutsch Cand A. Journel. GSLIB:Geostatistical software library and users guide. Oxford Univerity Press,1992
[49]Deutsch C. V and L. Wang. Quantifying object-based stochastic modeling of fluvial reservoirs. Mathematical Geology,1996:827-857
[50]Verly G. Sequential Gaussisn cosimulation:A simulation method integrating several types of information, in A Soares. Geostatistics-Troia.1991,1:543-554
[51]Suro-Perez V and A. G. Stochastic simulation of lithofacies:an improved sequential indicator approach.2nd European conference on the Maths of oil recovery, Paris 1990
[52]Suro-Perez. V, AJournel. Indicator principle kriging. Math Geology. 1991,23(5):759-788
[53]Suro-Perez V. Kriging and simulation based on principal component analysis. PhD thesis, Stanford Unversity, Stanford, CA,1992
[54]Deutsch C. and A. Journel. GSLIB:Geostatistical software library and users guide. Second Edittion:Oxford Univerity Press,1996
[55]White C.D and M. D. Barton. Translating outcrop data to flow models, with application to the Ferron sandstone. SOCIETY OF Petroleum Engineers Reservoir Evalution and Engineering.1999,2 (4):341-350
[56]Stephen Dalrymple. Reservoir simulations developed from an outcrop of incised valley fill strata. AAPG Bulletin.2002,86(5):797-822
[57]Wagoner J. C. V. et al. Sequence Stratigraphy in well, core, logs and outcrops:Concept for high-resolution correlation of time and facies. AAPG Motheds in Exploration Series,1990
[58]Galloway W. E. Genetic stratigraphic sequences in basin analysis I Architecture and flooding-surface bounded depositional units. AAPG Bulletin.1989,73:125-142
[59]Cross T. A. Field-scale reservoir characterization, in L. W. Lake, H. B. Carroll, and T. C. Wesson, (ed).Reservoir characterization II:Orlando, Florida, Acadenic Press,1991:493-497
[60]Cross T. A and R.G.Raynolds. Illustration of correlation techniques, facies prediction and reservoir compartment identification through genetic stratigraphy, Gallup sandstone and Mesa Verde Group (Cretaceous), Four-corners region. Rocky Mountain Association of Geologists.1993:71-75
[61]Cross T. A. and M. A. Lessenger. Sediment volume partitioning: rationle for stratigraphic model evaluation and high-resolution stratigraphic correlation, in, F. M. Gradstein, K.0. Sandvik and N. J. Milton, (ed),Sequence stratigraphy concepts and applicatons. NPF Special Publication,1998:171-195
[62]Cross T. A., (ed). Quantitative dynamic stratigraphy. New Jersey, Prentice Hall,1990:622-624
[63]Cross T. A., M. R. Baker, M. A. Chapin, M. S. Clark, M. H. Gardner, M. S. Hanson, M. A. Lessenger, L. D. Little, K. J. McDonough, M. D. Sonnenfeld, D. W. S. Valasek, M. R. Williams and D. N. Witter. Applications of high-resolution sequence stratigraphy to reservoir analysis, in R. Eschard and B. Doligez, (ed), Subsurface reservoir characterization from outcrop observation, Proceeding of the 7th IEP exploration and production research conference:technip,1993
[64]Cross T.A. Stratigraphic controls on reservoir attributes in continental strata. Earth science frontiers,2000,7(4):322-350
[65]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.1995,16(2)：89-97
[66]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.地学前缘.1997,7(4)：305-313
[67]樊太亮,吕延仓,顶明华.层序地层体制中的陆相储层发育规律.地学前缘.2000,7(4)：315-321
[68]邓宏文,王宏亮,李熙喆.层序地层基准而的识别、对比技术及应用.石油与天然气地质.1996,17(3)：177-184
[69]郑荣才,彭军,吴朝容.陆相盆地基准而旋回的级次划分和研究意义.沉积学报.2001,19(2)：249-255
[70]Guang ming Ti, D.O. Ogbe and D. G. Hatzignation. Use of flow unit as a tool for reservoir description:A case study. SPE.26919:122-128
[71]Amaefule et al. Enhanced reservoir description:using core and 1 data to identify hydraulic(flow) units and predict permeability in uncork intervals/well. SPE.26436,1993
[72]Maghsood et al. Permeability prediction by hydraulic flow unit theory and application. SPE Formation Evaluation.1996, (12)
[73]阎长辉,羊裔常,董继芬.动态流动单元研究.成都理工学院学报.1999,26(3)：273-275
[74]Scott H, Hamlin H. Depositional controls on reservoir properties in a braid-delta sandstone, Tirrawarra oil field, south Australia. AAPG Bulletin.1996,80(2):139-156
[75]Nei F Hurley. The ascertain of dolonitite karst cave flow nuits new mexico iol field. SPWLA 39th Annual Logging Symposiun.1998:1213-1218
[76]F Jervy Lucia. Characteri zation of Petropnysical Flow Units in Carbonate Reservoirs Discussion. AAPG Bulletin.1999,6(83):1161- 1163
[77]Feazel C T, Byrnes A P, Honefenger J W, et al. Carbonate Reservoir Characterization and simulation:From Facies To Flow Units.AAPG Bulletin.2004,88(11):1467-1470
[78]Canas J A, Malk E A. Characterization Of Flow Units in sands reservoirs La Cim Field,Colcmbin, South Amereca. Proceedings of the Peunian Basin oil Gas Recovery. SPE.1994:886-892
[79]高博禹,彭仕宓,陈烨菲.动态流动单元研究.成都理工学院学报.1999,26(3)：273-275
[80]李阳.储层流动单元模式及剩余油分布规律.石油学报.2003,24(3)：52-55
[81]赵翰卿.对储层流动单元研究的认识与建议.大庆石油地质与开发2001,20(8)：8-10
[82]吴胜和,王仲林.陆相储层流动单元研究的新思路.沉积学报.1999,17(2)：252-256
[83]Eilertsen Terje, et al.Experiments and numerical simulations of fluid flow in a cross layered reservoir model. Jouranl of Petroleum Science and Engineering.1997,18:49
[84]师永民,张玉广,何勇等.利用毛细管压力曲线分形分维方法研究流动单元.地学前缘.2006,13(3)：129-132
[85]张祥忠,吴欣松,熊琦华.模糊聚类和模糊识别法的流动单元分类新方法.石油大学学报.2002,26(5)：19-22
[86]金佩强,杨克远.国外流动单元研究描述与划分.大庆石油地质与开发.1998,17(4)：49-51
[87]尹太举,张昌民,王寿平等.濮53块流动单元评价.石油学报.2005,26(5)：85-89
[88]彭仕宓,尹志军,常学军.陆相储集层流动单元定量研究新方法.石油勘探与开发.2001,28(5)：68-70
[89]魏斌,陈建文,郑浚茂.应用储层流动单元研究高含水油田剩余油分布.地学前缘.2000,7(4)：403-409
[90]陈烨菲,彭仕宓,宋桂茹等.流动单元的井间预测及剩余油分布规律研究.石油学报.2003,24(3)：74-77
[91]Hewett T. A. Fractal methods for fracture characterization, in, Yarus and chambers (eds.), Stochastic modeling and geostatistics: principle, methods, and case studies. AAPG computer application in Geology.1994, (3)
[92]Wu H.and D. D Pollard. Detecting subsurface fracture network and drainage area using 1D borehole data:proceeding of the International conference of petroleum and petroleum chemistry. 1994:14
[93]Wu H. and D. D. Pollard. Imaging 3-D fracture networks around boreholes. AAPG Bulletin.2002,86(4):593-604
[94]Elsayed et. al. Multidisciplinary Reservoir Characterization and Simulation Study of the Weyburn Unit. SPE.1993, (11)
[95]Beliveau D, Payne D. A. and Mundry M. Waterflood nd C02 Flood of the Fractured Midale Field. JPT.1993:881-887
[96]Baker R.0, et. al. Characterization of the Dynamic Fracture Transport in an Naturally Fractured Reservoir. SPE.59690,2000
[97]Richard 0. Baker and Frank Kuppe, Reservoir Characterization for Naturally Fractured Reservoirs. SPE.2000, (11):1-13
[98]罗利.低孔砂岩孔隙度计算方法及裂缝识别技术.测井技术.1999,23(1)：33-37
[99]孙建孟,刘荣,梅基席等.青海柴西地区常规测井裂缝识别方布.测井技术.2005,29(1)：268-272
[100]张吉吕,郑丽辉.利用人工智能技术进行裂缝识别研究.测井技术.2005,29(1)：52-54
[101]中辉林,高松洋.基于BP神经网络进行裂缝识别研究.新疆石油天然气.2002,2(4)：39—52
[102]李雪英,蔺景龙,文慧俭.复杂地质背景下的多裂缝识别.大庆石油学院学报.2006,30(6)：16-19
[103]高霞,谢庆宾.储层裂缝识别与评价方法新进展.地球物理学进展.2007,22(5)：1460-1465
[104]Velde B, Duboes J, et al. Fractal analysis of fracture in rocks:the cantor's Dust method. Tectonphysics.1990(3):61-68
[105]Velde B. Structure of surface cracks in soil and mud. Tectonphysics.1999(1-2):101-104
[106]裘怿楠.储层地质模型.石油学报.1991,12(4)：55-62
[107]文健,裘怿楠.油藏早期评价阶段储层建模技术的发展方向.石油勘探与开发.1994,21(5)：88-93
[108]穆龙新,贾文瑞.建立定量储层地质模型的新方法.石油勘探与开发.1994,21(4)：82-86
[109]李元觉.层状定容气藏储层建模及其条件模拟法软件的实现.国际石油与石油化工科技研讨会.1994
[110]聂昌谋,纪发华.储层参数随机建模方法在胡状集油田储层非均质研究中的应用.断块油气田.1996,3(1)：26-30
[111]钟宝荣,李龙滟等.储层随机建模与条件模拟的计算机实现.油气成藏机理及油气资源评价国际研讨会.石油工业出版社.1998：312-317
[112]张永贵,陈明强.模拟退火组合优化算法在油气储层随机建模中应用.西南石油学院学报.1997,19(3)：1-7
[113]张永贵,李允,陈明强.储层地质统计随机模拟.石油大学学报.1998,22(3)：113-116
[114]王家华,张团峰.油气储层随机建模.石油工业出版社,2001：1-60
[115]张春雷,段林娣,王志章.储集层随机建模的改进河道模型条件算法.石油勘探与开发.2004,31(4)：76-78
[116]李少华,张昌民,林克湘等.应用改进的布尔方法建立砂体骨架模型.石油勘探与开发.2000,27(3)：91-92
[117]张祥忠,熊琦华,蔡毅.应用多级序贯指示模拟方法预测储集层岩性.石油勘探与开发.2003,30(6)：81-82
[118]吕晓光,潘懋,王家华等.指示主成分模拟建立分流河道砂体相模型及意义.石油学报.2003,24(1)：53-57
[119]刘振峰,郝天珧,方辉.用Markov链模型模拟储层岩相空间展布.石油学报.2005,26(5)：57-60
[120]尹太举,张昌民,王振奇等.利用序贯指示模拟方法预测储集层岩性.新疆石油地质.2002,23(1)：59-62
[121]徐景帧,刘晓冬等.渗透率建模的三维指示条件模拟方法及其应用.石油学报.2000,21(3)：61-65
[122]刘国旗,赵爱武.河流相多层砂岩油藏剩余油描述及挖潜技术.大庆石油地质与开发.2001,20(5)：34-37
[123]陈恭洋,何鲜,刘树明等.千米桥碳酸盐岩古潜山裂缝预测.中国石油勘探.2003,8(3)：84-91
[124]杨辉延,江同文,颜其彬.缝洞型碳酸盐岩储层三维地质建模方法初探.大庆石油地质与开发.2004,23(4)：11-16
[125]窦之林.储层流动单元研究.石油工业出版社,2000
[126]冉启全,王拥军,孙圆辉等.火山岩气藏储层表征技术.科学出版社,2011
[127]毛治国,胡望水,余海洋.油藏地质研究进展.特种油气藏.2007,14(4)：6-12
[128]申本科.油藏描述技术与展望.石油勘探与开发.2003,30(4)：78-81
[129]景成杰,胡望水,程超等.相控建模技术在高台子油藏精细描述中的应用.石油天然气学报,2009,31(1)：39-42
[130]高瑞琪,蔡希源.松辽盆地油气田形成条件与分布规律.石油工业出版社,1993：402-409
[2]牛世忠,胡望水,熊平.储层非均质性模型在红岗油田高台子油藏中的应用.石油天然气学报.2009,31(4)：31-35
[3]张一伟,熊琦华,王志章等.陆相油藏描述.石油工业出版社,1997：13-18
[4]穆龙新,裘怿楠.不同开发阶段的油藏描述原理.石油工业出版社,1999：1-32
[5]王继贤.油藏描述软件系统及其应用.石油工业出版社,1993：1-40
[6]W. F. Ebanks. Flow Unit Concept-integrated Approach to Reservoir Description for Engineering Projects. AAPG.1987
[7]裘怿楠,陈子琪.油藏描述.石油工业出版社,1996：184-196
[8]师永民,霍进,张玉广等.陆相油田开发中后期油藏精细描述.石油工业出版社,2004：1-18
[9]贾爱林.精细油藏描述与地质建模技术.石油工业出版社,2010：1-22
[10]王端平.复杂断块油田精细油藏描述.石油学报.2000,21(6)：111-116
[11]徐守余.油藏描述方法原理.石油工业出版社,2005：1-41
[12]王志章,石占中.现代油藏描述技术.石油工业出版社,1999：3-275
[13]C. C. Hearn, J. P. Hobson, M. L. Fowler. Reservoir Characteriation for simulation, Reservoir characterization. Acadeuwnc Press,1986
[14]Matheron, G. The theory of regionalied variables and its applications. Occludes Mines.1971
[15]Matheron G. The intrinsic random functions and their applications. A dunces in Applied Probability.1973, (5):439-468
[16]张团峰,王家华.储层表征中的随机模拟算法.西安电子科技大学报,1995,22(5)：89-97
[17]张团峰,王家华.试论克里金估计与随机模拟的本质区别.西安石油院学报.1997,12(2)：89-97
[18]Journel A G. Geostatistics for conditional simulation of forebodes. Economic Geology.1974, (69):673-680
[19]Journel A G and C. J. Huijbregts. Mining Geostatistics. Academic Press,1978
[20]Weber, K. L. C. Van Geuns. Framework for Constructing Clastic Reservoir Simulation Models. SPE.19582,1989:109-118
[21]Van De Graaff, W. J. E and P. J. Ealey. Geological Modeling for Simulation Studies. AAPG Bulletin.1989,73(11):1436-1444
[22]Haldorsen, H. H. and L.W. Lake. A new approach to shale management in field scale simulation models. SPE.10976,1984:1-8
[23]Dubrule G. and H. H. Haldorsen. A review of stochastic models for petroleum reservoirs. Geostatistics.1986,1(2):233-247
[24]Weber K.and B. V. Meats, B.V.choppy.How heterogeneity affects oil recovery. Reservoir characterization.1986:487-544
[25]Lasseter T. J, J.R.Waggoner and L. W. Lake. Reservoir heterogeneities and their in influence on ultimate recovery, in L. W. Lake and H. B. Carroll, eds. Reservoir characterization. Academic Press,1986: 545-559
[26]Matheron G. H. Beucher,C. deFouguet, A. Gall, P. Guerillal C. Conditional Simulation of the geometry of flurideltaic resole. SPE Annual Conference,1987:591-599
[27]Haldorsen H. H. Stochastic Modelling of Underground Reserivoir Faceies. SPE.16751,1987
[28]Begg S. H and P. King. Model ing the effects of shales on reservoir performance:Calculation of effective vertical permeability. SPE 13529,1985:22-25
[29]Geehan G. W. et al. Geological prediction of shale continuity in Prudhoe Bay Field. Reservoir characterization.1986:435-444
[30]Journel A G and F. G. Alabert. New Method for Reservoir Mapping.JPT. 1990, (2):212-218
[31]Journel A G D. POsa. Characteristic behavior and order relations for indicator variograms. Math Geology.1990,22 (81):685-718
[32]Journel A G E. Isaaks. Conditional indicator simulation: application to a Saskatchewan uranium deposit. Math Geology.1984, 16(7):655-718
[33]Journel A G and F.G.Alabert. Focusing on spatial connectivity of extreme-valued attributes:stochastic indicator modes of reservoir heterogeneity. SPE.1823,1988
[34]Hewett T. A. Fractal distributions of reservoir heterogeneity and their influence on fluid transport. SPE.15386,1986
[35]Emanuel A. S, G. K. Alameda, R. A. Behrens and T. A. Hewett. Reservoir performance prediction method based on fractal geostatistics. SPE. 1989, (8):311-318
[36]Hewett T. A, R. A. Behrens. Conditional simulation of reservoir heterogeneity with fractals. SPE.18326,1988:2-53
[37]Hearn C. L, Hobson J, P and FowlerM L. Reservoir characterization for simulation, Hartzog Draw field. Academic Press,1986
[38]Ebank W. J. Flow unit concept--Integrated approach to reservoir description for engineering projects. Amer. Assoc. Petol. Geol. Ann., Mtg, Los Angeles(abs),1987
[39]Kramers W. J. Integrated reservoir characterization:from the well to the numerical model, increased primary recovery.1987:5:5-11
[40]Rodriguez M. S. A. Facies modeling and the flow unit concept as a sedimentological tool in reservoir description:A case study.SPE.18154，1989
[41]穆龙新,周丽清,郑小武等.精细油藏描述及一体化技术.石油工业出版社,2006：1-12
[42]曾祥林,杜志敏.多学科协同化方法在复杂断块油藏开发调整方案中的应用.断块油气田.2002,1(24)：34-38
[43]Deutsch Cand A. Journel. GSLIB:Geostatistical software library and users guide. New York:Oxford Univerity Press,1992
[44]Deutsch C. V, L. Wang. Quantifying object-based stochastic modeling of fluvial reservoirs. Mathematical Geology.1996:827-857
[45]Dimitrakepoulos R. Coniditional simulation of intrinsic random function of order. Math Geology.1990,22 (3)
[46]王家华,张团峰.油气储层随机建模.石油工业出版社,2001：1-52
[47]李少华,尹艳树,张昌民.储层随机建模系列技术.石油工业出版社,2001：3-14
[48]Deutsch Cand A. Journel. GSLIB:Geostatistical software library and users guide. Oxford Univerity Press,1992
[49]Deutsch C. V and L. Wang. Quantifying object-based stochastic modeling of fluvial reservoirs. Mathematical Geology,1996:827-857
[50]Verly G. Sequential Gaussisn cosimulation:A simulation method integrating several types of information, in A Soares. Geostatistics-Troia.1991,1:543-554
[51]Suro-Perez V and A. G. Stochastic simulation of lithofacies:an improved sequential indicator approach.2nd European conference on the Maths of oil recovery, Paris 1990
[52]Suro-Perez. V, AJournel. Indicator principle kriging. Math Geology. 1991,23(5):759-788
[53]Suro-Perez V. Kriging and simulation based on principal component analysis. PhD thesis, Stanford Unversity, Stanford, CA,1992
[54]Deutsch C. and A. Journel. GSLIB:Geostatistical software library and users guide. Second Edittion:Oxford Univerity Press,1996
[55]White C.D and M. D. Barton. Translating outcrop data to flow models, with application to the Ferron sandstone. SOCIETY OF Petroleum Engineers Reservoir Evalution and Engineering.1999,2 (4):341-350
[56]Stephen Dalrymple. Reservoir simulations developed from an outcrop of incised valley fill strata. AAPG Bulletin.2002,86(5):797-822
[57]Wagoner J. C. V. et al. Sequence Stratigraphy in well, core, logs and outcrops:Concept for high-resolution correlation of time and facies. AAPG Motheds in Exploration Series,1990
[58]Galloway W. E. Genetic stratigraphic sequences in basin analysis I Architecture and flooding-surface bounded depositional units. AAPG Bulletin.1989,73:125-142
[59]Cross T. A. Field-scale reservoir characterization, in L. W. Lake, H. B. Carroll, and T. C. Wesson, (ed).Reservoir characterization II:Orlando, Florida, Acadenic Press,1991:493-497
[60]Cross T. A and R.G.Raynolds. Illustration of correlation techniques, facies prediction and reservoir compartment identification through genetic stratigraphy, Gallup sandstone and Mesa Verde Group (Cretaceous), Four-corners region. Rocky Mountain Association of Geologists.1993:71-75
[61]Cross T. A. and M. A. Lessenger. Sediment volume partitioning: rationle for stratigraphic model evaluation and high-resolution stratigraphic correlation, in, F. M. Gradstein, K.0. Sandvik and N. J. Milton, (ed),Sequence stratigraphy concepts and applicatons. NPF Special Publication,1998:171-195
[62]Cross T. A., (ed). Quantitative dynamic stratigraphy. New Jersey, Prentice Hall,1990:622-624
[63]Cross T. A., M. R. Baker, M. A. Chapin, M. S. Clark, M. H. Gardner, M. S. Hanson, M. A. Lessenger, L. D. Little, K. J. McDonough, M. D. Sonnenfeld, D. W. S. Valasek, M. R. Williams and D. N. Witter. Applications of high-resolution sequence stratigraphy to reservoir analysis, in R. Eschard and B. Doligez, (ed), Subsurface reservoir characterization from outcrop observation, Proceeding of the 7th IEP exploration and production research conference:technip,1993
[64]Cross T.A. Stratigraphic controls on reservoir attributes in continental strata. Earth science frontiers,2000,7(4):322-350
[65]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.1995,16(2)：89-97
[66]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.地学前缘.1997,7(4)：305-313
[67]樊太亮,吕延仓,顶明华.层序地层体制中的陆相储层发育规律.地学前缘.2000,7(4)：315-321
[68]邓宏文,王宏亮,李熙喆.层序地层基准而的识别、对比技术及应用.石油与天然气地质.1996,17(3)：177-184
[69]郑荣才,彭军,吴朝容.陆相盆地基准而旋回的级次划分和研究意义.沉积学报.2001,19(2)：249-255
[70]Guang ming Ti, D.O. Ogbe and D. G. Hatzignation. Use of flow unit as a tool for reservoir description:A case study. SPE.26919:122-128
[71]Amaefule et al. Enhanced reservoir description:using core and 1 data to identify hydraulic(flow) units and predict permeability in uncork intervals/well. SPE.26436,1993
[72]Maghsood et al. Permeability prediction by hydraulic flow unit theory and application. SPE Formation Evaluation.1996, (12)
[73]阎长辉,羊裔常,董继芬.动态流动单元研究.成都理工学院学报.1999,26(3)：273-275
[74]Scott H, Hamlin H. Depositional controls on reservoir properties in a braid-delta sandstone, Tirrawarra oil field, south Australia. AAPG Bulletin.1996,80(2):139-156
[75]Nei F Hurley. The ascertain of dolonitite karst cave flow nuits new mexico iol field. SPWLA 39th Annual Logging Symposiun.1998:1213-1218
[76]F Jervy Lucia. Characteri zation of Petropnysical Flow Units in Carbonate Reservoirs Discussion. AAPG Bulletin.1999,6(83):1161- 1163
[77]Feazel C T, Byrnes A P, Honefenger J W, et al. Carbonate Reservoir Characterization and simulation:From Facies To Flow Units.AAPG Bulletin.2004,88(11):1467-1470
[78]Canas J A, Malk E A. Characterization Of Flow Units in sands reservoirs La Cim Field,Colcmbin, South Amereca. Proceedings of the Peunian Basin oil Gas Recovery. SPE.1994:886-892
[79]高博禹,彭仕宓,陈烨菲.动态流动单元研究.成都理工学院学报.1999,26(3)：273-275
[80]李阳.储层流动单元模式及剩余油分布规律.石油学报.2003,24(3)：52-55
[81]赵翰卿.对储层流动单元研究的认识与建议.大庆石油地质与开发2001,20(8)：8-10
[82]吴胜和,王仲林.陆相储层流动单元研究的新思路.沉积学报.1999,17(2)：252-256
[83]Eilertsen Terje, et al.Experiments and numerical simulations of fluid flow in a cross layered reservoir model. Jouranl of Petroleum Science and Engineering.1997,18:49
[84]师永民,张玉广,何勇等.利用毛细管压力曲线分形分维方法研究流动单元.地学前缘.2006,13(3)：129-132
[85]张祥忠,吴欣松,熊琦华.模糊聚类和模糊识别法的流动单元分类新方法.石油大学学报.2002,26(5)：19-22
[86]金佩强,杨克远.国外流动单元研究描述与划分.大庆石油地质与开发.1998,17(4)：49-51
[87]尹太举,张昌民,王寿平等.濮53块流动单元评价.石油学报.2005,26(5)：85-89
[88]彭仕宓,尹志军,常学军.陆相储集层流动单元定量研究新方法.石油勘探与开发.2001,28(5)：68-70
[89]魏斌,陈建文,郑浚茂.应用储层流动单元研究高含水油田剩余油分布.地学前缘.2000,7(4)：403-409
[90]陈烨菲,彭仕宓,宋桂茹等.流动单元的井间预测及剩余油分布规律研究.石油学报.2003,24(3)：74-77
[91]Hewett T. A. Fractal methods for fracture characterization, in, Yarus and chambers (eds.), Stochastic modeling and geostatistics: principle, methods, and case studies. AAPG computer application in Geology.1994, (3)
[92]Wu H.and D. D Pollard. Detecting subsurface fracture network and drainage area using 1D borehole data:proceeding of the International conference of petroleum and petroleum chemistry. 1994:14
[93]Wu H. and D. D. Pollard. Imaging 3-D fracture networks around boreholes. AAPG Bulletin.2002,86(4):593-604
[94]Elsayed et. al. Multidisciplinary Reservoir Characterization and Simulation Study of the Weyburn Unit. SPE.1993, (11)
[95]Beliveau D, Payne D. A. and Mundry M. Waterflood nd C02 Flood of the Fractured Midale Field. JPT.1993:881-887
[96]Baker R.0, et. al. Characterization of the Dynamic Fracture Transport in an Naturally Fractured Reservoir. SPE.59690,2000
[97]Richard 0. Baker and Frank Kuppe, Reservoir Characterization for Naturally Fractured Reservoirs. SPE.2000, (11):1-13
[98]罗利.低孔砂岩孔隙度计算方法及裂缝识别技术.测井技术.1999,23(1)：33-37
[99]孙建孟,刘荣,梅基席等.青海柴西地区常规测井裂缝识别方布.测井技术.2005,29(1)：268-272
[100]张吉吕,郑丽辉.利用人工智能技术进行裂缝识别研究.测井技术.2005,29(1)：52-54
[101]中辉林,高松洋.基于BP神经网络进行裂缝识别研究.新疆石油天然气.2002,2(4)：39—52
[102]李雪英,蔺景龙,文慧俭.复杂地质背景下的多裂缝识别.大庆石油学院学报.2006,30(6)：16-19
[103]高霞,谢庆宾.储层裂缝识别与评价方法新进展.地球物理学进展.2007,22(5)：1460-1465
[104]Velde B, Duboes J, et al. Fractal analysis of fracture in rocks:the cantor's Dust method. Tectonphysics.1990(3):61-68
[105]Velde B. Structure of surface cracks in soil and mud. Tectonphysics.1999(1-2):101-104
[106]裘怿楠.储层地质模型.石油学报.1991,12(4)：55-62
[107]文健,裘怿楠.油藏早期评价阶段储层建模技术的发展方向.石油勘探与开发.1994,21(5)：88-93
[108]穆龙新,贾文瑞.建立定量储层地质模型的新方法.石油勘探与开发.1994,21(4)：82-86
[109]李元觉.层状定容气藏储层建模及其条件模拟法软件的实现.国际石油与石油化工科技研讨会.1994
[110]聂昌谋,纪发华.储层参数随机建模方法在胡状集油田储层非均质研究中的应用.断块油气田.1996,3(1)：26-30
[111]钟宝荣,李龙滟等.储层随机建模与条件模拟的计算机实现.油气成藏机理及油气资源评价国际研讨会.石油工业出版社.1998：312-317
[112]张永贵,陈明强.模拟退火组合优化算法在油气储层随机建模中应用.西南石油学院学报.1997,19(3)：1-7
[113]张永贵,李允,陈明强.储层地质统计随机模拟.石油大学学报.1998,22(3)：113-116
[114]王家华,张团峰.油气储层随机建模.石油工业出版社,2001：1-60
[115]张春雷,段林娣,王志章.储集层随机建模的改进河道模型条件算法.石油勘探与开发.2004,31(4)：76-78
[116]李少华,张昌民,林克湘等.应用改进的布尔方法建立砂体骨架模型.石油勘探与开发.2000,27(3)：91-92
[117]张祥忠,熊琦华,蔡毅.应用多级序贯指示模拟方法预测储集层岩性.石油勘探与开发.2003,30(6)：81-82
[118]吕晓光,潘懋,王家华等.指示主成分模拟建立分流河道砂体相模型及意义.石油学报.2003,24(1)：53-57
[119]刘振峰,郝天珧,方辉.用Markov链模型模拟储层岩相空间展布.石油学报.2005,26(5)：57-60
[120]尹太举,张昌民,王振奇等.利用序贯指示模拟方法预测储集层岩性.新疆石油地质.2002,23(1)：59-62
[121]徐景帧,刘晓冬等.渗透率建模的三维指示条件模拟方法及其应用.石油学报.2000,21(3)：61-65
[122]刘国旗,赵爱武.河流相多层砂岩油藏剩余油描述及挖潜技术.大庆石油地质与开发.2001,20(5)：34-37
[123]陈恭洋,何鲜,刘树明等.千米桥碳酸盐岩古潜山裂缝预测.中国石油勘探.2003,8(3)：84-91
[124]杨辉延,江同文,颜其彬.缝洞型碳酸盐岩储层三维地质建模方法初探.大庆石油地质与开发.2004,23(4)：11-16
[125]窦之林.储层流动单元研究.石油工业出版社,2000
[126]冉启全,王拥军,孙圆辉等.火山岩气藏储层表征技术.科学出版社,2011
[127]毛治国,胡望水,余海洋.油藏地质研究进展.特种油气藏.2007,14(4)：6-12
[128]申本科.油藏描述技术与展望.石油勘探与开发.2003,30(4)：78-81
[129]景成杰,胡望水,程超等.相控建模技术在高台子油藏精细描述中的应用.石油天然气学报,2009,31(1)：39-42
[130]高瑞琪,蔡希源.松辽盆地油气田形成条件与分布规律.石油工业出版社,1993：402-409