【作者】 王云龙；

【导师】 贾振岐； 宣美乐；

【作者基本信息】 大庆石油学院 ， 石油与天然气工程， 2009， 硕士

【摘要】 大安油田大208区位于松辽盆地中央坳陷区大安——红岗阶地二级构造带,为中央坳陷区和西部斜坡区两个相对升降运动的一级构造单元过渡带,属于阶地挤压构造油气聚集带。该区主要开发扶杨特低渗透油层,储层物性差,开发难度大。本研究通过对大208区三维地震资料、岩心资料和矿场动态数据的综合分析,开展油藏精细地质研究,确定研究区油层发育特征、储层四性关系及储层分布规律,进行扶杨油层储层三维地质建模,以指导该区域剩余油的研究和开发,为今后制定开发对策及调整方案提供依据。具体包括如下工作及成果:通过取芯井岩芯观察,确定该区域岩芯沉积微相类型及发育规律和特征,对每口井的每个小层或砂岩组进行沉积微相人工解释,确定岩—电对应关系标准,建立每口单井纵向沉积微相模型。在岩芯观察和测井资料综合解释的基础上,进行小层重新划分与对比,建立高分辨率层序控制下的小层体系。以岩石地层学和高分辨率层序地层学指导,应用点、线、面三位一体的方法,对扶杨油层67口井25个小层进行精细的小层划分与对比,建立精细的小层模型。根据试油、投产结果,开展四性特征及四性关系研究,建立油层识别电性界限,开展测井资料二次数字处理,对油水层进行综合解释工作,划分有效厚度。结合小层精细对比的结果,通过三维地震资料的精细解释,建立三维精细的构造地层模型,为精细储层模型的建立提供重要的基础资料。在上述研究的基础上,确定该区储层砂体空间分布的统计模型,为砂体骨架预测模型的建立提供参数,结合测井资料处理,分析工区沉积微相对储层物性的影响。根据小层对比及沉积微相研究成果,利用趋势和目标模拟相结合的方法,对小层或砂组的沉积微相进行模拟。应用地质统计学、相控随机模拟的方法,利用PETREL油藏建模软件,对储层的分布和物性参数进行相控随机建模,建立基质及其属性三维模型。更多还原

【Abstract】 Region 208 of Da’an Oilfield, an oil-gas accumulation zone squeezed by terrace structures, lies in the second tectonic zone of Da’an-Honggang terrace at the central depressed area of Songliao Basin. It belongs to a transition belt between two first grade structural units with relatively up-and-down movement as the central depressed area and the western slope area. The low permeable targets of Fu and Yang, which are developed as the main pay zones, have poor physical properties and are difficult to exploit. In this paper the fine reservoir geology were studied at the Region 208 of Da’an Oilfield by comprehensive analyses of the 3-D seismic method, core data and the dynamic information to determine the features of the oil layers development, the relations between 4 reservoir properties and the distribution laws of oil formation, then to build the 3-D model of Fu-Yang targets. This study would be meaningful to guide the studies and development of the residual oil inside this area, and to provide further foundation for the development methods and the adjustment program. There are fruits as following:Firstly cores from holes were surveyed to determine the types of sedimental microfacies and their development laws and features of the rocks within this area. For each substratum or sand group, the sedimental microfacies were interpreted manually to determine the standard of the relation between rock and electricity and to construct the model of the vertical sedimental microfacies of every well.On the combined bases of core survey and logging information, the substratum was divided and compared again to the substratum system under the control of high-resolution strata sequence. Based on the stratigraphy of the rock and the high-resolution strata sequence, in usage of the integrated method system of points, lines and fancies, the fine substratum model was built by closely division and comparison for the 25 substrata in the 67 wells of Fu-Yang reservoir.According to the results of oil testing and production, the relationship of the 4 properties were studied to build the electricity recognition limit of the pay zone. The well logging information was treated secondly digitally to interpret the oil-water layers comprehensively and to divide the effective thickness.With the results of the fine substratum contrast, by the fine interpretation with 3-D seismic data, a 3-D fine structural reservoir model was built to provide important bases for the fine reservoir model.In sum of the above studies, the statistical model about the space distribution of reservoir sand body was then fixed to provide parameters for the predictive model of the sand body skeleton. And in combination with the treatment of the logging data the effect of sedimental microfacies on reservoir physical properties was analyzed for the target area.In accordance with results of both substratum comparison and studies on sedimental microfacies, the two modeling methods of both trend and target were used to simulate the sedimental microfacies of substrata or sandstone groups.The reservoir model construction software, Petrel, is used to build the 3-D phased model of the Matrix and its properties such as the physical parameters and their random distribution.更多还原