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J4 ›› 2015, Vol. 21 ›› Issue (3): 449-.

• 汇源系统与储层地质学 专栏(一) • 上一篇    下一篇

基于地质矢量信息的冲积扇储层沉积微相建模: 以克拉玛依油田三叠系克下组为例

冯文杰,吴胜和*,夏钦禹,李俊飞,伍顺伟   

  • 出版日期:2015-09-20 发布日期:2015-10-20

Micro-faciesModelingofAlluvialFanReservoirBasedonGeological VectorInformation:ACaseStudyontheTriassicLowerKaramay Formation,YizhongArea,KaramayOilfield,NWChina

FENG Wenjie, WU Shenghe*, XIA Qinyu, LI Junfei, WU Shunwei   

  • Online:2015-09-20 Published:2015-10-20

摘要:

冲积扇储层具有典型的非平稳分布特征,传统的基于平稳假设的地质统计建模方法无法准确模拟其沉积微相。在充 分分析其沉积微相分布特征的基础上,以克拉玛依油田三叠系克下组冲积扇储层为例,综合现代沉积、密井网、露头等信 息,应用基于地质矢量信息的多点地质统计学方法建立了精细、合理的储层沉积微相三维模型。首先,综合现代沉积特征 与地下储层沉积微相解剖成果,应用“模式指导、规模约束”的方法,建立符合研究区沉积模式和定量规模的训练图像和 基于冲积扇沉积体系的矢量坐标系统,表征了训练图像的地质矢量信息,提出基于预模拟实现的模拟域地质矢量信息表征 方法,建立了待模拟地质体的三维矢量信息模型;最后,采用基于矢量信息的多点地质统计方法建立了冲积扇储层沉积微 相模型,并采用多种标准对模拟实现进行可靠性分析。模拟结果表明冲积扇相带分布符合地质认识,沉积微相的形态、展 布特征、组合样式、规模与训练图像、地下沉积微相解剖认识相符。

关键词: 克拉玛依油田, 冲积扇, 训练图像, 地质矢量信息, 多点地质统计学

Abstract:

 As alluvial fan reservoir is typical in non-stationary distribution, the traditional modeling algorithm based on the steady-state assumption cannot simulate it accurately. On the basis of full analysis of the reservoir distribution, a case study of alluvial fan reservoir on the Triassic Lower Karamay Formation, Yizhong Area, Karamay Oilfield was carried out to integrate modern sediments, underground dense well group, outcrops and other information, using the latest Vector Information based Multiple-Point Simulation to reproduce a fine and reasonable three-dimensional geological model of reservoir architecture, which can be used as a reference for similar reservoir stochastic simulations. First, based on modern sediment and underground alluvial fan reservoir architecture analysis, an alluvial fan training image in line with the study area was constructed under the instruction of pattern guiding and scale constraints. Second, the vector coordinate system of an alluvial fan was constructed. Then the vector information of both training image and the target modeling area was characterized in this system. Finally, the reservoir architecture was reproduced by using the Vector information based on the Multiple-Point Simulation method. The reliability analysis of the realizations was performed. The result shows that the realizations are faithful to well data. Alluvial fan facies distribution in the model is suitable to geological model. Architecture element characteristics including shape configuration, distribution, combination style and scales matches training image and understanding reservoir architecture acknowledgment perfectly.

Key words: Karanay Oilfield, alluvial fan, training image, geological vector information, non-stationary, multiple-point geostatistics