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在油田勘探开发的各个阶段,井数据显然是建立真实三维油藏模型的关键参数。通常,油藏模型基于已有的数据而建立,尽管它未必是油田建模的最佳数据。已有的数据可能不足以广泛地表征油藏中决定流动特征的关键非均质性。本文旨在提出一种方法,在研究早期就考虑地质非均质性,以便预期评价必备的条件和优化油藏建模中的岩石类型分布。事实上,该方法在于找到更好地表征和更快捷地诊断的统筹方法。应用不同例子阐述这一方法。该方法在油藏评价阶段和生产开发阶段各不相同。相应地,对不同的地质非均质性类型,所用的工具和技术也不相同。这些非均质类型包括:砂质碎屑储层,裂缝性/喀斯特化储层,混合岩性储层(碎屑岩和碳酸盐岩,碎屑岩和裂缝)等等。每种情形都需要不同类型的数据去表征其非均质性。在这些例子中对各种情形的诊断表明、当取样介质的数据具有代表性时,可获得最佳解释。
Well data is clearly a key parameter in establishing a true 3D reservoir model at each stage of exploration and development. In general, a reservoir model is built on existing data, although it may not be the best data for oilfield modeling. The available data may not be sufficient to broadly characterize the key heterogeneities that determine flow characteristics in the reservoir. This paper aims to propose a method to consider geological heterogeneity early in the study so that the conditions necessary for evaluation and the distribution of rock types in reservoir modeling can be optimized. In fact, the solution lies in finding an integrated approach that better characterizes and diagnoses faster. Use different examples to illustrate this method. This method varies in reservoir evaluation and production stages. Accordingly, the tools and techniques used are also different for different types of geological heterogeneity. These heterogeneous types include sandy clastic reservoirs, fractured / karstified reservoirs, mixed lithologic reservoirs (clastic and carbonate rocks, clastic rocks and fractures), and more. Each situation requires different types of data to characterize its heterogeneity. The diagnosis of various situations in these examples shows that the best explanation is obtained when the data on the sampling medium is representative.