致密储层流体性质测井识别

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致密油气由于储层非均质性强、孔隙结构复杂、岩性电性变化大、储层气水关系复杂、测井响应特征复杂,应用常规测井资料识别储层流体性质存在较大困难。根据以往的研究成果,论述了依据测井响应特征如何选取流体性质识别时所需的测井参数,并对重叠图法、交会图法、Archie公式法和BP神经网络法进行了梳理、归纳和优缺点分析,指出根据单一的测井解释方法识别流体性质容易引起多解性,技术风险较高。基于研究区地质、岩心、录井等资料,结合多种测井曲线,合理选取参数并进行优化处理,开展流体识别综合研究是一个重要的技术思路。未来的发展方向为研制适应致密储层定量解释要求的高精度测井装备,建立测井质量控制体系,深化研究致密储层孔隙结构测井评价,建立致密储层饱和度模型,进一步完善解释方法技术,开展致密储层油气成藏规律研究。 Due to the characteristics of reservoir heterogeneity, complex pore structure, large changes of lithology, complex gas-water relationship and complicated logging response characteristics, it is difficult to identify the properties of reservoir fluids by conventional logging data. According to the previous research results, the logging parameters required for fluid property identification based on log response characteristics are discussed, and the overlay method, intersection graph method, Archie formula method and BP neural network method are summarized and summarized Analysis of advantages and disadvantages, pointed out that according to a single log interpretation method to identify fluid properties easily lead to multiple solutions, the higher the technical risk. Based on the data of geology, core and well logging in the study area, combined with a variety of well logging curves, the reasonable selection of parameters and optimization, the comprehensive study of fluid identification is an important technical idea. Future directions for the development of high-precision logging equipment to meet the requirements of quantitative interpretation of tight reservoirs, the establishment of logging quality control system, deepen the study of the pore structure of tight reservoir logging evaluation, the establishment of tight reservoir saturation model to further improve the interpretation method Technology, research on hydrocarbon accumulation in tight reservoirs.
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