基于体积模型和约束优化算法的页岩气储层孔隙度测井解释方法研究
Study of Logging Interpretation of Porosity Based on Volume Model and Constrained Optimization Algorithm in Shale Gas Reservoir
DOI: 10.12677/OJNS.2020.81002, PDF,    科研立项经费支持
作者: 刘鸿博：四川水利职业技术学院，四川 成都
关键词: 页岩气；孔隙度；测井解释；四参数模型；九参数模型；Shale Gas； Porosity； Logging Interpretation； 4-Parameter Model； 9-Parameter Model
摘要: 页岩储层与常规储层之间有显著区别，针对我国典型陆相页岩储层的特征，利用页岩储层特征参数和测井参数，建立起孔隙度解释的四参数模型和九参数模型，利用最优化算法，在合理的范围内拟合干酪根固体部分的密度、流体密度、干酪根中有机碳的质量百分数等各参数的值，预测储层孔隙度。这两种模型可以在已知或未知部分参数的情况下，精度较高地解释孔隙度。由此可见这两种方法是页岩气储层孔隙度解释较为适合的方法。
Abstract: There is a significant difference between shale reservoir and conventional reservoir. Under the characteristics of typical continental shale reservoirs in China, 4-parameter models and 9-parameter models for porosity interpretation are established by using shale reservoir parame-ters and logging parameters. Using the optimization algorithm, some important parameters are fitted in reasonable ranges. These models can explain the porosity effectively when partial pa-rameters are known or unknown, and thus are a suitable method for the interpretation of the po-rosity of shale gas reservoirs.
文章引用：刘鸿博. 基于体积模型和约束优化算法的页岩气储层孔隙度测井解释方法研究[J]. 自然科学, 2020, 8(1): 6-17. https://doi.org/10.12677/OJNS.2020.81002

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