【摘要】 从非线性混沌理论的角度对储层测井信号进行分析以及特征提取,避开以往测井信号分类特征基于线性理论的传统做法。目的是寻求不同流体性质储集层(油层、水层和干层)与其测井信号的混沌特征之间联系,希望为不同流体储集层提供一种新颖的测井解释方法。首先分析测井信号的混沌机理,之后对测井信号分别进行预处理和非平稳分析。在此基础上,对实际测井数据进行混沌特征的提取,如关联维数、最大Lyapunov指数和近似熵的提取及分析。研究结果表明,不同流体储集层的混沌特征参量数值大小存在明显差异。因此,在对测井信号提取混沌特征参量值之后,可根据参量值所处区间范围对储集层的不同流体性质进行解释。更多还原

【Abstract】 From the perspective of non-linear theory,chaotic characteristics of logging data were analyzed and extracted,and traditional approach based on linear classification theory of logging signals was avoided.We try to find chaotic characteristics of different of reservoirs(oil,water layer and the dry layer) to seek the relationship between different fluid reservoirs(oil,water layer and dry layer) and the chaotic features of logging signals.We hope providing a novel logging explanation method for different fluid reservoirs.Firstly,the chaotic mechanism of logging signals generating was analyzed.Secondly,logging signals were respectively pre-processed and analyzed based on non-stationary.On this basis,chaotic characteristics of actual logging data were extracted,for example,correlation dimension,and largest Lyapunov exponent and approximate entropy.The research results showed that chaos characteristics in different reservoir is different,therefore,we can distinguish the different natures of reservoirs by extracting chaos characteristics.The results show there was significant difference about the parameter value of chaos characteristic among different fluid reservoirs.Therefore,after the chaotic characteristics of logging signals were extracted,the different fluid properties of reservoirs can be explained according to parameter values range.更多还原