混沌功率谱熵方法在识别水淹低阻油层中的应用

Study on spectral entropy power identification method in water-flooded low resistivity zone

储集层孔隙度和电阻率曲线间微差形态波形的复杂程度隐含着储集层含油气性的信息,可以用混沌动力学系统加以刻划。油层相空间庞加莱截面明显具有自相似结构,呈现混沌特性;而水淹层和水层的相空间庞加莱截面显示,其混沌性呈显著减弱之势,系统趋于简单有序。其功率谱密度不论水淹程度如何,整体为一随频率增大其能量按指数递减连续频谱;随水淹程度逐渐减弱,递减幅度减小,整体能量逐渐降低,某些频率成分被吸收削弱,由光滑状逐渐演变成锯齿起伏状,其功率谱熵逐渐增大。基于测井信息的混沌特征和功率谱熵特征识别水淹层的方法,对利用传统测井解释理论判别比较困难的低阻油层有较强的识别能力。

The information of petroliferous reservoir is hidden in the level of differential waveform complexity between the resistivity and porosity log curves of reservoirs, which can be described by the use of the chaotic dynamics. The poincar map of the oil layer phase space clearly shows resemblance and presents chaos characteristics. The poincar maps of the water layer and swept layer phase space show an obvious decrease on the chaos characteristics, which tends to be simple in order. The density of power spectrum, on the whole, is an exponential declining curve along with frequency augmentation without reference to water flooded extent. When the water flooded extent reduces gradually, the decreasing extent becomes smaller and the whole energy lowers down.. Some certain frequency components are absorbed, the curve changes gradually from slick to dentate, and the power spectral entropy increases gradually. The conventional log explanation theory poorly identifies the low resistivity oil layer, which is well identified by the identification method based on chaos and the power spectral entropy characteristic of log signal.