基于斑块饱和模型井控属性融合法油气检测

当前储层流体识别主要依靠地震资料振幅异常和弹性参数差异,实际应用中,往往存在地震振幅对油气层的反映不明显,弹性参数对油气层的区分性不强等问题,存在很强的多解性。针对该问题,根据斑块饱和模型分析对油气层敏感频率进行筛选,再利用已钻井钻遇的油气层信息进行控制,将速度频散属性和能量衰减属性进行融合获得油气敏感因子,提出了速度频散和能量衰减井控属性融合油气检测方法。渤海A油田的实际资料应用结果证明了本文方法能够有效检测储层含油气情况。

At the present stage,the recognition of reservoir fluid mainly relies on seismic amplitude anomalies and elastic parameters difference.In practical applications,there are always problems that seismic amplitude response is not obvious to hydrocarbon and the elastic parameters distinction between hydrocarbon and water is not clear.So conventional methods would lead to multiplicity of hydrocarbon detection.The oil-bearing reservoir leads to more strong velocity dispersion and energy attenuation of seismic wave than water-bearing reservoir,so it is feasible to use patchy-saturation model to sort hydrocarbon-sensitive frequency.In this paper,we obtain hydrocarbon-sensitive factor by merging velocity dispersion strong and energy attenuation strong,use the information of drilled reservoir in wells to control the merge answers and proposed the well-controlled velocity dispersion and energy attenuation attributes fusion method for hydrocarbon detection.The practical data test from Bohai A oilfield proved that this method can effectively predict hydrocarbon reservoir.

国家科技重大专项(2016ZX05058)资助。