最大熵谱分解技术在A油田薄砂储层厚度预测中的应用

Application of Maximum Entropy Spectrum Decomposition Technology to Thickness Prediction of Thin Sand Reservoir in Oilfield A

渤海A油田目的层为曲流河沉积,河道砂体厚度薄,砂体厚度精确预测是油田开发方案设计的关键。首先介绍了各种谱分解方法的特点,然后介绍了薄层识别原理,最后应用最大熵谱分解方法对渤海新近系A油田明化镇组下段储层厚度进行了定量预测。有效预测了厚度小于10m的储层,与已钻井有很好的吻合度。最大熵谱分解方法具有分辨率高、效率高的特点,适合油田勘探及开发初期少井储层预测。

The target layer of Bohai oilfield A is meandering river deposition,the thickness of channel sand body is thin,and the accurate prediction of sand body thickness is the key to the design of oilfield development plan.Firstly,the characteristics of various methods of spectral decomposition are introduced,and then the principle of thin-layer identification is introduced.Finally,the maximum entropy spectrum decomposition method is used to quantitatively predict the reservoir thickness of the lower member of Minghuazhen formation in Neogene oilfield A in Bohai bay basin.The reservoir thickness less than 10 meters is effectively predicted,which is in good agreement with the drilling.The maximum entropyspectrum decomposition method has high resolution and high efficiency,which is suitable for reservoir prediction with few wells in the early stage of exploration and development.