Study On Reservoir Physical Properties Prediction Method Based On Sedimentary Facies Control

Adjusting well reservoir property prediction is very important for adjusting well deployment and drilling completion design.Under the control of sedimentary facies,the thickness,porosity and permeability of planar strata have heterogeneity.Traditional kriging interpolation method to predict reservoir physical properties such as formation in the adjustment wells,due to there have different sedimentary facie between adjustment well and some known well point,only consider interpolation points and the spatial difference between the sample points,and ignore the influence of sedimentary facies,reservoir property prediction result error is large.Therefore,it is necessary to classify the stratigraphic sedimentary facies according to the reservoir physical data of the stratigraphic sample point of the adjustment well,and then select the sample points in the same sedimentary facies region to predict the reservoir property of the adjustment well and improve the prediction accuracy.Firstly,based on the characteristics of stratigraphic sedimentary facies and the analysis of existing sedimentary facies division methods,because it is necessary to have the seismic,logging and drilling core data for the existing sedimentary facies classification method,and the prediction process is complex and time-consuming.In this paper,a method of sedimentary facies division based on k-means clustering algorithm is presented.which uses well logging interpretation data to divide stratigraphic sedimentary facies,and laying a foundation for the adjustment of reservoir physical property prediction.Then,through the different interpolation method to predict reservoir physical property,presents a facies-controlled-kriging interpolation method,the method through the sedimentary facies classification make interpolation well point data selection more reasonable,improve the precision of reservoir property prediction.Reservoir physical property prediction results in Penglai field show that facies-controlled-kriging interpolation prediction method to predict the formation permeability reservoir property error than ordinary kriging decrease by more than 7%.