Application Of Wavelet Transform In The Stratigraphic Division And Correlation Of Well Logs

Stratigraphic division and correlation are indispensable parts in oilfield exploration and development.The geological structure and contact relationship of the underground strata can be obtained through the division of stratigraphic sequence,the identification of lithology and lithofacies,and the acquisition of stratum thickness,.Then the variation characteristics of the reservoir in the vertical and horizontal directions can be concluded.It's very important for exploring the distribution of the oil-gas reservoirs and the connectivities among them.There are many methods for stratigraphic division and correlation,such as geological analysis,paleomagnetism,paleontology,geochemistry and geophysics,etc.They are all based on changes in stratigraphic elements caused by changes in sedimentary environment.Well-logging curves contain abundant geological information,so the stratigraphic correlation method based on logging curve is very important.The basic idea of this method is to extract these information to divide the horizons,and then to compare the well logs.In this paper,the logging curve is analyzed by wavelet to obtain the layer information such as lithology,thickness,location and so on.As one of the most popular timefrequency analysis methods,wavelet transform can convert the logging curves into depthfrequency domain.By extracting the reconstruction curves at different scales,the interfaces of strata can be identified as abrupt points,then the horizons can be devided.Based on the result of the stratigraphic division,the window correlation can be carried out on the extracted curves between two adjacent wells,and the layer with the largest correlation coefficient can be identified to the target layer.The method proposed in this paper gets rid of the over dependence of traditional methods on geological information,combines logging curve data with mathematical tools,and automatically divides and contrasts the formation through self-adaptive parameter selection,which has the advantages of high precision,strong flexibility and convenient operation.