The Method of Logging Curves Fusion Based on Multi-Scale Wavelet Transform

摘要

The mutation and form of logging curve can be represented by the variation of modulus maxima coefficients of wavelet transform within different scales exactly, then we can use wavelet multiscale edge detection theory to analyze characteristics of sequence stratigraphy boundaries in logging curves. Obtain the modulus maximum of approximation coefficient matrix and detail coefficient matrix after decompositing GR and SP curve in every scales. Compare and amend the modulus maximum of approximation coefficient matrix and detail coefficient matrix reciprocally, applicate the Mallat alternation foldover algorithm to reconstruction logging curve eventually, we can get the fusion curves in different scales. The fusion curves can greatly enhance characteristics of sequence stratigraphy boundaries in logging curves.