Real-time Baseline Drift Correction Method for Transient Electromagnetic Logging Signals Based on Adaptive Segmentation

The empirical mode decomposition can be used to solve the problem of baseline drift caused by downhole temperature changes. However, the endpoint effect problem of this method seriously affects the accuracy of data processing, and the increase of data volume reduces the efficiency of real-time data processing. In view of the above problems, a real-time baseline drift correction method for transient electromagnetic logging signals based on adaptive segmentation is proposed. The method combines the algorithm of adaptive segmentation processing on the basis of the mirror extension method, performing baseline drift correction processing after automatic segmentation of the logging signal, and realizing the automatic splicing of each segment signal by software, so as to obtain a complete reconstructed signal. The test results of field experimental data show that this method can realize the real-time and segmented baseline drift correction of original logging data, and can effectively improve the efficiency and accuracy of data processing.