An Intelligent Depth Correction Method for Logging Curves Based on Pearson Correlation Coefficient and DTW

A key step in the exploration and development of oil and gas fields in the oil and gas industry is to measure various geophysical parameters along the well depth by means of logging equipment. These measurements are used to understand underground geological conditions and to discover and evaluate hydrocarbon reservoirs. Different well logging tools measure the same well multiple times. Before logging interpretation and evaluation, the correction of well logging depth in a single well for different times is an essential link, and also a long-term problem in the industry. The typical method in the existing commercial logging software system is the correlation method based on two logging curves or the magnetic marking curve method, which achieves depth correction semi-automatically or manually, with low efficiency. This paper has developed a full-automatic depth correction method for well logging curves by combining Pearson correlation coefficient method with DTW algorithm. Firstly determine the sliding range of the dual windows, and calculate the correlation coefficient of the twocurves; then calculate the distance between the two curves within the window range by the DTW algorithm to control the quality of the curves and avoid correction errors. Determine the depth correction value based on the correlation coefficient and DTW distance, and complete the interpolation of logging curves using Akima interpolation algorithm. The experiment shows that this method can quickly and reliably complete automatic correction of logging curves, greatly increase the efficiency of logging interpretation, and improve the accuracy of correction.