Automated depth matching of heterogeneous well logs using cross-correlation method

Abstract

Well logging is one of the main decision support methods in the oil and gas industry. However, depth mismatches between logs recorded with different runs or different logging tools in the same well remain a complex problem in the industry. Until now, the oil and gas industry has relied heavily on the judgment of log analysts, who manually align log data before interpreting them. Nevertheless, the process of manually depth alignment is subjective and time-consuming. This paper proposes a preprocessing algorithm that clean the data to apply Pearson correlation as a depth alignment metric. A cross-correlation depth alignment algorithm was proposed and tested on five wells located in Western Siberia. We also derived pairs of different-type logs from different bundles to calculate the optimal offset by cross-correlation.