Monte Carlo CLEAN Spectral Analysis Method for Detecting the Stratigraphic Cycles Based on High-resolution Electrical Image Log Data

Abstract

This paper performs a Monte Carlo CLEAN (MC-CLEAN) spectral analysis with high-resolution electrical image log data and interpret the high-resolution formation sequence by investigating the cycles in the sediments. Firstly, in order to perform a spectral analysis with high-resolution electrical image log data, the background conductivity log curve was extracted from the borehole image. Secondly, the MC-CLEAN spectrum analysis method was used to isolate all the peaks of the logging signal. Then the 95% significance level of the CLEAN spectrum was calculated to identify the true period of the formation by Monte Carlo simulation. Finally, the MC-CLEAN spectral analysis method was applied in the two shale intervals from Lower Pannonian interval of Vienna basin to identify the stratigraphic cycles. The analysis results showed that the identified cycles in the sedimentary record good matched the Milankovitch cycles. This paper provided a new approach of identifying stratigraphic cycles and interpreting high-resolution sequence stratigraphy.