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Logs in the petroleum boreholes indirectly records the sedimentary cycles in the deep burial formation. In order to extract and understand the periodicity and cyclicity, it is necessary to process the data by digital signal analysis method. Taking the gamma ray (GR) log as the primary material, an identification approach of Milankovitch cycles in boreholes is proposed in this paper, which is based on the Maximum Entropy Spectral Analysis (MESA). The first stage chooses the appropriate windows for calculating the frequency spectral properties in a short section of the data. In each depth window, the second stage generates the two-dimension frequency spectrum utilizing the MESA. At each depth point, the third stage finds the potential Milankovitch cycles in the one-dimension frequency spectrum, in which the average amplitude spectrum peak would be matched to the ratio of Milankovitch period. According to the frequency and wavelength of the maximum amplitude in Milankovitch cycles, the fourth stage estimates the sedimentation rate controlled by cyclical factor. Finally, the Milankovitch cycles in Lower Member of Miocene Zhujiang Formation in north slope of Baiyun Sag, Pearl River Mouth Basin, are identified and the cyclical sedimentation rate is estimated. The results demonstrate that the proposed method is feasible and effective to identify Milankovitch cycles in boreholes, which may contribute to the other geological researches.

open geosciences

Utilizing Maximum Entropy Spectral Analysis (MESA) to identify Milankovitch cycles in Lower Member of Miocene Zhujiang Formation in north slope of Baiyun Sag, Pearl River Mouth Basin, South China Sea