An intelligent log-seismic integrated stratigraphic correlation method based on wavelet frequency-division transform and dynamic time warping: A case study from the Lasaxing oilfield

Abstract

Stratigraphic correlations are essential for the fine-scale characterization of reservoirs. However, conventional data-driven methods that rely solely on log data struggle to construct isochronous stratigraphic frameworks for complex sedimentary environments and multi-source geological settings. In response, this study proposed an intelligent, automatic, log-seismic integrated stratigraphic correlation method that incorporates wavelet frequency-division transform (WFT) and dynamic time warping (DTW) (also referred to as the WFT-DTW method). This approach integrates seismic data as constraints into stratigraphic correlations, enabling accurate tracking of the seismic marker horizons through WFT. Under the constraints of framework construction, a DTW algorithm was introduced to correlate sublayer boundaries automatically. The effectiveness of the proposed method was verified through a stratigraphic correlation experiment on the SA0 Formation of the Xingshugang block in the Lasaxing oilfield, the Songliao Basin, China. In this block, the target layer exhibits sublayer thicknesses ranging from 5 m to 8 m, an average sandstone thickness of 2.1 m, and pronounced heterogeneity. The verification using 1760 layers in 160 post-test wells indicates that the WFT-DTW method intelligently compared sublayers in zones with underdeveloped faults and distinct marker horizons. As a result, the posterior correlation of 1682 layers was performed, with a coincidence rate of up to 95.6 %. The proposed method can complement manual correlation efforts while also providing valuable technical support for the lithologic and sand body characterization of reservoirs.