The Study of Interlayer Identification Based on Well Logging Curve Units

The distribution of interlayers in reservoirs has a significant impact on the flow of reservoir fluids. Accurate identification of interlayer distribution is crucial for analyzing oil–water migration patterns and formulating optimal development strategies. Current research on interlayers mainly focuses on qualitative analysis, particularly regarding sedimentary environments and petrophysical characteristics. However, research on the quantitative analysis of interlayers is relatively scarce, and most identification methods rely on manual interpretation, which introduces human bias. To address this issue, this paper proposes an automatic interlayer identification method based on logging curve units, in P Oilfield. By analyzing the sedimentary and petrophysical characteristics of argillaceous and calcareous interlayers, along with their logging curve responses, multiple logging curves are integrated into a single comprehensive curve. This enables the automatic identification of both single-well and inter-well interlayers, achieving an identification accuracy of up to 90%. This method effectively improves the accuracy and efficiency of interlayer identification and demonstrates high application potential. Analyzing actual data from the P Oilfield, this study reveals the dominant role of interlayers in controlling the distribution of remaining oil in bottom-water reservoirs. It also summarizes three typical remaining oil distribution patterns: basal oil, dome oil, and cap oil. These findings provide practical guidance for subsequent oilfield development and enhanced recovery. This method not only offers an automated solution for interlayer identification in oilfields but also provides scientific evidence for precise decision-making in oilfield development.