Thin interbed identification method based on seismic waveform similarity

As degrees of oil field exploration and development deepen，most target reservoirs are found to be thin，small，deep，and fractured. High⁃precision identification of thin interbedding has become the focus of reservoir prediction. At present，timefrequency analysis methods and spectral decomposition techniques commonly used in thin interbedding identification are limited by seismic data，and the processing results fail to meet the requirements of accurate characterization of thin interbedding. Due to the nonlinear characteristics of geophysical inversion，the results of high⁃resolution inversion have multiple solutions. In this paper，a thin interbedding identification method based on the similarity of seismic waves is proposed. Firstly，the idea of a waveform library is used to construct the waveform library of well bypass⁃sensitive logging curves. Secondly，the improved Manhattan distance combined linear correlation coefficient method is then used to calculate the waveform similarity. Finally the waveform similarity is taken as the only driver to establish the mathematical relationship between seismic data and high⁃resolution logging data，until the high⁃resolution processing profile is obtained. This method makes full use of the high transverse resolution of seismic data and the high longitudinal resolution of logging data，effectively identifies thin interbedding，and greatly reduces the multi⁃solution of inversion results. The feasibility of this method is verified by model test. The actual data processing results show that the proposed method significantly improves the longitudinal resolution and provides technical support for the identification of thin interbedding within a tuned scale. © 2024 Editorial office of Oil Geophysical Prospecting. All rights reserved.