Compressive Sensing-Marchenko Multiple Elimination in Complex Field Land Seismic Data

Abstract

In seismic exploration, the multiple suppression is crucial for accurate subsurface imaging and resource identification. Internal multiples, generated by multiple reflections at impedance interfaces, act as interference signals that can mislead resource exploration. Compared to traditional methods, the conventional Marchenko multiple elimination (C-MME) method allows for the direct extraction of primary waves from seismic records without requiring a macro velocity model or predictive subtraction, thereby preserving effective signals. However, challenges, such as low signal-to-noise ratios (SNRs) and high-density sampling requirements, have hindered its application to field land seismic data. To address these challenges of C-MME in field seismic data processing, we propose a compressive sensing-based Marchenko multiple elimination (CS-MME) method, which incorporates efficient denoising, reconstruction, and deconvolution capabilities. In this study, the CS-MME method has demonstrated exceptional performance in processing field land seismic data, successfully overcoming the aforementioned challenges. marking the first successful implementation of Marchenko multiple elimination (MME) on field land data.