A minimalist approach for improved time imaging of a noisy vibroseis data: A case study from Jaisalmer Basin, Rajasthan

Abstract

AbstractProcessing land seismic data, especially vibroseis data, is often challenging due to complicated near‐surface situations and source‐generated noise. The case study deals with noisy vibroseis data acquired in the Jaisalmer Basin. The near‐surface estimation in this area is difficult due to a possible velocity reversal manifested in the shingled patterns of the first breaks. The near‐surface workflow incorporates a model‐adaptive first break‐picking approach, essentially integrating two problems of first‐break‐picking and model estimation into a single problem. The signal‐conditioning workflow is based on cascaded scaling and single‐channel‐based noise reduction to prevent the removal of weak signals. Horizon‐based migration velocity analysis was used to focus reflectors on the constant velocity‐migrated stacks. This was particularly useful in areas with dubious velocity trends based on semblance panels. The velocity volume has structural consistency, which provides a better time‐migrated image. The workflow also incorporates a targeted post‐stack processing sequence to enhance continuity, sharpen discontinuities and improve the resolution, as notable by comparing the legacy‐processing results of the same dataset.