Optimal Processing of Single-Channel Sparker Marine Seismic Data

Abstract

Abstract Single-channel sparker seismic reflection systems are currently preferred in offshore geo-engineering studies due to their cost-effectiveness, ease of use in shallow areas, their high-resolution data, and straightforward data processing. However, the distinctive characteristics of sparker data introduce specific challenges in the processing of single-channel seismic datasets. These include (i) unavailability of the stacking process for single-channel seismic data, which is highly effective in eliminating random and coherent noise, (ii) inability to derive subsurface velocity distribution from single-channel seismic profiles, (iii) limitations imposed by ghost reflections and bubble effects as well as random noise amplitudes, and (iv) the suitability of only predictive deconvolution for suppressing multiple reflections. Applications demonstrate that the inability to apply the stacking process to single-channel seismic data poses a significant challenge in suppressing both random and coherent noise, and increasing the signal-to-noise (S/N) ratio. The F-X prediction filter has proven highly effective in mitigating random noise in sparker data. Appropriate determination of operator length and prediction lag parameters allows predictive deconvolution to effectively suppress multiple reflections, despite some residual multiple amplitudes in the output. Spiking deconvolution significantly eliminates ghost reflections and bubble effects, enhancing temporal resolution by eliminating the ringy appearance of the input signal. However, transforming the source wavelet to its minimum phase or zero phase equivalent is essential prior to deconvolution. Trace mixing is a crucial data processing step for enhancing sparker data resolution. The method can be applied as weighted mix for random noise suppression or as trimmed mix for suppressing high-amplitude spike-like noises.