Harmonic Decomposition Utilization for Frequency Broadening and Signal Decontamination in Zero-Offset VSP Data

Vertical Seismic Profiling (VSP) is a crucial subsurface imaging technique that is used to establish a link between the surface-recorded seismic data and subsurface-recorded geological data such as well logs. Among the various VSP acquisition geometries, the zero-offset VSP (ZVS) configuration, characterized by the seismic source being positioned very close to the well-head, is the most commonly acquired. That is because ZVSP data is fundamental in obtaining a reliable time-depth relationship at the well's location. With several of such control points at multiple wells, reliable imaging of seismic in the depth domain is further enhanced due to better-constrained depth imaging velocity models. Furthermore, ZVSP data can be used to obtain a corridor stack, which is a single trace largely free of multiples, offering a reliable record of primary reflections at the well's location. Notably, the VSP data exhibits a broader frequency spectrum compared to surface seismic data because the waves travel through the attenuating near-surface layers only once as opposed to twice for surface seismic data. This inherent higher frequency content allows ZVSP data the potential to resolve finer beds in the subsurface, a capability that the methodology discussed in this paper aims to further exploit and showcase. The repeated emphasis on ZVSP data's function as a bridge between well log data, which is inherently in the depth domain, and surface seismic data, which is in the time domain, underscores its role as an essential tool for a comprehensive interpretation and integration of seismic data. The interested reader is directed to Hardage (1983) for a detailed explanation of VSP theory. Despite its inherent advantages, achieving optimal subsurface resolution remains a challenge, and the presence of noise contamination can significantly affect the quality of the results. Conventional ZVSP processing techniques may not be able to fully utilize the broadband frequency spectrum contained within the data. Noise can be emitted from various sources, including ground conditions at the Vibroseis location, which can significantly degrade the quality of the emitted seismic signal, as well as harmonic distortions generated by the source itself (More et al., 2007). Such noise contaminations can severely affect data quality, limiting the effective frequency content, and reducing the accuracy of the correlation with synthetic seismograms derived from well-log data. To address these challenges, we propose the utilization of harmonic decomposition and its filtration as a technique for noise-mitigation and frequency broadening. Harmonic decomposition offers a method to analyze, separate, and leverage the higher-frequency components of the seismic data, known as harmonics, which are often overlooked in conventional seismic processing. By effectively isolating, processing, and incorporating these harmonics, we aim to substantially broaden the frequency content of the processed data. Furthermore, harmonic decomposition may facilitate signal decontamination by isolating and separately processing the fundamental and harmonic modes of the data. Leveraging harmonics - traditionally regarded as unavoidable noise - for the purpose of enhancing subsurface imaging represents a paradigm shift in approach that this paper will attempt to showcase in detail.