Location: Watershed Physical Processes ResearchTitle: Utilizing CRS stack for enhanced near-surface seismic reflection imaging: Examples from consolidated and unconsolidated environments
|BAKHTIARA, RAD - University Of Mississippi|
|HICKEY, CRAIG - University Of Mississippi|
Submitted to: Geophysics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/2/2022
Publication Date: 4/29/2022
Citation: Bakhtiara, R.P., Hickey, C. 2022. Utilizing CRS stack for enhanced near-surface seismic reflection imaging: Examples from consolidated and unconsolidated environments. Geophysics. 87(5):1-91.
Interpretive Summary: Near-surface seismic reflection surveys are usually employed to obtain valuable information about subsurface structures, void and tunnel detection, groundwater prospecting, and engineering site characterization. However, high levels of noise in the data make it difficult to extract useful information. The authors propose a new workflow for enhancing near-surface seismic reflection imaging. The proposed approach makes use of wavefront properties of seismic waves and helps to predict and fill the missing parts of shallow seismic sections. The results of the study will be used to improve geophysical detection of subsurface features such as the detection underground voids.
Technical Abstract: The small geophone spacing and spread lengths commonly used to investigate ultra-shallow layers in conjunction with the limited bandwidth of surface impact sources do not allow for clear separation of different seismic arrivals. The interference of events and the high noise levels due to near-source offsets make shallow seismic data processing a challenging task. The wavefront attributes of seismic waves commonly used in conventional seismic processing are suggested to improve near-surface seismic reflection imaging. These wavefront attributes are often utilized as the stacking parameters in multidimensional time imaging methods such as common reflection surface (CRS). It is shown in this paper that the CRS method can improve near-surface seismic data processing by enhancing: (1) unstacked gathers via a CRS-based local stacking scheme, (2) semblance picking for velocity model building, and (3) zero-offset stacked data via the CRS global stacking. The CRS-based local stacking can mitigate the loss of data associated with optimum-windowing based muting of coherent noise. The CRS local stacking infills the muted zones via its robust data interpolation and regularization features and enhances the image quality. Furthermore, the CRS-based enhanced data allows for improved near-surface velocity model building by producing higher coherence and more focused semblance peaks. The CRS global stacking is shown to further smooth and provide more continuity of events in the zero-offset data. Applications to a synthetic and two field data sets collected from high and low velocity environments, show the efficiency and feasibility of the proposed approach.