Waveform tomography of field vibroseis data using an approximate 2D geometry leads to improved velocity models

Abstract

Waveform tomography, a combination of traveltime tomography (or inversion) and waveform inversion, is applied to vibroseis first-arrival data to generate an interpretable model of P-wave velocity for a site in the Nechako Basin, south-central British Columbia, Canada. We use constrained 3D traveltime inversion followed by 2D full-waveform inversion to process long-offset (14.4 km) first-arrival refraction waveforms, resulting in a velocity model of significantly higher detail than a conventional refraction-statics model generated for a processing workflow. The crooked-line acquisition of the data set makes 2D full-waveform inversion difficult. Thus, a procedure that improves the tractability of waveform tomography processing of vibroseis data recorded on crooked roads is developed to generate a near-surface ([Formula: see text]) velocity model for the study area. The data waveforms are first static corrected using a time shift determined by 3D raytracing, which accounts for the crossline offsets produced by the crooked-line acquisition. The velocity model generated from waveform tomography exhibits substantial improvement when compared with a conventional refraction-statics model. It also shows improved resolution of sharp discontinuities and low-velocity regions when compared to the model from traveltime tomography alone, especially in regions where the geometry errors are moderate. Interpretation of the near-surface velocity model indicates possible subbasins in the Nechako Basin and delineates the Eocene volcanic rocks of the study area. This approach limits the ability of the full-waveform inversion to fit some propagation modes; however, the tractability of the inversion in the near-surface region is improved. This new development is especially useful in studies that do not warrant 3D seismic acquisition and processing.

Waveform tomography in 2.5D: Parameterization for crooked‐line acquisition geometry

“…However, the static‐correction approach introduces additional errors into the data waveforms and is only applicable for certain wave arrivals (i.e., those that are well modeled by the initial travel time tomography processing). Here we present an improved version of the result from Smithyman and Clowes []; the new 2D methodology uses the logarithmic l 2 norm rather than the l 2 norm. It results in fundamentally different model perturbations that are more geologically consistent than those seen when the l 2 norm was used.…”

New geophysical models for subsurface velocity structure in the Nechako–Chilcotin plateau from 2.5-D waveform tomography

“…This choice reflected standard procedures in previous studies (e.g., Brenders and Pratt 2007;Smithyman and Clowes 2012), wherein the AVO correction was applied to partially account for aspects of the real data outside of the range of the 2-D viscoacoustic modelling operator; most notably, this accounts approximately for the differences in geometric spreading of wavefronts between 2-D and 3-D. In the 2.5-D case, the log-linear correction affected the recovered attenuation model, but was not required to account for geometric spreading effects.…”

“…The direction of geological strike for the FWI geometry was taken to be 17°, which is reasonable given the lithological boundaries observed in exposed basement and Eocene-age rocks at surface. However, this choice was made initially to optimally fit the orientation of the local section of the acquisition line for 2-D FWI processing (Smithyman and Clowes 2012) prior to the development of the 2.5-D waveform tomography methodology discussed by Smithyman and Clowes (2013). The +x direction was aligned to 107°(see Fig.…”

Application of waveform tomography to a crooked-line 2D land seismic data set

“…We also did not time shift traces because it is not trivial to properly time shift seismic waveforms including later arrivals. This projection approach leads to errors in offsets, and it potentially degrades the inversion results as discussed by Smithyman and Clowes (2012). Instead, a 2.5D waveform tomography approach may be more suitable for this data set (Smithyman and Clowes, 2013).…”