True-amplitude vector-acoustic imaging: Application of Gaussian beams

Abstract

Acoustic Gaussian beam migration is an attractive imaging method because it is flexible with input geometry, efficient, and accurate in imaging multipath arrivals. However, one of the hurdles that this method must overcome in production processing is its extension to use multimeasurement data, as recently allowed by novel acquisition technologies. This is inevitable when the compensation of the ghost effect is best corrected within a true-amplitude imaging process, a necessity for amplitude-variation-with-offset work. For this purpose, I introduced a novel formalism for vector-acoustic imaging, based on Green’s function theory, which can remove the ghost effect and produce amplitudes on reflectors that are proportional to the reflection coefficients. I established a theoretical framework with Gaussian beam representations of Green’s functions, including the weighted beam-stacking approach that reduced the cost of computation. I extended my formulas to use the steep-descent (i.e., stationary phase) approximation. Then, I explained the impact of this approximation on the illumination and the event continuity and sharpness. I also studied the special case of acoustic imaging corresponding to using single-measurement (i.e., pressure) data. I applied the derived formulations to realistic synthetic multisensor data (North Sea) using a research code of Gaussian beam migration. The numerical examples demonstrated that I can improve the illumination of the final images and obtain wide-bandwidth reflectivity maps.

A fast algorithm for prestack Gaussian beam migration adopting the steepest descent approximation

“…Casasanta and Gray (2015) proposed converted-wave Gaussian beam migration, in which the steepest descent approximation was adopted to solve the migration formula. Yadari (2015) proposed the method of vector-acoustic Gaussian beam migration, in which the steepest descent approximation was also used. Hu et al (2016) developed a least-squares Gaussian beam migration method to increase the illumination and broaden the bandwidth of the migration images, in which a time-domain expression similar to Hale (1993a) but for the prestack Gaussian beam migration formula was presented.…”

Vector-acoustic reverse time migration of Volve ocean-bottom cable data set without up/down decomposed wavefields

“…Zhenhua and van der Baan (2014) use VARTM for microseismic event localization. El Yadari andHou (2013) andEl Yadari (2015) adapt the VA framework to Kirchhoff and beam migration, respectively. Finally, Ravasi and Curtis (2013a) and Ravasi et al (2014a) extend this methodology to elastic (e.g., land or hard-seabed) data sets, in which wave-mode (P-and S-wave) separation is also embedded within wavefield extrapolation (Mittet, 1994).…”

The effect of free‐surface reflections on depth images for acquisition with buried sources and receivers: Investigation through the point spread function#

“…These multicomponent records can determine actual wave propagation directions. Therefore, the primary reflections can be separated from free‐surface reflections and then injected for migration imaging (Amundsen & Robertsson, 2014; El Yadari, 2015; Fleury & Vasconcelos, 2013; Ravasi et al., 2015; Vasconcelos, 2013). This type of acquisition and the corresponding processing provide possibilities to use the separated free‐surface reflections as useful signals, rather than treating them as noises (Carlson et al., 2007; Day et al., 2013; Kumar et al., 2016; Lu et al., 2014; Liu & Liu, 2019; Whitmore et al., 2010).…”