Pre-stack full waveform inversion of ultra-high-frequency marine seismic reflection data

Abstract

SUMMARYThe full waveform inversion (FWI) of seismic reflection data aims to reconstruct a detailed physical properties model of the subsurface, fitting both the amplitude and traveltime of the reflections generated at physical discontinuities in the propagation medium. Unlike reservoirscale seismic exploration, where seismic inversion is a widely adopted remote characterisation tool, ultra high frequency (UHF, 0.2-4.0 kHz) multi-channel marine reflection seismology is still most often limited to a qualitative interpretation of the reflections' architecture. Here we propose an elastic full waveform inversion methodology, custom-tailored for pre-stack UHF marine data in vertically heterogeneous media to obtain a decimetric-scale distribution of Pimpedance, density and Poisson's ratio within the shallow sub-seabed sediments. We address the deterministic multi-parameter inversion in a sequential fashion. The complex trace instantaneous phase is first inverted for the P-wave velocity to make-up for the lack of low-frequency in the data and reduce the non-linearity of the problem. This is followed by a short-offset Pimpedance optimisation and a further step of full offset range Poisson's ratio inversion. Provided that the seismogram contains wide reflection angles (> 40 degrees), we show that it is possible to invert for density and decompose a-posteriori the relative contribution of P-wave velocity and density to the P-impedance. A broad range of synthetic tests is used to prove the potential of the methodology and highlights sensitivity issues specific to UHF seismic. An example application to real data is also presented. In the real case, trace normalisation is applied to minimise the systematic error deriving from an inaccurate source wavelet estimation. G. Provenzano et al.The inverted model for the top 15 meters of the sub-seabed agrees with the local lithological information and core-log data. Thus we can obtain a detailed remote characterisation of the shallow sediments using a multi-channel sub-bottom profiler within a reasonable computing cost and with minimal pre-processing. This has the potential to reduce the need of extensive geotechnical coring campaigns.

State‐of‐the‐art remote characterization of shallow marine sediments: the road to a fully integrated solution

“…Even when an acquisition geometry/method is used whereby S‐wave velocities can be derived, the uncertainties compared to P‐wave velocities are often very high (Provenzano et al . ). While P‐wave properties such as P‐wave velocity and impedance can be expected to demonstrate some relationship to the soil strength/stiffness, it will be a much more complex one that is both site‐specific and, in all likelihood, facies‐specific.…”

“…S‐waves have long been known to have an increased sensitivity to lithology (as well as pore pressure conditions) over P‐waves (e.g., Ayres and Theilen ), but quantifying S‐wave structure in the marine setting is difficult, relying on either using complex and often unwieldy source/receiver geometries (e.g., Vanneste et al . ) or estimating mode‐conversion through AVO effects as part of an FW inversion (e.g., Provenzano, Vardy and Henstock ). ‐factor, in contrast, can be estimated using several different techniques (e.g., Schock et al .…”

“…S-waves have long been known to have an increased sensitivity to lithology (as well as pore pressure conditions) over P-waves (e.g., Ayres and Theilen 1999), but quantifying S-wave structure in the marine setting is difficult, relying on either using complex and often unwieldy source/receiver geometries (e.g., Vanneste et al 2011) or estimating mode-conversion through AVO effects as part of an FW inversion (e.g., Provenzano, Vardy and Henstock 2017). Q-factor, in contrast, can be estimated using several different techniques (e.g., Schock et al 1989;Stevenson, McCann and Runciman 2002;Pinson et al 2008;Morgan et al 2012) and has been shown empirically to have a strongly bi-modal relationship with grain size, in essence, differentiating between cohesive and granular materials (Pinson et al 2008;Vardy et al 2012).…”

“…However, as previously discussed, S-wave measurements of the marine near-surface data are rare (see Table 2). Even when an acquisition geometry/method is used whereby S-wave velocities can be derived, the uncertainties compared to P-wave velocities are often very high (Provenzano et al 2017). (Leighton and Robb 2008;Vardy et al 2015), whereas Figure 6d shows Poisson's ratio curves for inside and outside the gas front derived using an FW inversion (Provenzano et al 2016).…”

Appraisal of Instantaneous Phase-Based Functions in Adjoint Waveform Inversion

“…It is suitable for all types of acquisition geometries and it is appropriate for marine and land data. It has so far been applied to a broad range of frequencies; long wavelengths (up to 0.1 Hz) for regional studies with global earthquake records [3], [9], for active seismic source experiments for subsurface data at medium scale (10 Hz), and for the water column at small scale (50 Hz) [8] and even at ultrahigh frequency marine seismic reflection data (1 kHz) [21]. Also, it allows multiparameter inversion; e.g., p and s wavevelocities, anisotropy, density, and attenuation.…”