Deriving shallow‐water sediment properties using post‐stack acoustic impedance inversion

Abstract

In contrast to the use of marine seismic reflection techniques for reservoir‐scale applications, where seismic inversion for quantitative sediment analysis is common, shallow‐waterm, very‐high‐resolution seismic reflection data are seldom used for more than qualitative reflection interpretation. Here, a quantitative analysis of very‐high‐resolution marine seismic reflection profiles from a shallow‐water (<50 m water depth) fjord in northern Norway is presented. Acquired using Sparker, Boomer, and Chirp sources, the failure plane of multiple local landslides correlates with a composite reflection that reverses polarity to the south. Using a genetic algorithm, a 1D post‐stack acoustic impedance inversion of all three profiles is performed, calibrating against multi‐sensor core logger (MSCL) data from cores. Using empirical relationships the resulting impedance profiles are related to remote sediment properties, including: P‐wave velocity; density; mean grain size; and porosity. The composite reflector is consistently identified by all three data sources as a finer‐grained (by one ϕ), lower density (c. 0.2 g/cm3 less than background) thin bed, with an anomalous low velocity zone (at least 100 m/s lower than background) associated with the polarity reversal to the south. Such a velocity contrast is consistent with an accumulation of shallow free gas trapped within the finer‐grain, less permeable layer. This study represents the first application of acoustic impedance inversion to very‐high‐resolution seismic reflection data and demonstrates the potential for directly relating seismic reflection data with sediment properties using a variety of commonly used shallow seismic profiling sources.

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

“…Estimates of physical properties, such as undrained shear strength, effective stress, overpressure ratio and porosity, can be derived from the inverted elastic model (Hamilton, 1970;Richardson & Briggs, 1993;Mavko et al, 2009;Vardy, 2015). This opens the way to the extensive use of quantitative seismic interpretation as a means to obtain a detailed characterisation of the shallow sediment properties, as an efficient alternative to costly and time-consuming coring campaign.…”

“…The reflectors of the PSDM seismic section are used to correlate the inversion results to the core measurements, which have been filtered down to the seismic resolution after the removal of outliers and non-significant values. The axis scale of the porosity is reversed, to highlight the positive correlation between the reduction of porosity and the P-impedance (Vardy, 2015); we also expect to find a positive correlation between the clay content and the Poisson's ratio (Hamilton, 1970). The sedimentary log ranges from clay to gravel for loose sediments, whereas the presence of lithified material is marked by values going past the gravel base-line.…”

“…Holland & Dettmer (2013) used the angle-dependent reflection amplitude as a function of frequency to derive physical properties layering and gradients within the shallow sediments. Recently, post-stack acoustic inversion has been successfully applied on ultra-high-frequency seismic data (Vardy, 2015) to derive quantitative sediment properties from the acoustic impedance.…”

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

“…; Ker et al . ; Vardy ). For hydrocarbon applications, this has been expanded to multiple incidence angles in the form of extended elastic impedance or amplitude‐versus‐offset (AVO) inversion (e.g., Ma ), which derives S‐wave and P‐wave impedance.…”

“…, ; Holland and Dettmer ; Ker, Gonidec and Gilbert ; Vardy ; Vardy et al . ). Traditionally, however, geophysicists are interested in quantitatively characterizing the shallow subsurface using parameters that control the propagation of the seismic wavefield because at the heart of all seismic inversion approaches lies a reliable forward model that predicts the observed seismic data.…”