Quantitative Seismic Inversion

SAND has developed a family of seismic processing and inversion algorithms specifically tuned for application to high-frequency, marine near-surface seismic reflection data. Broadly these are grouped into two software suites, QSI and QSI-3D, which deal with 2D and 3D data, respectively.

QUANTITATIVE SEISMIC IMAGING

The software includes bespoke imaging algorithms that have been developed to maximise the penetration and resolution of a variety of UHR marine seismic reflection data. These algorithms are capable of handling the irregular spatial sampling, high frequency content, and contamination by coherent noise (specifically source/receiver ghosts and seafloor multiples) while supporting quantitative imaging workflows including seismic inversion. Both time and depth imaging solutions are available.

QUANTITATIVE IMAGING

Seismic Inversion

By far the most novel component of QSI are a family of seismic inversion codes that use the amplitude, phase, and frequency content of seismic reflection data to derive quantitative information regarding the nature of the seabed and near-surface sediments. A range of different machine learning approaches can be applied, depending on the data/project requirements, permitting both bulk physical properties (e.g., P-wave velocity, bulk density, and porosity) as well as more advanced geotechnical properties (e.g., undrained shear strength, relative density, and soil classification) to be derived and mapped at a resolution controlled by the geophysical data.

The figure on the right shows an example where relative density (Dr) was derived from Chirp SBP data and mapped a high fidelity over a large area.

Attribute Analysis

Seismic attributes are properties derived directly from the seismic trace using some form of mathematical manipulation. These can include attributes that look at traces individually (such as instantaneous frequency) or collectively (such as structural dip). SAND have developed workflows to combine relevant attributes together that effectively highlight key structural features in a semi-quantitative manner. Effectively highlighting these often subtle facets in a way that permits efficient communication to other data users.

The figure on the left shows an example where several attributes have been combined to highlight free gas migration pathways within the shallow subsurface.

Interval velocities

Acquisition of multi-offset seismic reflection data is now standard practice for most large offshore site surveys, offering improvements over single-channel data in both image quality and the ability to derive detailed subsurface velocity models. SAND have developed several algorithms and workflows specially designed to produce high quality interval velocity models from typical ultra-high-resolution seismic reflection data, permitting these data to be pre-stack depth migrated.

In addition to providing enhanced seismic images and presenting the data in the more useful depth-domain, high-resolution interval velocity models provide excellent sediment discrimination, supporting detailed geological and geotechnical interpretation.

Q-factor Quantification

Q-factor quantifies seismic wavefield attenuation, representing the energy lost as seismic waves propagate through the subsurface. Q-factor has been shown to be strongly linked to the hydraulic permeability, allowing differentiation between cohesive and granular sediment behaviour. Q-factor analysis provides valuable information on the compressibility of near-surface sediments and can also offer estimates of gas saturation for shallow gas fronts.