A petrophysical approach to the investigation of shallow marine geology

Abstract

Interpretations of commercial marine shallow seismic data are generally limited to a prognosis of lithologies based on sparse ground truth data and regional stratigraphic models and a probability assessment of encountering perceived geohazards. However, an approach based on analyses of available petrophysical data can provide a more robust assessment of shallow marine lithologies and a more confident interpretation of shallow gas and overpressured formations. Generation of well‐ and borehole‐log acoustic impedance curves provides the starting point for these investigations and, although not all of the requisite data may be present in shallow section wireline suites, the Faust and Gardner equations, and other empirically derived relationships, can supply acceptable mathematical approximations. Impedance inversions of reflection seismic data facilitate more confident interpretations of lithological units, especially when combined with additional datasets such as gamma‐ray, resistivity, porosity, and S‐wave sonic, as elastic and extended elastic inversions. Anomalous seismic events interpreted to represent a probability of encountering shallow gas using traditional interpretation methods may be further investigated using amplitude‐versus‐offset cross‐plotting techniques, including fluid factor calculations, and the potential for overpressured gas accumulations or flow sands may be estimated from velocity‐derived pore pressure calculations. Geological and synthetic seismic modelling exercises provide the opportunity to test petrophysical interpretations in the absence of ground truth control data.

A regional CO2 containment assessment of the northern Utsira Formation seal and overburden, northern North Sea

“…It is possible that the seismic indicators used here to highlight potential gas presence and palaeo-gas migration can be produced by different geological processes, including: (a) velocity pull-downs and acoustic blanking from overlying glacial valleys (Huuse & Kristensen, 2016); (b) pockmarks caused by de-watering (Andresen & Huuse, 2011) and (c) high-amplitude reflections from thin bed tuning or lithological effects (Barrett et al, 2017). Although not used here, well data are highly informative at identifying gas (Buckley & Cottee, 2017 (IEA, 2016(IEA, , 2017Stocker, 2014).…”