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Estimating gas saturation in a thin layer by using frequency-dependent amplitude versus offset modellingNormal access

Authors: Zhaoyu Jin, Mark Chapman, Xiaoyang Wu and Giorgos Papageorgiou
Journal name: Geophysical Prospecting
Issue: Vol 65, No 3, May 2017 pp. 747 - 765
DOI: 10.1111/1365-2478.12437
Organisations: Wiley
Language: English
Info: Article, PDF ( 21.66Mb )

Various models have been proposed to link partial gas saturation to seismic attenuation and dispersion, suggesting that the reflection coefficient should be frequencydependent in many cases of practical importance. Previous approaches to studying this phenomenon typically have been limited to single-interface models. Here, we propose a modelling technique that allows us to incorporate frequency-dependent reflectivity into convolutional modelling. With this modelling framework, seismic data can be synthesised from well logs of velocity, density, porosity, and water saturation. This forward modelling could act as a basis for inversion schemes aimed at recovering gas saturation variations with depth. We present a Bayesian inversion scheme for a simple thin-layer case and a particular rock physics model and show that, although the method is very sensitive to prior information and constraints, both gas saturation and layer thickness theoretically can be estimated in the case of interfering reflections.

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