Written by: Ehsan Zabihi Naeini and Mark Sams
Broadband re-processed seismic data from the NW Shelf of Australia were inverted using a standard approach to wavelet estimation. The inversion method applied was a facies-based deterministic inversion where the low frequency model is a product of the inversion process itself, constrained by facies dependent input trends, the resultant facies distribution and the match to the seismic. The results identified the presence of a gas reservoir that had recently been confirmed through drilling. The reservoir is thin, with up to 15 ms of maximum thickness.
The bandwidth of the seismic data is approximately 5-70 Hz and only a short well log was availabe to extract the wavelets. As such there was little control on the lowest frequencies of the wavelet. Wavelets were then estimated using a variety of new techniques that attempt to address the limitations of short well-log segments and low frequency seismic. The revised inversion produced similar results but showed greater continuity and an extension of the reservoir at one flank. These differences could be traced back to the low frequency component of the inversion results and suggest that subtle variations in the low frequency component of wavelets can have an impact on seismic reservoir characterisation of thin beds.
Introduction
The conventionally acquired Willem 3D seismic survey in the Carnarvon Basin of the North West Shelf of Australia was reprocessed to achieve a broader bandwidth by applying de-ghosting algorithms (Sams et al., 2016). The seismic were then inverted using a facies based inversion technology (Kemper and Gunning, 2014). One objective of the inversion was to explore the then recently discovered gas sand at the Pyxis-1 well. The inversion predicted the presence of a thin gas sand (approximately 60 ft. thick) within the Upper Jurassic, consistent with the reports from Woodside Petroleum. Despite this success, it was recognised at the time that the estimated wavelet might not be completely compatible with the seismic data given that the well data used for the inversion was only available over 400 ms and the bandwidth of the seismic was approximately 5-70 Hz. Uncertainties or errors in the representation of the lowest frequencies within the seismic data due to the lack of constraints provided by conventional wavelet estimation from limited well data might impact the detailed characterisation of the reservoir. The objective of the current study is to observe the differences in the estimated gas sand distribution of the Pyxis discovery for a range of wavelets derived with and without broadband considerations. We also show some synthetic scenarios to further assist in understanding the impact of wavelets on inversion for thin bed detection and characterisation.
