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Forensic mapping of seismic velocity heterogeneity in a CO2 layer at the Sleipner CO2 storage operation, North Sea, using time-lapse seismics

Chadwick, R.A.; Williams, G.A.; Falcon Suarez, I.. 2019 Forensic mapping of seismic velocity heterogeneity in a CO2 layer at the Sleipner CO2 storage operation, North Sea, using time-lapse seismics. International Journal of Greenhouse Gas Control, 90, 102793. https://doi.org/10.1016/j.ijggc.2019.102793

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Abstract/Summary

CO2 separated from natural gas produced at the Sleipner and Gudrun fields is being injected into the Utsira Sand, with around 18 million tons currently stored. Time-lapse 3D seismics have been deployed to monitor development of the CO2 plume. The 2010 seismic survey resolved, for the first time in 3D, the topmost CO2 layer into distinct reflections from its top and base. Seismic velocity is diagnostic of CO2 layer properties and a forensic interpretative approach is adopted to determine spatial velocity variation in the topmost CO2 layer. Velocity is obtained by equating absolute layer thickness, derived by subtracting a constructed flat CO2 – water contact from the topographical relief of the reservoir top, to the temporal separation of the layer top and base reflections, with appropriate correction for wavelet interference effects. Layer velocities show a systematic and robust spatial variation between a northern area with a mean velocity of 1371 ± 122 ms−1 and a central area with a much higher mean velocity of 1638 ± 103 ms−1. Recent fluid flow simulations of the topmost CO2 layer have shown that incorporating a high permeability channel in the model reservoir significantly improves the history-match. This high permeability channel corresponds remarkably closely to the low seismic velocities mapped in the northern area, with higher layer velocities of the central area interpreted as more argillaceous, less permeable overbank deposits. The new velocity analysis therefore provides independent support for including deterministic permeability heterogeneity in predictive fluid flow modelling of Sleipner.

Item Type: Publication - Article
Digital Object Identifier (DOI): https://doi.org/10.1016/j.ijggc.2019.102793
ISSN: 17505836
Date made live: 14 Aug 2019 14:26 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/524756

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