Quantitative seismic analysis of a thin layer of CO2 in the Sleipner injection plume

Williams, Gareth; Chadwick, Andrew. 2012 Quantitative seismic analysis of a thin layer of CO2 in the Sleipner injection plume. Geophysics, 77 (6). R245-R256. https://doi.org/10.1190/geo2011-0449.1

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Abstract/Summary

Time-lapse seismic reflection data have proved to be the key monitoring tool at the Sleipner CO2 injection project. Thin layers of CO2 in the Sleipner injection plume show striking reflectivity on the time-lapse data, but the derivation of accurate layer properties, such as thickness and velocity, remains very challenging. This is because the rock physics properties are not well-constrained nor are CO2 distributions on a small scale. However, because the reflectivity is dominantly composed of interference wavelets from thin-layer tuning, the amplitude and frequency content of the wavelets can be diagnostic of their temporal thickness. A spectral decomposition algorithm based on the smoothed pseudo Wigner-Ville distribution has been developed. This enables single frequency slices to be extracted with sufficient frequency and temporal resolution to provide diagnostic spectral information on individual CO2 layers. The topmost layer of CO2 in the plume is particularly suitable for this type of analysis because it is not affected by attenuation from overlying CO2 layers and because there are areas in which it is temporally isolated from deeper layers. Initial application of the algorithm to the topmost layer shows strong evidence of thin-layer tuning effects. Analysis of tuning frequencies on high-resolution 2D data suggests that layer two-way temporal thicknesses in the range 6 to 11 ms can be derived with an accuracy of c. 2 ms. Direct measurements of reflectivity from the top and the base of the layer permit calculation of layer velocity, with values of around 1470 ms−1, in reasonable agreement with existing rock physics estimates. The frequency analysis can, therefore, provide diagnostic information on layer thicknesses in the range of 4 to 8 ms. The method is currently being extended to the full 3D time-lapse data sets at Sleipner.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1190/geo2011-0449.1
Programmes:	BGS Programmes 2010 > Energy Science
ISSN:	0016-8033
Date made live:	07 Mar 2013 09:05 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/500281

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1190/geo2011-0449.1

Programmes:

BGS Programmes 2010 > Energy Science

ISSN:

0016-8033

Date made live:

07 Mar 2013 09:05 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/500281