Time-lapse tomographic inversion using a Gaussian parameterization of the velocity changes

Abstract

Most seismic studies of changes in traveltimes are of a qualitative nature and a major challenge in four dimensions is to use the information contained in time shifts to quantify the nature of velocity changes in the subsurface layers. We propose a 4D tomographic inversion method that uses time shifts from prestack seismic data to estimate parameters describing the 2D velocity field after changes have occurred. Prestack data allow for the usage of many offsets, thus increasing the information input for the inversion. The velocity changes are parameterized by a chosen number of Gaussian functions in two dimensions and weighted least-squares inversion is used to estimate the parameters describing these functions. We have found that the parameters describing the position and shape of the Gaussian velocity anomalies can be estimated with this method for simple synthetic cases. For more complex cases with overlapping Gaussian functions, resolution of the parameters can be difficult and in these cases our recommendation is to find the best fit for a simple smooth anomaly to a more complex real world. The method is tested on a real data set from a [Formula: see text] injection project above the Sleipner field in the North Sea, where quantification of changes is important for monitoring purposes. We have found that the noise levels in prestack traveltime data are on the high side for large-scale analysis; however, we estimate reasonable [Formula: see text] layer thickness and velocity compared to previous work in a nearby area.

Dual sensor streamer technology used in Sleipner CO2 injection monitoring

“…In addition we will compare image qualities between the dual sensor streamer and conventional data. Several authors have made estimations of the CO 2 thickness from the conventional seismic data based on a variety of inversion and pre-stack analysis methods of amplitude and time shifts (Ghaderi and Landrø 2009;Queisser and Singh 2010;Evensen and Landrø 2010;Delépine et al 2011;Velis and Rubino 2011;White, Williams and Chadwick 2012;Williams and Chadwick 2012). We show how the improved resolution of the dual sensor streamer data results in improved thickness estimates for the uppermost CO 2 -filled layer in the Utsira Fm at Sleipner, and compare to estimates from the literature.…”

“…* E-mail: akafu@statoil.com 1 PGS GeoStreamer CO 2 is injected into the Utsira Fm, a saline aquifer at 800-1100 m depth below sea surface. Several authors have made estimations of the CO 2 thickness from the conventional seismic data based on a variety of inversion and pre-stack analysis methods of amplitude and time shifts (Ghaderi and Landrø 2009;Queisser and Singh 2010;Evensen and Landrø 2010;Delépine et al 2011;Velis and Rubino 2011;White, Williams and Chadwick 2012;Williams and Chadwick 2012). Repeated seismic surveys were acquired in 1999, 2001, 2002, 2004, 2006, 2008 and 2010, to monitor the CO 2 .…”

Third‐order elasticity of transversely isotropic field shales

“…This illustrates the importance of comparing 4D attributes within the same context, that is whether it is pre‐stack or post‐stack data. Even though post‐stack analysis of 4D data in many cases gives substantial insight into production‐induced events, pre‐stack analysis may disclose details that would be difficult to observe in stacked data (Dvorak et al., 2018; Evensen & Landrø, 2010; Røste et al., 2007; Shragge & Lumley, 2013).…”

Estimating saturation and density changes caused by CO2 injection at Sleipner — Using time-lapse seismic amplitude-variation-with-offset and time-lapse gravity

“…They clearly show the potential for using amplitude information to distinguish between acoustic impedance and density at Sleipner. Evensen and Landrø (2010) use a time-lapse tomographic inversion method and seismic data sets from 1994 and 2001 to estimate the P-wave velocity in a thin CO 2 layer.…”