Gonzalez_edit.qxp 28/10/08 2:33 pm Page 89
An Emerging Trend – Reservoir Characterisation Using Seismic Inversion and Multipoint Geostatistics
Figure 3: Schematic Representation of the Inversion Step When Visiting Figure 4: Detailed Representation of the Procedure to Obtain the Best
the Seismic Trace at the Well Location (First Surface Location Visited) Elastic Properties When Visiting the Trace at the Well Location
The synthetic seismic profile shown in Figure 6 was computed using
a 15Hz Ricker wavelet. Consequently, the approximate mean
wavelengths for the channel sand and background shale were 210
Multiple realisations of compressional velocity (Vp) and density (ρ) (conditional rock physics) for each
and 140m, respectively. We intentionally selected a wavelet with
MSIMPAT simulated lithofacies pseudo-log and selecting the one that best matches the collocated seismic
trace. At the well location, the values from the logs are directly accepted.
low central frequency in order to show the value of our technique
in situations where it is difficult to define sub-resolution geological different from the one used to create the true model for the
features (channels in this case) directly from the analysis of inversion. Although in the selected cross-sections the channels were
seismic amplitudes. a good representation of channel shapes in the true model, their
spatial arrangements were different. The values of the true model
The training image used as input was constructed by extracting 12 (lithofacies, Vp and ρ) at common depth points (CDPs) 40 and 120m
cross-sections from the Stanford VI synthetic reservoir, parallel to but were used as well-logs for the inversion. Conditional rock physics
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