SEG Technical Program Expanded Abstracts 2006 2006
DOI: 10.1190/1.2370196
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Determination of a seismic and engineering consistent petro‐elastic model for time‐lapse seismic studies: Application to the Schiehallion Field

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Cited by 7 publications
(3 citation statements)
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“…A multi-attribute time-lapse inversion approach is used to determine simulated saturation changes in the reservoir (Floricich et al, 2006). For this method, production data from three wells are used to calibrate each time-lapse attribute.…”
Section: Saturation Estimationmentioning
confidence: 99%
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“…A multi-attribute time-lapse inversion approach is used to determine simulated saturation changes in the reservoir (Floricich et al, 2006). For this method, production data from three wells are used to calibrate each time-lapse attribute.…”
Section: Saturation Estimationmentioning
confidence: 99%
“…The above studies re-affirm that time-lapse attributes can be affected not only by production changes in the reservoir but also by overburden complexity. However, time-lapse pressure and saturation inversion schemes such as the one presented by Floricich et al (2006) depend on attributes which are assumed to represent changes driven solely by reservoir production. Thus, there is a need to explore the interaction between the acquisition and overburden, and how this ultimately affects the estimation of reservoir state.…”
Section: Introductionmentioning
confidence: 99%
“…This again does not reveal the role of the petroelastic model sufficiently but does highlight that for most reservoirs under production and recovery, a linear relation in pore pressure and water saturation change may suffice for inversion purposes. Both of the above approaches have been used to invert for pressure and saturation changes from time-lapsed seismic data with some degree of success (Landrø 2001;Floricich et al 2006). Unfortunately, neither of the techniques can readily identify how the petroelastic model parameters manifest themselves in mapped 4D seismic signatures, this understanding would require extensive sensitivity tests using forward modelling.…”
Section: Introductionmentioning
confidence: 99%