Technical article: Mapping reservoir pressure and saturation changes using seismic methods - possibilities and limitations

doi:10.1046/j.1365-2397.2001.00226.x

Cited by 59 publications

(1 citation statement)

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“…Different authors have demonstrated the added value of using time-lapse differences in arrival times to map, interpret, and estimate changes in reservoir properties. Landrø et al (2001) notices a good correlation between overpressured areas and an increase in arrival times (push-down); the time-shift analysis also gave information about the vertical distribution of the production-related changes within the reservoir. Landrø (2002) proposes a way to express changes in fluid properties as a weighted linear combination of the estimation coming from changes in AVO coefficients and from changes in P-and S-waves traveltimes.…”

Section: Introductionmentioning

confidence: 86%

Estimation of changes in saturation and pressure from 4D seismic AVO and time-shift analysis

et al. 2011

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A reliable estimate of reservoir pressure and fluid saturation changes from time-lapse seismic data is difficult to obtain. Existing methods generally suffer from leakage between the estimated parameters. We propose a new method using different combinations of time-lapse seismic attributes based on four equations: two expressing changes in prestack AVO attributes (zero-offset and gradient reflectivities), and two expressing poststack time-shifts of compressional and shear waves as functions of production-induced changes in fluid properties. The effect of using different approximations of these equations was tested on a realistic, synthetic reservoir, where seismic data have been simulated during the 30-year lifetime of a water-flooded oil reservoir. Results found the importance of the porosity in the inversion with a clear attenuation of the porosity imprint on the final estimates in case the porosity field or the vertically averaged porosity field is known a priori. The use of a first-order approximation of the gradient reflectivity equation leads to severely biased estimates of changes in saturation and leakage between the two different parameters. Both the bias and the leakage can be reduced, if not eliminated, by including higher-order terms in the description of the gradient, or by replacing the gradient equation with P-and/or S-wave time-shift data. The final estimates are relatively robust to random noise, as they present fairly high accuracy in the presence of white noise with a standard deviation of 15%. The introduction of systematic noise decreases the inversion accuracy more severely.

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Section: Introductionmentioning

confidence: 86%