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Use of PP and PS time-lapse stacks for fluid-pressure discrimination. ALEXEY STOVAS 1, MARTIN LANDRØ 1 & BØRGE ARNTSEN 2 1 NTNU, Dept. of Petroleum Engineering and Applied Geophysics, Trondheim, Norway 2 Statoil R&D centre, Trondheim, Norway 2 Statoil R&D centre, Trondheim, Norway

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Outline Change in PP and PS reflectivity due to change in pressure and saturation (reflection pattern) Pressure-saturation discrimination and uncertainties Application on the Gullfaks synthetic data set Conclusions Acknowledgments

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Method Methodology (Stovas & Landrø, 2002a,b) Water saturation model (Gassmann, 1951) Pressure model (Mindlin, 1949) Reflection coefficients (Ursin & Stovas, 2002) The Gullfaks synthetic data set (Arntsen, 2002)

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Gassmann and Hertz-Mindlin models give Reflectivity versus saturation and pressure (1)

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Reflection coefficients versus incident angle Reflectivity versus saturation and pressure (2)

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Stacked reflection coefficients versus opening angle ( Q ) Reflectivity versus saturation and pressure (3)

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Basic principle (1) We establish relationship between the change in the PP and PS stack amplitudes and the change in water saturation and pressure We establish relationship between the change in the PP and PS stack amplitudes and the change in water saturation and pressure where operator maps the input vector of the change in saturation and pressure into the output vector of the change in the stacks amplitudes

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Mapping

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Opening angle (ray tracing)

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Basic principle (2) The procedure: The procedure: Compute elastic parameters Compute PP&PS reflection coefficients Evaluate min/max opening angle Compute stacked PP&PS reflection coefficients Build up the reflection patterns Compute PP&PS calibration factors Compute the difference PP&PS stacks Place amplitudes into corresponding reflection patterns

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Uncertainties in saturation&pressure from uncertainties in PP&PS stacked amplitudes a = discrimination angle

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Weighting factors for uncertainties

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Gullfaks synthetic data Data set includes: 8 types of reservoir rock (Tarbert and Ness formations) overlaid by shale (Shetland formation) 3 time-lapse models with PP and PS seismic data Saturation-pressure condition is known for Model I and has to be predicted for Model II and Model III

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P-wave Gullfaks model Time, ms Distance, m Oil water contact Top reservoir

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Reservoir rock physics parameters

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P- and S-wave velocities for reservoir rock SM1

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Isolines for reflectivity changes for the interface Shetland/SM1

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PP&PS stacks for Gullfaks Model I

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PP&PS stacks for Gullfaks Model II

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PP&PS stacks for Gullfaks Model III

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Saturation-pressure prediction for reservoir rock SM1

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Seismic amplitudes and saturation-pressure uncertainties

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Weighting factors for uncertainties

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Uncertainties vs. opening angle (water saturation)

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Uncertainties vs. opening angle (gas saturation)

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Conclusions Method of fluid-pressure discrimination from PP and PS stacks is developed Method is applied on synthetic data set from Gullfaks model which consists of three time-lapse situations. The results of water saturation and pressure prediction are very close to the modelled data (2-3% error in average). The analysis of weighting factors for uncertainties in water saturation and pressure shows that for all reservoir rocks representing Gullfaks Field the relative uncertainties in saturation are bigger than the corresponding uncertainties in pressure.

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Acknowledgments We want to acknowledge the financial support from the EC project ENK6-CT-2000-00108, ATLASS and Statoil.

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