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Pressure and saturation estimation from 4D seismic constrained by reservoir flow simulation *Alessandra Davolio Célio Maschio.

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Presentation on theme: "Pressure and saturation estimation from 4D seismic constrained by reservoir flow simulation *Alessandra Davolio Célio Maschio."— Presentation transcript:

1 Pressure and saturation estimation from 4D seismic constrained by reservoir flow simulation *Alessandra Davolio Célio Maschio Denis Schiozer Summer Research Workshop 2012 SEG/SPE/AAPG

2 Objective Main research: development of methodology to integrate reservoir simulation and 4D seismic data in a quantitative way. This work: estimation of pressure and saturation variations from 4D seismic data constrained by flux conditions.

3 Main idea of the methodology 4D seismic Optimization Pre Sw Constraints S min < S w < S max P min < Pre < P max Reservoir simulation Uncertainty analysis Model 1Model nModel 2 … PreSwPreSw PreSw

4 Inversion procedure Usual constraints S wc < S w < 1-S or Pre b < Pre < Pre over Constraints from multiple simulations S min < S w < S max Pre min < Pre < Pre max

5 Methodology: multiple models For each grid block: minimum (lower among all simulations) and maximum (higher among all simulations) values

6 Problem Statement (building a synthetic data set to test the methodology) Reference reservoir model P,S maps Inversion Algorithms Inverted P,S maps Base model P,S maps PEM “Base” seismic attributes Multiple realizations P,S min & max values PEM “Reference” seismic attributes Inverted P,S maps (calibrated) Simplification: no scale differences between seismic and simulation data!

7 Assumptions Seismic is at simulation scale Water injection case  above bubble point pressure (no presence of gas) PEM – unconsolidated sand model + Gassman equations

8 8 Application: case studied Uncertainties  Porosity and permeability fields Geostatistical realizations  Faults transmissibility  Relative permeability  Kz/Kx Example: geostatistical realizations of porosity (left) and permeability (right) 400 models

9 9 Synthetic seismic 4D difference (without noise) P impedance S impedance

10 10 Synthetic seismic 4D difference (with random noise) P impedance S impedance

11 Application First case Inversion is run using usual constraints. Second case Inversion constrained by min and max extracted from 400 models simulations. Third case Inversion constrained by min and max extracted from some selected models simulations. Selection based on well pressure data.

12 12 Application: production data to select the best models 2nd case 3rd case

13 13 Expected Results

14 14 Constraints S wc < S w < 1-S or P b < Pre < P over Inversion results Errors (estimated – true answer) Results – First case

15 15 Results – Second case Inversion results Errors (estimated – true answer)

16 16 Results – Third case Inversion results Errors (estimated – true answer)

17 Increases number of blocks with low error Reduces number of blocks with high error Results

18 18 Conclusion It was presented a methodology that uses uncertainty analysis with reservoir simulation to constrain the estimation of dynamic properties from 4D seismic  Necessary due to problems related do 4DS (noise, resolution, scale, …)  More iterations may be necessary so each technique can constrain the other Well data (pressure) was used to improve the constraint applied to the inversion Promising results, specially in the estimation of water saturation variation Next step: to use seismic information in a probabilistic approach.

19 Acknowledgments UNISIM-UNICAMP

20 Thank you! *Alessandra Davolio Célio Maschio Denis Schiozer Summer Research Workshop 2012 SEG/SPE/AAPG


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