1887
image of Adaptive scaling for an enhanced dynamic interpretation of 4D seismic data

Abstract

ABSTRACT

In this study, importance is drawn to the role of engineering principles when interpreting dynamic reservoir changes from 4D seismic data. In particular, it is found that in clastic reservoirs the principal parameters controlling mapped 4D signatures are not the pressure and saturation changes per se but these changes scaled by the corresponding thickness (or pore volume) of the reservoir volume that these effects occupy. For this reason, pressure and saturation changes cannot strictly be recovered by themselves, this being true for all data interpretation. This understanding is validated both with numerical modelling and analytic calculation. Interestingly, the study also indicates that the impact of gas saturation on the seismic can be written using a linear term but that inversion for gas saturation can yield at best only the total thickness/pore volume of the distribution. The above provides a basis for a linear equation that can readily and accurately be used to estimate pressure and saturation changes. Quantitative updates of the static and dynamic components of the simulation model can be achieved by comparing thickness or pore volume‐scaled changes from the simulator with the corresponding quantities on the inverted observations.

Loading

Article metrics loading...

/content/journals/10.1111/1365-2478.12005
2013-02-27
2024-04-18
Loading full text...

Full text loading...

References

  1. AliA., TaggartI., MeeB., SmithM., GerhardtA. and BourdonL.2008. Integrating 4D seismic data with production related effects at Enfield, North West Shelf, Australia. SPE 116916.
  2. AlsosT., OsdalB. and HøiåsA.2009. The Many Faces of Pressure Changes in 4D Seismic at the Svale Field and Its Implication on Reservoir Management. 71th EAGE Conference & Exhibition, Vienna , Austria .
  3. AlvarezE. and MacBethC.2012. An insightful parameterisation for the flatlander's interpretation of time‐lapsed seismic data. 74th EAGE Conference & Exhibition, Copenhagen , Denmark .
  4. AminiH., MacBethC., and ShamsA., 2011, Calibration of Simulator to Seismic Modelling for Quantitative 4D Seismic Interpretation. 73rd EAGE Conference & Exhibition incorporating SPE EUROPEC, Vienna , Austria .
  5. ClarkN.J.1969. Elements of Petroleum Reservoirs , Society of Petroleum Engineers, H.L.Doherty Series. ISBN 0‐89520‐209‐3
    [Google Scholar]
  6. DakeL. P.2002. Fundamental of Reservoir Engineering, Nineteenth impression . Elsevier Science B. V., Amsterdam , The Netherlands .
    [Google Scholar]
  7. DomenicoS. N.1974. Effect of water saturation on seismic reflectivity of sand reservoirs encased in shale. Geophysics 39–6.
    [Google Scholar]
  8. FalahatR., ShamsA. and MacBethC.2011. Towards quantitative evaluation of gas injection using time‐lapse seismic data. Geophysical Prospecting 59, 310–322.
    [Google Scholar]
  9. FletcherJ.2004. Rock and fluid physics understanding the impact of pressure changes. SPE/EAGE Joint Workshop ‘What Do Petroleum Engineers Expect from Time Lapse Seismic, and Do Geophysicists Answer The Right Questions?’ 23–25 March, Copenhagen , Denmark .
  10. FloricichM., MacBethC., StammeijerJ., StaplesR., EvansA. and DijksmanC.2006. A New Technique for Pressure – Saturation Separation from Time‐Lapse Seismic. Schiehallion Case Study, 68th EAGE Conference & Exhibition, Vienna , Austria .
  11. GarciaA. and MacBethC.2011. Estimation of effective stress changes in the reservoir from 4D seismic data. Geophysical Prospecting , In press.
    [Google Scholar]
  12. GhaderiA. and LandrøM.2009. Estimation of thickness and velocity changes of injected carbon dioxide layers from prestack seismic data. Geophysics 74, 17–28.
    [Google Scholar]
  13. HaleD.2007. A method for estimating apparent displacement vectors from time lapse seismic images. Centre for Wave Phenomena Report 566.
  14. HuangY., MacBethC., BarkvedO. and van GestelJ‐P.2011. Enhancing dynamic interpretation at the Valhall Field by correlating well activity to 4D seismic signatures. First Break 29, March Issue.
    [Google Scholar]
  15. LandrøM.2001. Discrimination between pressure and fluid saturation changes from time‐lapse seismic data. Geophysics 66, 836–844.
    [Google Scholar]
  16. MacBethC.2004. A classification for the pressure‐sensitivity properties of a sandstone rock frame. Geophysics 69, 497–510.
    [Google Scholar]
  17. MacBethC., SoldoJ., FloricichM.2004. Going quantitative with 4D seismic. 74th Annual International Meeting, Society of Exploration Geophysicists, Expanded Abstracts, 2283–2286.
  18. MartinK. and MacdonaldC.2010. Schiehallion Field: Applying a Geobody Modelling Approach to Piece Together a Complex Turbidite Reservoir. 7th European Production & Development Conference, Aberdeen , UK .
    [Google Scholar]
  19. StaplesR., CookA., BraisbyJ., HodgsonB. and MabillardA.2006. Integration of 4D seismic data and the dynamic reservoir model reveal new targets in Gannet C. The Leading Edge , 1126–1133.
    [Google Scholar]
  20. StephenK. D. and MacBethC.2008. Reducing reservoir prediction uncertainty by updating a stochastic model using seismic history matching. SPE Journal, December, 991–999.
  21. TuraA. and LumleyD. E.1999. Estimating pressure and saturation changes from time‐lapse AVO data. 69th Annual International Meeting, Society of Exploration Geophysicists, Expanded Abstracts, 1655–1658.
http://instance.metastore.ingenta.com/content/journals/10.1111/1365-2478.12005
Loading
/content/journals/10.1111/1365-2478.12005
Loading

Data & Media loading...

  • Article Type: Research Article
Keywords: 4D signatures ; Gas saturation ; Quantitative interpretation
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error