1887
Volume 64, Issue 1
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Pressure drops associated with reservoir production generate excess stress and strain that cause travel‐time shifts of reflected waves. Here, we invert time shifts of P‐, S‐, and PS‐waves measured between baseline and monitor surveys for pressure reduction and reservoir length. The inversion results can be used to estimate compaction‐induced stress and strain changes around the reservoir. We implement a hybrid inversion algorithm that incorporates elements of gradient, global/genetic, and nearest neighbour methods and permits exploration of the parameter space while simultaneously following local misfit gradients. Our synthetic examples indicate that optimal estimates of reservoir pressure from P‐wave data can be obtained using the reflections from the reservoir top. For S‐waves, time shifts from the top of the reservoir can be accurately inverted for pressure if the noise level is low. However, if noise contamination is significant, it is preferable to use S‐wave data (or combined shifts of all three modes) from reflectors beneath the reservoir. Joint wave type inversions demonstrate improvements over any single pure mode. Reservoir length can be estimated using the time shifts of any mode from the reservoir top or deeper reflectors. We also evaluate the differences between the actual strain field and those corresponding to the best‐case inversion results obtained using P‐ and S‐wave data. Another series of tests addresses the inversion of the time shifts for the pressure drops in two‐compartment reservoirs, as well as for the associated strain field. Numerical testing shows that a potentially serious source of error in the inversion is a distortion in the strain‐sensitivity coefficients, which govern the magnitude of stiffness changes. This feasibility study suggests which wave types and reflector locations may provide the most accurate estimates of reservoir parameters from compaction‐induced time shifts.

Loading

Article metrics loading...

/content/journals/10.1111/1365-2478.12253
2015-12-15
2024-03-28
Loading full text...

Full text loading...

References

  1. AsterR.C., BorchersB. and ThurberC.2005. Parameter Estimation and Inverse Problems. Academic Press.
  2. BatzleM. and HanD.2009. Rock and fluid properties: seismic rock physics. SEG Continuing Education Series, Denver Geophysical Society.
    [Google Scholar]
  3. CalvertR.2005. Insights and Methods for 4D Reservoir Monitoring and Characterization. Distinguished Instructor Short Course, Society of Exploration Geophysicists.
    [Google Scholar]
  4. COMSOL AB2008. COMSOL Multiphysics.
  5. De GennaroS., OnaisiA., GrandiA., Ben‐BrahimL. and NeilloV.2008. 4D reservoir geomechanics: a case study from the HP/HT reservoirs of the Elgin and Franklin fields. First Break26, 53–59.
    [Google Scholar]
  6. DownsJ. and FauxD.A.1995. Calculation of strain distributions in multiple‐quantum‐well strained‐layer structures. Journal of Applied Physics77, 2444–2447.
    [Google Scholar]
  7. FuckR.F., BakulinA. and TsvankinI.2009. Theory of traveltime shifts around compacting reservoirs: 3D solutions for heterogeneous anisotropic media. Geophysics74, D25–D36.
    [Google Scholar]
  8. FuckR.F., TsvankinI. and BakulinA.2011. Influence of background heterogeneity on traveltime shifts for compacting reservoirs. Geophysical Prospecting59, 78–89.
    [Google Scholar]
  9. GeertsmaJ.1973. Land subsidence above compacting oil and gas reservoirs. Journal of Petroleum TechnologySPE3730, 734–744.
    [Google Scholar]
  10. GreavesR.J. and FulpT.J.1987. Three‐dimensional seismic monitoring of an enhanced oil recovery process. Geophysics52, 1175–1187.
    [Google Scholar]
  11. GubbinsD.2004. Time Series Analysis and Inverse Theory for Geophysicists. Cambridge University Press, London, UK.
    [Google Scholar]
  12. HatchellP. and BourneS., 2005. Rocks under strain: strain‐induced time‐lapse time shifts are observed for depleting reservoirs. The Leading Edge24, 1222–1225.
    [Google Scholar]
  13. HearmonR.1953. ‘Third‐Order’ elastic coefficients. Acta Crystallographica6, 331–340.
    [Google Scholar]
  14. HerwangerJ.2008. R we there yet? 70th EAGE annual international meeting, Expanded Abstracts, n. 4038.
  15. HodgsonN., MacBethC., DurantiL., RickettJ. and NiheiK.2007. Inverting for reservoir pressure change using time‐lapse time strain: application to Genesis field, Gulf of Mexico. The Leading Edge26, 649‐652.
    [Google Scholar]
  16. HornbyB.E.1996. Experimental investigation of effective stress principles for sedimentary rocks. SEG Technical Program Expanded Abstracts, 1707–1710.
  17. HuS.M.1989. Stress from a parallelepipedic thermal inclusion in a semispace. Journal of Applied Physics66, 2741–2743.
    [Google Scholar]
  18. JanssenA.L., SmithB.A. and ByerleyG.W.2006. Measuring velocity sensitivity to production‐induced strain at the Ekofisk field using time‐lapse time‐shifts and compaction logs. SEG Technical Program Expanded Abstracts, 3200–3204.
  19. LandrøM.2001. Discrimination between pressure and fluid saturation changes from time lapse data. Geophysics66, 836–844.
    [Google Scholar]
  20. LumleyD.2001. Time‐lapse seismic reservoir monitoring. Geophysics66, 50–53.
    [Google Scholar]
  21. MacBethC.2004. A classification for the pressure‐sensitivity properties of a sandstone rock frame. Geophysics69, 497–510.
    [Google Scholar]
  22. MacBethC., FloricichM. and SoldoJ.2006. Going quantitative with 4D seismic analysis. Geophysical Prospecting54, 303–317.
    [Google Scholar]
  23. MagnesanM., DepagneS., NixonK., RegelB., OpichJ., RogersG.et al. 2005. Seismic processing for time‐lapse study: Genesis field, Gulf of Mexico. The Leading Edge24, 364–373.
    [Google Scholar]
  24. McCannG.D. and WiltsC.H.1951. A mathematical analysis of the subsidence in the Long Beach‐San Pedro area. California Institute of Technology.
  25. MindlinR.D. and ChengD.H.1950. Nuclei of strain in the semi‐infinite solid. Journal of Applied Physics21, 926–930.
    [Google Scholar]
  26. RickettJ., DurantiL., HudsonT., RegelB. and HodgsonN.2007. 4D time strain and the seismic signature of geomechanical compaction at Genesis. The Leading Edge26, 644.
    [Google Scholar]
  27. RickettJ. and LumleyD.1998. A cross‐equalization processing flow for off‐the‐shelf 4D seismic data. SEG Technical Program Expanded Abstracts 17.
  28. RickettJ. and LumleyD.2001. Cross‐equalization data processing for time‐lapse seismic reservoir monitoring: a case study from the Gulf of Mexico. Geophysics66, 1015–1025, doi:10.1190/1.1487049.
    [Google Scholar]
  29. RosteT.2007. Monitoring overburden and reservoir changes from prestack time‐lapse seismic data ‐ applications to chalk fields. PhD thesis, Norwegian University of Science and Technology, Norway.
  30. SambridgeM.1999. Geophysical inversion with a neighbourhood algorithm ‐ I. searching a parameter space. Geophysical Journal International138, 479–494.
    [Google Scholar]
  31. SarkarD., BakulinA. and KranzR.L.2003. Anisotropic inversion of seismic data for stressed media: theory and a physical modeling study on Berea sandstone. Geophysics68, 690–704.
    [Google Scholar]
  32. SavaP., YanJ. and GodwinJ.2010. SFEWE elastic finite difference wave‐propagation development code for the Madagascar seismic software collection. http://www.reproducability.org.
  33. SayersC.M.2010. Geophysics Under Stress: Geomechanical Applications of Seismic and Borehole Acoustic Waves. Distinguished Instructor Short Course, Society of Exploration Geophysicists, n. 13.
    [Google Scholar]
  34. SayersC.M. and SchutjensP.M.2007. An introduction to reservoir geomechanics. The Leading Edge26, 597–601.
    [Google Scholar]
  35. SchutjensP.M.T.M., HanssenT.H., HettemaM.H.H., MerourJ., de BreeP., CoremansJ.W.A.et al. 2004. Compaction‐induced porosity/permeability reduction in sandstone reservoirs: data and model for elasticity‐dominated deformation. SPE Reservoir Evaluation & EngineeringSPE 88441, 202–216.
    [Google Scholar]
  36. SenM.K. and StoffaP.L.1995. Global optimization methods in geophysical inversion. In: Advances in Exploration Geophysics, Vol. 4. Elsevier Science.
    [Google Scholar]
  37. SmithS. and TsvankinI.2012. Modeling and analysis of compaction‐induced traveltime shifts for multicomponent seismic data. Geophysics77, T221–T237.
    [Google Scholar]
  38. SmithS. and TsvankinI.2013. Sensitivity of compaction‐induced multicomponent seismic time shifts to variations in reservoir properties. Geophysics78, T151–T163. doi: 10.1190/geo2012‐0361.1
    [Google Scholar]
  39. StaplesR., ItaJ., BurrelR. and NashR.2007. Monitoring pressure depletion and improving geomechanical models of the Shearwater field using 4D seismic. The Leading Edge26, 636–642.
    [Google Scholar]
  40. ThurstonR.N. and BruggerK.1964. Third‐order elastic constants and the velocity of small amplitude elastic waves in homogeneously stressed media. Physical Review133, A1604–A1610.
    [Google Scholar]
  41. TsvankinI.2005. Seismic Signatures and Analysis of Reflection Data in Anisotropic Media, 2nd edn. Elsevier Science.
    [Google Scholar]
  42. TuraA., BarkerT., CattermoleP., CollinsC., DavisJ., HatchellP., et al. 2005. Monitoring primary depletion reservoirs using amplitudes and time shifts from high‐repeat surveys. The Leading Edge24, 1214–1221.
    [Google Scholar]
  43. WikelK.R.2008. Three‐dimensional geomechanical modeling of a tight gas reservoir, Rulison Field, Colorado. MS thesis, Colorado School of Mines, USA.
  44. YaleD.P. and JamiesonW.H.1994. Static and dynamic mechanical properties of carbonates. In: Rock Mechanics, Models, and Measurements Challenges from Industry, Proceedings of the 1st North American Rock Mechanics Symposium (eds P.P.Nelson and S.E.Laubach), pp. 463–471.
http://instance.metastore.ingenta.com/content/journals/10.1111/1365-2478.12253
Loading
/content/journals/10.1111/1365-2478.12253
Loading

Data & Media loading...

Most Cited This Month Most Cited RSS feed

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