1887
Volume 59, Issue 4
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

The hydrocarbon industry is moving increasingly towards tight sandstone and shale gas resources – reservoirs that require fractures to be produced economically. Therefore, techniques that can identify sets of aligned fractures are becoming more important. Fracture identification is also important in the areas of coal bed methane production, carbon capture and storage (CCS), geothermal energy, nuclear waste storage and mining. In all these settings, stress and pore pressure changes induced by engineering activity can generate or reactivate faults and fractures. P‐ and S‐waves are emitted by such microseismic events, which can be recorded on downhole geophones. The presence of aligned fracture sets generates seismic anisotropy, which can be identified by measuring the splitting of the S‐waves emitted by microseismic events. The raypaths of the S‐waves will have an arbitrary orientation, controlled by the event and geophone locations, meaning that the anisotropy system may only be partly illuminated by the available arrivals. Therefore to reliably interpret such splitting measurements it is necessary to construct models that compare splitting observations with modelled values, allowing the best fitting rock physics parameters to be determined. Commonly, splitting measurements are inverted for one fracture set and rock fabrics with a vertical axis of symmetry. In this paper we address the challenge of identifying multiple aligned fracture sets using splitting measured on microseismic events.

We analyse data from the Weyburn CCS‐EOR reservoir, which is known to have multiple fracture sets, and from a hydraulic fracture stimulation, where it is believed that only one set is present. We make splitting measurements on microseismic data recorded on downhole geophone arrays. Our inversion technique successfully discriminates between the single and multiple fracture cases and in all cases accurately identifies the strikes of fracture sets previously imaged using independent methods (borehole image logs, core samples, microseismic event locations). We also generate a synthetic example to highlight the pitfalls that can be encountered if it is assumed that only one fracture set is present when splitting data are interpreted, when in fact more than one fracture set is contributing to the anisotropy.

Loading

Article metrics loading...

/content/journals/10.1111/j.1365-2478.2010.00943.x
2011-02-14
2024-04-26
Loading full text...

Full text loading...

References

  1. AbtD.L. and FischerK.M.2008. Resolving three‐dimensional anisotropic structure with shear wave splitting tomography. Geophysical Journal International173, 859–886.
    [Google Scholar]
  2. AngusD.A., KendallJ.‐M., FisherQ.J., SeguraJ.M., SkachkovS., CrookA.J.L. and DutkoM.2010. Modelling microseismicity of a producing reservoir from coupled fluid‐flow and geomechanical simulation. Geophysical Prospecting58, 901–914.
    [Google Scholar]
  3. BakulinA., GrechkaV. and TsvankinI.2000. Estimation of fracture parameters from reflection seismic data – Part I: HTI model due to a single fracture set. Geophysics65, 1788–1802.
    [Google Scholar]
  4. BakulinA., GrechkaV. and TsvankinI.2002. Seismic inversion for the parameters of two orthogonal fracture sets in a VTI backgroound medium. Geophysics67, 292–299.
    [Google Scholar]
  5. BarruolG. and HoffmannR.1999. Upper mantle anisotropy beneath the Geoscope stations. Journal of Geophysical Research104, 10757–10774.
    [Google Scholar]
  6. BellefleurG., AdamL., WhiteD.J., MattocksB. and DavisT.L.2003. Seismic imaging and anisotropy analysis of 9C 3D‐VSP data at Weyburn Field, Saskatchewan, Canada. 73rd SEG meeting, Dallas, Texas, USA, Expanded Abstracts, 1326–1329.
  7. BellefleurG., WhiteD.J. and DavisT.L.2004. P‐wave imaging using 3D‐VSP data in VTI media, Weyburn Field, Saskatchewan Canada. 74th SEG meeting, Denver, Colorado, USA, Expanded Abstracts, 2521–2524.
  8. BlackmanD.K. and KendallJ.‐M.1997. Sensitivity of teleseismic body waves to mineral texture and melt in the mantle beneath a mid‐ocean ridge. Philosophical Transactions of the Royal Society of London A355, 217–231.
    [Google Scholar]
  9. BlackmanD.K., OrcuttJ.A., ForsythD.W. and KendallJ.‐M.1993. Seismic anisotropy in the mantle beneath an oceanic spreading center. Nature366, 675–677.
    [Google Scholar]
  10. BonessN.L. and ZobackM.D.2006. Mapping stress and structurally controlled crustal shear velocity anisotropy in California. Geology34, 825–828.
    [Google Scholar]
  11. BrownL.T.2002. Integration of rock physics and reservoir simulation for the interpretation of time‐lapse seismic data at Weyburn field, Saskatchewan . Master's thesis, Colorado School of Mines .
  12. Bunge, R.J., 2000. Midale reservoir fracture characterization using integrated well and seismic data, Weyburn field , Saskatchewan . Master's thesis, Colorado School of Mines , Golden , Colorado .
  13. CrampinS.1991. A decade of shear‐wave splitting in the Earth's crust: what does it mean? what use can we make of it? and what should we do next?Geophysical Journal International107, 387–407.
    [Google Scholar]
  14. CrampinS., GaoY. and PeacockS.2008. Stress‐forcasting (not predicting) earthquakes: A paradigm shift?Geology36, 427–430.
    [Google Scholar]
  15. CrampinS. and PeacockS.2008. A review of the current understanding of seismic shear‐wave splitting in the earth's crust and common fallacies in interpretation. Wave Motion45, 675–722.
    [Google Scholar]
  16. DavisT.L., TerrellM.‐J., BensonR.D., CardonaR., KendallR.R. and WinarskyR.2007. Multicomponent seismic characterization and monitoring of the CO2 flood at Weyburn Field, Saskatchewan. The Leading Edge22, 696–697.
    [Google Scholar]
  17. De MeersmanK., KendallJ.‐M. and Van der BaanM.2009. The 1998 Valhall microseismic data set: An integrated study of relocated sources, seismic multiplets and S‐wave splitting. Geophysics74, B183–B195.
    [Google Scholar]
  18. EisnerL., Williams‐StroudS., HillA., DuncanP. and ThorntonM.2010. Beyond the dots in the box: Microseismicity‐constrained fracture models for reservoir simulation. The Leading Edge29, 326–333.
    [Google Scholar]
  19. GrechkaV. and TsvankinI.2003. Feasibility of seismic characterisation of multiple fracture sets. Geophysics68, 1399–1407.
    [Google Scholar]
  20. HallS.A. and KendallJ.‐M.2000. Constraining the interpretation of AVOA for fracture characterisation. In: Anisotropy 2000: Fractures, Converted Waves, and Case Studies (eds L.Ikelle and A.Gangi ), pp. 107–144. SEG.
    [Google Scholar]
  21. HallS.A., KendallJ.‐M., MaddockJ. and FisherQ.2008. Crack density tensor inversion for analysis of changes in rock frame architecture. Geophysical Journal International173, 577–592.
    [Google Scholar]
  22. HolmesG.M., CrampinS. and YoungR.P.2000. Seismic anisotropy in granite at the Underground Research Laboratory, Manitoba. Geophysical Prospecting48, 415–435.
    [Google Scholar]
  23. HorneS. and MacBethC.1994. Inversion for seismic anisotropy using genetic algorithms. Geophysical Prospecting42, 953–974.
    [Google Scholar]
  24. HorneS., MacBethC., QueenJ., RizerW. and CoxV.1997. Fracture characterization from near offset VSP inversion. Geophysical Prospecting45, 141–164.
    [Google Scholar]
  25. HudsonJ.A.1981. Wave speeds and attenuation of elastic waves in material containing cracks. Geophysical Journal of the Royal Astronomical Society64, 133–150.
    [Google Scholar]
  26. HudsonJ.A., LiuE. and CrampinS.1996. The mechanical properties of materials with interconnected cracks and pores. Geophysical Journal International124, 105–112.
    [Google Scholar]
  27. KeirD., KendallJ.‐M., EbingerC.J. and StuartG.W.2005. Variations in late syn‐rift melt alignment inferred from shear‐wave splitting in crustal earthquakes beneath the Ethiopian rift. Geophysical Research Letters32, L23308.
    [Google Scholar]
  28. KendallJ.‐M., FisherQ.J., Covey CrumpS., MaddockJ., CarterA., HallS.A. et al . 2007. Seismic anisotropy as an indicator of reservoir quality of siliclastic rocks. In: Structurally Complex Reservoirs (eds S.Jolley , D.Barr , J.Walsh and R.Knipe ), pp. 123–136. Geological Society of London.
    [Google Scholar]
  29. KendallJ.‐M., PilidouS., KeirD., BastowI.D., StuartG.W. and AyeleA.2006. Mantle upwellings, melt migration and magma assisted rifting in Africa: Insights from seismic anisotropy. In: Structure and Evolution of the Rift Systems within the Afar Volcanic Province , Northeast Africa (eds G.Yirgu , C.J.Ebinger and P.K.H.Maguire ), pp. 57–74. Geological Society of London.
    [Google Scholar]
  30. KendallJ.‐M., StuartG.W., EbingerC.J., BastowI.D. and KeirD.2005. Magma assisted rifting in Ethiopia. Nature433, 146–148.
    [Google Scholar]
  31. Le CalvezJ.H., BennetL., TannerK.V., GrantW.D., NuttL., JochenV. et al . 2005. Monitoring microseismic fracture development and production in aging fields. The Leading Edge24, 72–75.
    [Google Scholar]
  32. LuoM., TakahashiI., TakanashiM. and TamuraY.2005. Improved fracture network mapping through reducing overburden influence. The Leading Edge24, 1094–1098.
    [Google Scholar]
  33. LuoM., TakanashiM., NakayamaK. and EzakaT.2007. Physical modeling of overburden effects. Geophysics72, T37–T45.
    [Google Scholar]
  34. PointerT., LiuE. and HudsonJ.A.2000. Seismic wave propagation in cracked porous media. Geophysical Journal International142, 199–231.
    [Google Scholar]
  35. RialJ.A., ElkibbiM. and YangM.2005. Shear‐wave splitting as a tool for the characterization of geothermal fractured reservoirs: lessons learned. Geothermics34, 365–385.
    [Google Scholar]
  36. RümpkerG., TommasiA. and KendallJ.‐M.1999. Numerical simulations of depth‐dependent anisotropy and frequency‐dependent wave propagation effects. Journal of Geophysical Research104, 23141–23153.
    [Google Scholar]
  37. RutledgeJ.T., PhillipsW.S. and MayerhoferM.J.2004. Faulting induced by forced fluid injection and fluid flow forced by faulting: An interpretation of hydraulic fracture microseismicity, Carthage Cotton Valley Gas Field, Texas. Bulletin of the Seismological Society of America94, 1817–1830.
    [Google Scholar]
  38. SchoenbergM. and SayersC.M.1995. Seismic anisotropy of fractured rock. Geophysics60, 204–211.
    [Google Scholar]
  39. ShuckE.L., DavisT.L. and BensonR.D.1996. Multicomponent 3‐D characterization of a coalbed methane reservoir. Geophysics61, 315–330.
    [Google Scholar]
  40. SilverP.G. and ChanW.W.J.1991. Shear‐wave splitting and subcontinental mantle deformation. Journal of Geophysical Research96, 16429–16454.
    [Google Scholar]
  41. TeanbyN.A., KendallJ.‐M., JonesR.H. and BarkvedO.2004a. Stress‐induced temporal variations in seismic anisotropy observed in microseismic data. Geophysical Journal International156, 459–466.
    [Google Scholar]
  42. TeanbyN.A., KendallJ.‐M. and Van Der BaanM.2004b. Automation of shear‐wave splitting measurements using cluster analysis. Bulletin of the Seismological Society of America94, 453–463.
    [Google Scholar]
  43. ThomsenL.1986. Weak elastic anisotropy. Geophysics51, 1954–1966.
    [Google Scholar]
  44. TodS.R.2002. The effects of stress and fluid pressure on the anisotropy of interconnected cracks. Geophysical Journal International149, 149–156.
    [Google Scholar]
  45. ValckeS.L.A., CaseyM., LloydG.E., KendallJ.‐M. and FisherQ.J.2006. Lattice preferred orientation and seismic anisotropy in sedimentary rocks. Geophysical Journal International166, 652–666.
    [Google Scholar]
  46. VerdonJ.P.2010. Microseismic monitoring and geomechanical modelling of CO2 storage in subsurface reservoirs . PhD thesis, University of Bristol.
  47. VerdonJ.P., AngusD.A., KendallJ.‐M. and HallS.A.2008. The effects of microstructure and nonlinear stress on anisotropic seismic velocities. Geophysics73, D41–D51.
    [Google Scholar]
  48. VerdonJ.P., KendallJ.‐M. and WüstefeldA.2009. Imaging fractures and sedimentary fabrics using shear wave splitting measurements made on passive seismic data. Geophysical Journal International179, 1245–1254.
    [Google Scholar]
  49. VerdonJ.P., KendallJ.‐M. and MaxwellS.C.2010a. A comparison of passive seismic monitoring of fracture stimulation due to water versus CO2 injection. Geophysics75, MA1–MA7.
    [Google Scholar]
  50. VerdonJ.P., WhiteD.J., KendallJ.‐M., AngusD.A., FisherQ. and UrbancicT.2010b. Passive seismic monitoring of carbon dioxide storage at Weyburn. The Leading Edge29, 200–206.
    [Google Scholar]
  51. WhiteD.2009. Monitoring CO2 storage during EOR at the Weyburn‐Midale field. The Leading Edge28, 838–842.
    [Google Scholar]
  52. WintersteinD.F., DeG.S. and MeadowsM.A.2001. Twelve years of vertical birefringence in nine‐component VSP data. Geophysics66, 582–597.
    [Google Scholar]
  53. WookeyJ.2010. Direct probabilistic inversion of shear‐wave data for anisotropy. Bulletin of the Seismological Society of America (sub judice).
    [Google Scholar]
  54. WookeyJ. and HelffrichG.R.2008. Inferences on inner‐core shear‐wave anisotropy and texture from an observation of PKJKP waves. Nature454, 873–876.
    [Google Scholar]
  55. WüstefeldA., Al‐HarrasiO., VerdonJ.P., WookeyJ. and KendallJ.‐M.2010. A strategy for automated analysis of passive microseismic data to study seismic anisotropy and fracture characteristics. Geophysical Prospecting58, 755–773.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1111/j.1365-2478.2010.00943.x
Loading
/content/journals/10.1111/j.1365-2478.2010.00943.x
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): Fractures; Microseismic

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