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Volume 65, Issue 4
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Using seismic attributes such as coherence and curvature to characterise faults not only can improve the efficiency of seismic interpretation but also can expand the capability to detect faults. The coherence and curvature have been widely applied to characterising faults for years. These two methods detect faults based on the similarity of seismic waveforms and shapes of the reflectors, respectively, and they are complementary to each other and both have advantages and disadvantages in fault characterisation. A recent development in fault characterisation based on reflector shapes has been the use of the rate of change of curvature. Through an application to the seismic data from Western Tazhong of the Tarim Basin, China, it was demonstrated that the rate of change of curvature is more capable of detecting subtle faults having quite small throws and heaves. However, there often exist multiple extreme values indicating the same fault when applying the rate of change of curvature, which significantly degrades the signal‐to‐noise ratio of the computation result for multiple extrema interfering with each other. To resolve this problem, we propose the use of a linear combination of arctangent and proportional functions as the directrix of a cylindrical surface to fit the fault model and calculate its third derivative, which can then be used to characterise the fault. Through an application to the 3D seismic data from Western Tazhong of the Tarim Basin, the results show that the proposed method not only retains the same capability to detect subtle faults having small throws as the curvature change rate but also greatly improves the signal‐to‐noise ratio of the calculated result.

© 2017 European Association of Geoscientists & Engineers © 2016 European Association of Geoscientists & Engineers
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/content/journals/10.1111/1365-2478.12462
2016-09-23
2024-04-24

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References

  1. Al‐DossaryS. and MarfurtK.J.2006. 3D volumetric multispectral estimates of reflector curvature and rotation. Geophysics71, P41–P51.
     [Google Scholar]
  2. BahorichM. and FarmerS.1995. 3D seismic discontinuity for faults and stratigraphic features: the coherence cube. The Leading Edge14, 1053–1058.
     [Google Scholar]
  3. ChopraS. and MarfurtK.J.2007a. Volumetric curvature attributes add value to 3D seismic data interpretation. The Leading Edge26, 856–867.
     [Google Scholar]
  4. ChopraS. and MarfurtK.J.2007b. Volumetric curvature attributes for fault/fracture characterization. First Break25, 19–30.
     [Google Scholar]
  5. CohenI. and CoifmanR.R.2002. Local discontinuity measures for 3D seismic data. Geophysics67, 1933–1945.
     [Google Scholar]
  6. DiH. and GaoD.2015. Efficient volumetric extraction of most positive/negative curvature and flexure for fracture characterization from 3D seismic data. Geophysical Prospecting.
  7. GaoD.2013. Integrating 3D seismic curvature and curvature gradient attributes for fracture characterization: methodologies and interpretational implications. Geophysics78, O21–O31.
     [Google Scholar]
  8. GaoD. and DiH.2015. Extreme curvature and extreme flexure analysis for fracture characterization from 3D seismic data: new analytical algorithms and geologic implications. Geophysics80, IM11–IM20.
     [Google Scholar]
  9. GersztenkornA. and MarfurtK.J.1999. Eigenstructure‐based coherence computations as an aid to 3D structural and stratigraphic mapping. Geophysics64, 1468–1479.
     [Google Scholar]
  10. LiY., LuW., XiaoH., ZhangS. and LiY.2006. Dip‐scanning coherence algorithm using eigenstructure analysis and supertrace technique. Geophysics71, V61–V66.
     [Google Scholar]
  11. LisleR.J.1994. Detection of zones of abnormal strains in structures using Gaussian curvature analysis. AAPG Bulletin78, 1811–1819.
     [Google Scholar]
  12. LuW., LiY., ZhangS., XiaoH. and LiY.2005. Higher‐order‐statistics and supertrace‐based coherence‐estimation algorithm. Geophysics70, P13–P18.
     [Google Scholar]
  13. MarfurtK.J.2006. Robust estimates of 3D reflector dip and azimuth. Geophysics71, P29–P40.
     [Google Scholar]
  14. MarfurtK.J., KirlinzR.L., FarmerS.L. and BahorichM.S.1998. 3D seismic attributes using a semblance‐based coherency algorithm. Geophysics63, 1150–1165.
     [Google Scholar]
  15. MarfurtK.J., SudhakerzV., GersztenkornA., CrawfordK.D. and NissenS.E.1999. Coherency calculations in the presence of structural dip. Geophysics64, 104–111.
     [Google Scholar]
  16. RobertsA.2001. Curvature attributes and their application to 3D interpreted horizons. First Break19, 85–100.
     [Google Scholar]
  17. TingdahlK.M. and De RooijM.2005. Semi‐automatic detection of faults in 3D seismic data. Geophysical Prospecting53, 533–542.
     [Google Scholar]
  18. YuJ.2014. Using cylindrical surface‐based curvature change rate to detect faults and fractures. Geophysics79, O1–O9.
     [Google Scholar]
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Arctangent function‐based third derivative attribute for characterisation of faults
Geophysical Prospecting 65, 913 (2017); https://doi.org/10.1111/1365-2478.12462
/content/journals/10.1111/1365-2478.12462
/content/journals/10.1111/1365-2478.12462
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  • Article Type: Research Article
Keyword(s): Arctangent function; Fault characterization; Seismic attribute; Subtle faults; Third derivative

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