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Correcting source and receiver scaling for virtual source imaging and monitoring

Authors:

Virtual source redatuming is a data-driven interferometric approach that relies on constructive and destructive interference, and as a result it is quite sensitive to input seismic trace amplitudes. Land surveys are prone to amplitude changes that are unrelated to subsurface geology (source/receiver coupling, etc.). We have determined that such variations may be particularly damaging to construct a virtual-source signal for imaging and seismic monitoring applications, and they need to be correctly compensated before satisfactory images, repeatability, and proper relative amplitudes are achieved. We examine two methods to correct for these variations: a redatuming approach based on multidimensional deconvolution and multisurvey surface-consistent (SC) scaling. Using synthetic data, we discover that the first approach can only balance time-dependent variations between repeat surveys, e.g., compensate for variable shot scaling. In contrast, a multisurvey SC approach can compensate for shot and receiver scaling within each survey and among the surveys. As a result, it eliminates redatuming artifacts, brings repeat surveys to a common amplitude level, while preserving relative amplitudes required for quantitative interpretation of 4D amplitude differences. Applying an SC approach to a land time-lapse field data set with buried receivers from Saudi Arabia, we additionally conclude that separate SC scaling of early arrivals and deep reflections may produce better image and repeatability. This is likely due to the significantly different frequency content of early arrivals and deep reflections.

REFERENCES

  • Alexandrov, D., J. Van der Neut, A. Bakulin, and B. Kashtan, 2015a, Improving repeatability of land seismic data using virtual source approach based on multidimensional deconvolution: 77th Annual International Conference and Exhibition, EAGE, Extended Abstracts, doi: 10.3997/2214-4609.201412558.CrossrefGoogle Scholar
  • Alexandrov, D., J. Van der Neut, A. Bakulin, and B. Kashtan, 2015b, Correcting for non-repeatable source signatures in 4D seismic with buried receivers: Virtual source case study from Saudi Arabia: 85th Annual International Meeting, SEG, Expanded Abstracts, 5343–5347, doi: 10.1190/segam2015-5890959.1.AbstractGoogle Scholar
  • Bakulin, A., R. Burnstad, M. Jervis, and P. Kelamis, 2012, Evaluating permanent seismic monitoring with shallow buried sensors in a desert environment: 82nd Annual International Meeting, SEG, Expanded Abstracts, doi: 10.1190/segam2012-0951.1.AbstractGoogle Scholar
  • Bakulin, A., and R. Calvert, 2004, Virtual source: New method for imaging and 4D below complex overburden: 74th Annual International Meeting, SEG, Expanded Abstracts, 2477–2480, doi: 10.1190/1.1845233.AbstractGoogle Scholar
  • Bakulin, A., A. Mateeva, K. Mehta, P. Jorgensen, I. Sinha Herhold, and J. Lopez, 2007, Virtual source applications to imaging and reservoir monitoring: The Leading Edge, 26, 732–740, doi: 10.1190/1.2748490.AbstractGoogle Scholar
  • Bakulin, A., R. Smith, M. Jervis, and R. Burnstad, 2014, Near surface changes and 4D seismic repeatability in desert environment: From days to years: 84th Annual International Meeting, SEG, Expanded Abstracts, 4843–4847, doi: 10.1190/segam2014-0429.1.AbstractGoogle Scholar
  • Hauge, P. S., 1981, Measurements of attenuation from vertical seismic profiles: Geophysics, 46, 1548–1558, doi: 10.1190/1.1441161.GPYSA70016-8033AbstractWeb of ScienceGoogle Scholar
  • Jervis, M., A. Bakulin, R. Burnstad, C. Berron, and E. Forgues, 2012, Suitability of vibrators for time-lapse monitoring in the Middle East: 82nd Annual International Meeting, SEG, Expanded Abstracts, doi: 10.1190/segam2012-0948.1.AbstractGoogle Scholar
  • Kragh, E., and P. Christie, 2002, Seismic repeatability, normalized rms, and predictability: The Leading Edge, 21, 640–647, doi: 10.1190/1.1497316.AbstractGoogle Scholar
  • Mehta, K., A. Bakulin, J. Sheiman, R. Calvert, and R. Snieder, 2007, Improving the virtual source method by wavefield separation: Geophysics, 72, no. 4, V79–V86, doi: 10.1190/1.2733020.GPYSA70016-8033AbstractWeb of ScienceGoogle Scholar
  • Quan, Y., and J. M. Harris, 1993, Seismic attenuation tomography based on centroid frequency shift: 63rd Annual International Meeting, SEG, Expanded Abstracts, 41–44, doi: 10.1190/1.1822504.AbstractGoogle Scholar
  • Retailleau, M., R. El Asrag, and J. Shorter, 2014, Processing land broadband data: Challenges that Oman surveys present and how they are addressed: Presented at the EAGE/SPG Workshop on Broadband Seismic, Session: Broadband OBC & Land, doi: 10.3997/2214-4609.20141699.CrossrefGoogle Scholar
  • Taner, M. T., and F. Koehler, 1981, Surface consistent corrections: Geophysics, 46, 17–22, doi: 10.1190/1.1441133.GPYSA70016-8033AbstractWeb of ScienceGoogle Scholar
  • Telford, W. M., L. P. Geldart, and R. E. Sheriff, 1990, Applied geophysics: Cambridge University Press.CrossrefGoogle Scholar
  • Wapenaar, K., and J. Van der Neut, 2011, Seismic interferometry by crosscorrelation and by multidimensional deconvolution: A systematic comparison: Geophysical Journal International, 185, 1335–1364, doi: 10.1111/j.1365-246X.2011.05007.x.GJINEA0956-540XCrossrefWeb of ScienceGoogle Scholar
  • Wapenaar, K., J. van der Neut, and E. Ruigrok, 2008, Passive seismic interferometry by multidimensional deconvolution: Geophysics, 73, no. 6, A51–A56, doi: 10.1190/1.2976118.GPYSA70016-8033AbstractWeb of ScienceGoogle Scholar
  • Wiggins, R. A., K. L. Larner, and R. D. Wisecup, 1976, Residual statics analysis as a general linear inverse problem: Geophysics, 41, 922–938, doi: 10.1190/1.1440672.GPYSA70016-8033AbstractWeb of ScienceGoogle Scholar