1887

Abstract

Summary

3D borehole-related seismic data has superior quality and higher-frequency content compared to surface seismic data. These unique properties make it possible to produce high-resolution images and accurate velocity models especially around the borehole. However, using conventional imaging algorithms, that assume primary reflection energy, will retrieve only a limited area around the borehole. This problem can be overcome by including surface-related and internal multiples in the imaging algorithm to enhance the illumination of the. In addition, on-the-fly the velocity model can be updated using the so-called Joint Migration Inversion (JMI) process, which explains the full wavefield seismic data in terms of reflectivity and a propagation velocity model. To augment the results, datasets from different wells in the area can reinforce each other by simultaneous inversion to assure the consistency and improve the quality of the results. To steer and constrain the velocity estimation, the estimated reflectivity in the JMI process can be used as additional constraint for the velocity updating process.

In this paper we have deployed the full wavefield of the 3D borehole data, from two different wells, containing all orders scattering, both up- and down-going wavefields, in one integrated inversion-imaging process as proposed by the JMI methodology. The final result is a smooth accurate background velocity model along with a true amplitude reflectivity image with high resolution and maximum lateral extent.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201803055
2018-11-27
2020-07-06
Loading full text...

Full text loading...

References

  1. Caprioli, P.B.A., Du, X., Fletcher, R.P. and Vasconcelos, I.
    [2014] 3D source deghosting after imaging: 84th Annual International Meeting, SEG, Expanded Abstracts.
    [Google Scholar]
  2. Cavalca, M., Fletcher, R.P. and Du, X.
    [2015] Q-compensation through depth domain inversion: 77th Conference and Exhibition, EAGE, Extended Abstracts.
    [Google Scholar]
  3. Cavalca, M., Fletcher, R.P., and Caprioli, P.
    , [2016] Least-squares Kirchhoff depth migration in the image domain. 78th Conference & Exhibition, EAGE, Extended Abstracts.
    [Google Scholar]
  4. Dingwall, S., DeGroot, A. and Wright, S.
    [2017] The Cook Field: Uncertainty mitigation through subsurface integration and quantitative geophysics. PESGB Geophysics Seminar: Quantitative Interpretation, Expanded Abstracts.
    [Google Scholar]
  5. Fletcher, R.P., Archer, S., Nichols, D., and Mao, W.
    [2012] Inversion after depth imaging. 82nd Annual International Meeting, SEG, Expanded Abstracts.
    [Google Scholar]
  6. Fletcher, R.P., Nichols, D., Bloor, R., and Coates, R.T.
    [2016] Least-squares migration: data domain versus image domain using point spread functions. The Leading Edge, Vol 35, No. 2, 157–162.
    [Google Scholar]
  7. Lecomte, I.
    [2008] Resolution and illumination analyses in PSDM: A ray-based approach. The Leading Edge, Vol 27, No. 5, 650–663.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201803055
Loading
/content/papers/10.3997/2214-4609.201803055
Loading

Data & Media loading...

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