1887

Abstract

Summary

This paper describes the construction of a high-resolution anisotropic FWI model that is used to help image a karstified carbonate layer (Faumai) and also to help define the underlying clastic reservoirs. The karst zones show extreme velocity rugosity. Conventional reflection tomography cannot resolve these anomalous velocities, and the seismic images below these karstified carbonates are distorted and are poor for interpretation.

In 2009 an isotropic FWI algorithm, up to 7Hz, was applied to this OBC survey by BP. Image quality was significantly improved. However, in and below the karst formation, the FWI velocity resolution improved less.

In 2015, anisotropic FWI, up to 12Hz including Q attenuation, was applied to this survey using the latest algorithms and methodologies. This paper presents the improved results and discusses the best strategies for determining the appropriate input data for FWI (diving-wave, reflection, or both), and depth limitation. The complete modelling required five components: diving-wave velocity updates to depths of 2200m; reflection waves included from 1600m onwards; derived anisotropic values; derived Q-model; and residual curvature tomography.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201601188
2016-05-31
2020-06-05
Loading full text...

Full text loading...

References

  1. da Silva, N. V., Ratcliffe, A., Conroy, G., Vinje, V. and Body, G.
    [2014] A new parameterization for anisotropy update in full waveform inversion. 85th SEG Annual International Meeting, Expanded abstract, 1050–1055.
    [Google Scholar]
  2. Guillaume, P., Lambaré, G., Leblanc, O., Mitouard, P., Le Moigne, J., Montel, J.P., Prescott, A., Siliqi, R., Vidal, N., Zhang, X. and Zimine, S.
    [2008] Kinematic invariants: an efficient and flexible approach for velocity model building. 78th Annual SEG Meeting, workshop “Advanced velocity model building techniques for depth imaging”.
    [Google Scholar]
  3. Lin, R. and Thomson, L.
    [2013] Extracting polar anisotropy parameters from seismic data and well logs. SEG Houston 2013 Annual Meeting. Expanded abstract, 310–314.
    [Google Scholar]
  4. Mothi, S. and Kumar, R.
    [2014] Detecting and estimating anisotropy errors using full waveform inversion and ray-based tomography: A case study using long-offset acquisition in the Gulf of Mexico. 85th SEG Annual International Meeting, Expanded abstract, 1066–1071.
    [Google Scholar]
  5. Ray, S., Zhang, Z., Fu, Z., Liu, L. and Wang, P.
    [2014] Noise attenuation using a dipole sparse Tau-P inversion. 84th SEG Annual International Meeting, Expanded abstract, 4213–4217.
    [Google Scholar]
  6. Schurter, G.J., Supriatna, Y., Nuraeni, A., Supriyono, Regone, C.J. and Kabir, N.
    [2009] A 3D finite-difference modeling study of seismic imaging challenges in Bintuni Bay, Irian Jaya Barat, The Leading Edge, 28, 1008–1021.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201601188
Loading
/content/papers/10.3997/2214-4609.201601188
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