A Case Study Of A New Time-Depth Conversion Workflow Designed For Optimizing Recovery

References

1. P.Abrahamsen
   (1996), “Geostatistics for Seismic Depth Conversion”, Report, NR-note SAND/06/1996, 9 pages.
   [Google Scholar]
2. P.Abrahamsen
   (1993), “Bayesian Kriging for Seismic Depth Conversion of a Multi-layer Reservoir” in A.Soares (ed.) “Geostatistics Troia 92”, Kluwer Academic Publ. Dordrecht, pp. 385–398
   [Google Scholar]
3. Etris, E.L., Crabtree, R.J. and Dewar, J.
   (2001), “True depth conversion: More than a pretty picture: Recorder”, 26, no. 11, 1122
   [Google Scholar]
4. Hwang, L. & McCorkindale, D.
   (1994), “Troll field depth conversion using geostatistically derived average velocities”, The Leading Edge13(4), 561–569
   [Google Scholar]
5. Xu, W., Tran, T.T., Srivastava, R.M., Journel, A.G.
   (1992), “Integrating seismic data in reservoir modeling: The collocated cokriging alternative”, in 67th Annual Technical Conference and Exhibition, Society of Petroleum Engineers, Washington DC, pp.833–842, SPE 24742.
   [Google Scholar]
6. DubruleO
   (2003), “Geostatistics for seismic data integration in earth models: 2003 Distinguished Instructor Short Course”; sponsored by the Society of Exploration Geophysicists and European Association of Geoscientists & Engineers
   [Google Scholar]
7. Emery, X.
   (2008), “A Turning Bands Program for Conditional Co-Simulation of Cross-Correlated Gaussian Random Fields”, Computers & Geosciences, 34, 1850–1862.
   [Google Scholar]
8. Deutsch, C., Journel, A.
   , (1998), “GSLIB: Geostatistical Software Library and User’s Guide”2nd Edition, Oxford University Press, New York – Oxford
   [Google Scholar]
9. Gonzales, E., McLennan, J. A., & Deutsch, C. V.
   (2006). “A new approach to sequential gaussian simulation with a trend: Non-stationary transformation tables” - Paper 120. Report 8. Centre for Computational Geostatistics.
   [Google Scholar]
10. Soares, A.
    (2001), “Direct Sequential Simulation and Cosimulation”, Math Geol33(8):911–926
    [Google Scholar]
11. Jeannee, N., Shiner, P., Deraisme, J.
    , (2004), “Geostatistical assessment of time picking uncertainties and theirimpact on GRV”, AAPG European Region Conference, Prague, October-2004
    [Google Scholar]
12. Matheron, G.
    , (1982), “Pour une Analyse Krigeante de Données Régionalisées” Note interne, N-732, Centre de Géostatistique, Fontainebleau, France, 22 p.
    [Google Scholar]
13. Jaquet, O.
    , (1989), “Factorial Kriging Analysis Applied to Geological Data from Petroleum Exploration”, International Association for Mathematical Geology, 0882-8121/89/1000-0683 $06.00/1
    [Google Scholar]
14. WackernagelH.
    (2003) Universal Kriging. In: Multivariate Geostatistics. Springer, Berlin, Heidelberg
    [Google Scholar]
15. Matheron, G.
    (1971). “The Theory of Regionalized Variables and Its Applications”. Les Cahiers du Centre de Morphologie Mathematique de Fontainebleau, No. 5. Fontainebleau: Ecole Nationale Sup´erieure des Mines de Paris.
    [Google Scholar]
16. Fomel, S., Landa, S.
    , (2014), “Structural uncertainty of time-migrated seismic images”, Journal of Applied Geophysics, Volume 101, February - 2014, Pages 27–30
    [Google Scholar]
17. Yilmaz, O.
    , (2001), “Seismic data analysis: Processing, inversion, and interpretation of seismic data”, 2nd ed.: SEG.
    [Google Scholar]
18. Poliannikov, O., Malcom, A.
    , (2016), “The effect of velocity uncertainty on migrated reflectors: Improvements from relative-depth imaging”, Geophysics, Vol. 81, January-February 2016, P. S21–S29
    [Google Scholar]
19. Cameron, M. K., S.Fomel, and J. A.Sethian
    , (2007), “Seismic velocity estimation from time migration velocities”, Inverse Problems, 23, 1329–1369.
    [Google Scholar]
20. Røe, P., Georgsen, F. and Abrahamsen, P.
    , (2014), “An Uncertainty Model for Fault Shape and Location”, Mathematical Geosciences46 (8).
    [Google Scholar]