Probabilistic facies prediction in a carbonate gas reservoir of Iran using stochastic seismic inversion and connectivity algorithm
Ansari, H.R., Motafakkerfard, R. and Riahi, M.A., 2015. Probabilistic facies prediction in a carbonate gas reservoir of Iran using stochastic seismic inversion and connectivity algorithm. Journal of Seismic Exploration, 24: 15-35. Inversion methods are valuable tools for obtaining reservoir properties from seismic data. However, results of the seismic inversion are band-limited due to band-limited source wavelet. Therefore, the low and high frequency information is lost in seismic traces. In order to overcome this problem, well logs and seismic data were used together in a seismic inversion algorithm using stochastic methods. In this paper, the stochastic inversion method was based on spectral simulation to create acoustic impedance realizations. Also, an initial broad-band model was derived from kriging of the well log data. Then, spectral simulation was applied for the seismic inversion. This method was conducted on one of the marine carbonate gas fields in Iran and the results were compared with deterministic inversion. In the second part of this study, acoustic impedance realizations and rock density volume, obtained from the previous section, were combined with instantaneous frequency as the input of an unsupervised neural network for clustering the three rock facies and a vector quantizer network was utilized for this purpose. The network results were calibrated with porosity in the well location and provided threshold parameters to conduct the connectivity facies analysis. Finally, the connectivity algorithm was applied to all the realizations of stochastic inversion results to achieve highly probable favorable facies.
- Bortoli, L.J., Alabert, F., Haas, A. and Journel, A., 1993. Constraining stochastic images to
- seismic data. In: Soares, A. (Ed.), Quantitative Geology and Geostatistics: Geostatistics
- Troia 92. Springer Verlag, Dordrecht, p. 325-337.
- Bosch, M., Mukerji, T. and Gonzalez, E.F., 2010. Seismic inversion for reservoir properties
- combining statistical rock physics and geostatistics - a review. Geophysics, 75(5): 165-76.
- PROBABILISTIC FACIES PREDICTION 35
- Buland, A. and Omre, H., 2003. Bayesian linearized AVO inversion. Geophysics, 68: 185-198.
- Cooke, D.A. and Schneider, W.A., 1983. Generalized linear inversion of reflection seismic data.
- Geophysics, 48: 665-676.
- Debeye, H.W.J., Sabbah, E. and van der Made, P.M., 1996. Stochastic inversion. Expanding
- Abstr., 66th Ann. Internat. SEG Mtg., Denver: 1212-1215.
- Deutsch, C., 1998. FORTRAN programs for calculating connectivity of three dimensional numerical
- models and for ranking multiple realizations. Comput. Geosci., 24: 69-76.
- Deutsch, C. and Journel, A., 1998. GSLIB - Geostatistical Software Library and User’s Guide.
- Oxford University Press, New York.
- Eidsvik, J., Avseth, P., More, H., Mukerji, T. and Mavko, G., 2004. Stochastic reservoir
- characterization using prestack seismic data. Geophysics, 69: 978-993.
- Francis, A., 2005. Limitations of deterministic and advantages of stochastic seismic inversion.
- CSEG Recorder, 30(2): 5-11.
- Francis, A., 2006a. Understanding stochastic inversion - Part 1. First break, 24(11): 69-77.
- Francis, A., 2006b. Understanding stochastic inversion - Part 2. First break, 24 (12): 79-84.
- Gersho, A. and Gray, R.M., 1992. Vector Quantization and Signal Compression. Kluwer Academic
- Publishers, New York.
- Gonzalez, E.F., Mukerji, T. and Mavko., G., 2008. Seismic inversion combining rock physics and
- multiple-point geostatistics. Geophysics, 73(1): R11-R21.
- Haas, A. and Dubrule, O., 1994. Geostatical inversion: a sequential method of stochastic reservoir
- modeling constrained by seismic data. First break, 12: 561-569.
- Kane, J., Rodi, W., Herrmann, F. and Tokséz, M.N., 1999. Geostatistical seismic inversion using
- well log constraints. Expanding Abstr., 69th Ann. Internat. SEG Mtg., Houston: 1504-1507.
- Kelkar, M. and Perez, G., 2002. Applied Geostatistics for Reservoir Characterization. Soc. Petrol.
- Engin. Publicat., Richardson, TX: 52-97.
- Lancaster, S. and Whitcombe, D., 2000. Fast-track coloured inversion. Expanding Abstr., 70th
- Ann. Internat. SEG Mtg., Calgary, AB: 1572-1575.
- Matos, M.C., Osério, P.L.M. and Johann, P.R.S., 2005. Vertical seismic facies detection through
- unsupervised 3D voxel based seismic facies classification applied to a turbidite field in
- Campose Basin - Brazil. 9th Internat. Congr. Braz. Geophys. Soc., Salvador, Brazil.
- Pardo-Iguzquiza, E. and Chica-Olmo, M., 1993. The Fourier integral method - an efficient spectral
- method for simulation of random fields. Mathemat. Geol., 25; 177-217.
- Russel, B., 1988. Model-based Inversion. Introduction to Seismic Inversion Methods. SEG, Tulsa,
- OK.
- Russel, B., 2005. Neural network applications in geophysics. CSEG Nat. Conv.: 339-342.
- Tavakoli, V., Rahimpour-Bonab, H. and Esrafili-Dizaji, B., 2011. Diagenetic controlled reservoir
- quality of South Pars gas field - an integrated approach. Comptes Rendus Geosc., 343:
- 55-71.
- Taner, M.T., Schuelke, J.S., O’Doherty, R. and Baysal, E., 1994. Seismic attributes revisited.
- Expanded Abstr., 64th Ann. Internat. SEG Mtg., Los Angeles: 1104-1106.
- Yao, T., Calvert, C., Bishop, G., Jones, T., Ma, Y. and Foreman, L., 2004. Spectral component
- geologic modeling - a new technology for integrating seismic information at the correct scale.
- In: Leuangthong, O. and Deutsch, C.V. (Eds.), Geostatistics Banff. Springer Verlag,
- Dordrecht: 23-33.
