Abstract
Accurate incorporation of geological concepts such as lithological facies distributions is an important aspect of building reservoir models. Consequently, accounting for facies in seismic inversion generates models conditioned to geological concepts and plays an important role in decision-making. Shell’s proprietary probabilistic model-based seismic inversion engine Promise is generally applied to invert for continuous variables, such as NTG, saturation, and layer thickness from seismic data. In some depositional environments, the spatial variability of reservoir properties is characterized at fine geological scale by facies and the corresponding petrophysical properties; hence, an implementation of facies in seismic inversion is desirable. In this study, we propose a novel methodology for lithological facies inversion utilizing Plurigaussian rock-type rules. Direct inversion of facies may result in unrealistic facies contacts; therefore, the proposed technique instead inverts for a pair of “guide” variables using Promise. The guide variables are then classified into facies using a methodology inspired by Plurigaussian simulations, where a defined lithofacies rule map is used to constrain facies proportions and contacts. The required inputs for the workflow are the lithofacies rules and variogram estimates of the guide variables. Both of these can be derived from a prior estimate of the facies distribution and can also take into account geological constraints from a human expert. We demonstrate the workflow for a three facies case with a synthetic wedge model and seismic data of a marine survey.
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Bibliography
Allen D (1984) Laminated sand analysis. SPWLA 25th Annual Logging Symposium. New Orleans: Society of Petrophysicists and Well-Log Analysts, 20
Armstrong M et al (2011) Plurigaussian simulations in geosciences. Springer Science & Business Media, New York
Coléou T, Manuel P, Azbel K (2003) Unsupervised seismic facies classification: a review and comparison of techniques and implementation. Lead Edge 22(10):942–953
Doyen P (2007) Seismic reservoir characterization: an earth modelling perspective. EAGE publications, Houten
Doyen PM, Psaila DE, Den Boer LD, Jans D (1997) Reconciling data at seismic and well log scales in 3-D earth modelling, SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers, San Antonio, p 10
Dubois M, Bohling G, Chakrabarti S (2007) Comparison of four approaches to a rock facies classification problem. Comput Geosci 33(5):599–617
Gelderblom P, Leguijt J (2010) Geological constraints in model-based seismic inversion, SEG International Exposition and 84th Annual Meeting. Society of Exploration Geophysicists, Denver, pp 2825–2829
Gómez-Hernández JJ, Rodrigo-Ilarri J, Cassiraga E (2016) Extended abstract example for GEOSTATS2016, Instructions for GEOSTATS2016 participants. Universitat Politècnica de València, Valencia, pp 1–4
Grana D, Della Rossa E (2010) Probabilistic petrophysical-properties estimation integrating statistical rock physics with seismic inversion. Geophysics 75(3):21–37
Gunning JS, Kemper M, Pelham A (2014) Obstacles, challenges and strategies for facies estimation in AVO seismic inversion. 76th EAGE Conference and Exhibition 2014
Hesthammer J, Landrø M, Fossen H (2001) Use and abuse of seismic data in reservoir characterisation. Mar Pet Geol 18(5):635–655
Larsen AL, Ulvmoen M, Omre H, Buland A (2006) Bayesian lithology/fluid prediction and simulation on the basis of a Markov-chain prior model. Geophysics 71(5):69–78
Leguijt J (2001) A promising approach to subsurface information integration, 63rd Conference Extended Abstracts. European Association of Geoscientists & Engineers, Amsterdam, p 4
Leguijt J (2009) Seismically constrained probabilistic reservoir modeling. Lead Edge (Soc Explor Geophys) 28(12):1478–1484
Rimstad K, Omre H (2010) Impact of rock-physics depth trends and Markov random fields on hierarchical Bayesian lithology/fluid prediction. Geophysics 75(4):93–108
Ulvmoen M, Omre H (2010) Improved resolution in Bayesian lithology/fluid inversion from prestack seismic data and well observations: part 1—methodology. Geophysics 75(2):21–35
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Li, L., Xu, S., Gelderblom, P. (2017). Facies Inversion with Plurigaussian Lithotype Rules. In: Gómez-Hernández, J., Rodrigo-Ilarri, J., Rodrigo-Clavero, M., Cassiraga, E., Vargas-Guzmán, J. (eds) Geostatistics Valencia 2016. Quantitative Geology and Geostatistics, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-319-46819-8_42
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DOI: https://doi.org/10.1007/978-3-319-46819-8_42
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