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2016 | OriginalPaper | Chapter

18. Statistical Lobe Hierarchy Constraint in Surface-based Reservoir Modeling

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Abstract

Surface-based geomodeling produces realistic and complex stratigraphy of hydrocarbon reservoirs by imitating the underlying physics with depositional rules. However, conventional rules utilized in surface-based models are designed based on qualitative understandings, which are normally implemented with a large number of tuning parameters. The increment of tuning parameters increases workloads in model conditioning and history matching. Moreover, there is no quantitative criterion to validate reproduction of the qualitative rules in model realizations. This work aims to introduce a set of simple random walk based depositional rules for lobate environments such that the number of empirical coefficients and parameters are minimized while the realism of the model is maintained. A quantitative characterization of the qualitative concept of lobe stacking pattern is also defined based on hierarchical clustering analysis. Demonstrations show that realizations of the new model were hierarchically similar to the input lobe sequence.

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Literature
1.
go back to reference Xu, S.: PhD Dissertation, Integration of Geomorphic Experimental Data in Surface-based Modeling, Stanford University (2014) Xu, S.: PhD Dissertation, Integration of Geomorphic Experimental Data in Surface-based Modeling, Stanford University (2014)
2.
go back to reference Scheidt, C. and Caers, J.: A new method for uncertainty quantification using distances and kernel methods: Application to a deep water turbidite reservoir. SPE J, 14 (4), 680–692. doi:10.2118/118740-PA (2008) Scheidt, C. and Caers, J.: A new method for uncertainty quantification using distances and kernel methods: Application to a deep water turbidite reservoir. SPE J, 14 (4), 680–692. doi:10.​2118/​118740-PA (2008)
Metadata
Title
Statistical Lobe Hierarchy Constraint in Surface-based Reservoir Modeling
Authors
Siyao Xu
Tapan Mukerji
Copyright Year
2016
DOI
https://doi.org/10.1007/978-3-319-18663-4_18