Abstract
Although object models are popular with geologists due to their ability to control the geometries that are produced, they tend to have convergence issues when conditioning on complex well patterns. In this paper, we present a new well conditioning algorithm that utilizes more local data when generating channels. We show that this algorithm performs better than the currently commercially available state-of-the-art object model and thus makes object models viable in modern mature field well settings.
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Hauge, R., Vigsnes, M., Fjellvoll, B., Vevle, M.L., Skorstad, A. (2017). Object-Based Modeling with Dense Well Data. 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_37
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DOI: https://doi.org/10.1007/978-3-319-46819-8_37
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