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- W2054452016 abstract "This paper describes a novel algorithm for the joint stochastic inversion of well logs and multiple angle stacks of migrated 3D pre-stack seismic data. The inversion algorithm is based on a Bayesian statistical search criterion implemented with fast Markov-Chain Monte Carlo updates. It implements a-priori measures of spatial correlation as well as specific geometrical properties of structural and stratigraphic embedding. Results consist of spatial distributions of elastic properties with a vertical resolution intermediate between that of seismic amplitude data and well logs. In addition, the algorithm provides quantitative estimates of non-uniqueness based on the statistical distribution of multiple spatial realizations derived from random initial models. It is also possible to estimate lithology and petrophysical properties such as porosity and water saturation by enforcing multi-dimensional statistical correlations between elastic and petrophysical properties sampled from well-log measurements." @default.
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- W2054452016 date "2005-01-01" @default.
- W2054452016 modified "2023-10-17" @default.
- W2054452016 title "Joint stochastic inversion of 3D pre‐stack seismic data and well logs for high‐resolution reservoir characterization and petrophysical modeling: application to deepwater hydrocarbon reservoirs in the central Gulf of Mexico" @default.
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- W2054452016 doi "https://doi.org/10.1190/1.2147935" @default.
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