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- W3201979025 abstract "Summary Fractures are important for reservoir characterization and development. In this paper, we present a new method of Bayesian linearized inversion to invert aspect ratio and fracture density for a quantitative description of fractured reservoirs. The first-order Hudson’s model is linearized based on the Taylor series expansion. Moreover, the model parameters and data error are assumed to be Gaussian distributed. Then the posterior distribution of model parameters can be explicitly expressed and computed analytically. The proposed approach is demonstrated on a synthetic study in which a fractured model is built based on a thin-section micrograph. The inverted rock velocities are used as the inputs for the prediction of fracture parameters and at the same time the estimation uncertainty analysis is performed by the proposed Bayesian scheme." @default.
- W3201979025 created "2021-10-11" @default.
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- W3201979025 date "2021-01-01" @default.
- W3201979025 modified "2023-09-23" @default.
- W3201979025 title "Bayesian linearized inversion of aspect ratio and fracture density based on seismic inversion" @default.
- W3201979025 doi "https://doi.org/10.3997/2214-4609.202113225" @default.
- W3201979025 hasPublicationYear "2021" @default.
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