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Jesus de Moraes, R. (author), Hajibeygi, H. (author), Jansen, J.D. (author)
In data assimilation problems, various types of data are naturally linked to different spatial resolutions (e.g., seismic and electromagnetic data), and these scales are usually not coincident to the subsurface simulation model scale. Alternatives like upscaling/downscaling of the data and/or the simulation model can be used, but with...
journal article 2020
document
Jesus de Moraes, R. (author), de Zeeuw, W. (author), R. P. Rodrigues, José (author), Hajibeygi, H. (author), Jansen, J.D. (author)
We introduce a semi-analytical iterative multiscale derivative computation methodology that allows for error control and reduction to any desired accuracy, up to fine-scale precision. The model responses are computed by the multiscale forward simulation of flow in heterogeneous porous media. The derivative computation method is based on the...
journal article 2019
document
Jesus de Moraes, R. (author), Rodrigues, José R.P. (author), Hajibeygi, H. (author), Jansen, J.D. (author)
A generic framework for the computation of derivative information required for gradient-based optimization using sequentially coupled subsurface simulation models is presented. The proposed approach allows for the computation of any derivative information with no modification of the mathematical framework. It only requires the forward model...
journal article 2018
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Jesus de Moraes, R. (author), Rodrigues, José R P (author), Hajibeygi, H. (author), Jansen, J.D. (author)
An efficient multiscale (MS) gradient computation method for subsurface flow management and optimization is introduced. The general, algebraic framework allows for the calculation of gradients using both the Direct and Adjoint derivative methods. The framework also allows for the utilization of any MS formulation that can be algebraically...
journal article 2017
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