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A novel approach for subsurface characterization of coupled fluid flow and geomechanical deformation: the case of slightly compressible flows

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Abstract

We are concerned with stochastic methods for predictive simulations of flows in the subsurface that can incorporate dynamical data (such as pressure data and production curves in field-scale operations) to reduce uncertainty in determining time-dependent subsurface properties such as absolute permeability, porosity and Young’s modulus in the context of poroelasticity. There exists a considerable amount of work in the development of these methods with focus on rigid porous media. Procedures such as Markov chain Monte Carlo methods and Kalman filters have been considered for rock characterization and Monte Carlo simulations applied for predicting fluid flow. This is not the case with deformable subsurface formations. Although clearly relevant for the exploration of oil and gas, considerably less developments have been reported in this case. Difficulty arises because subsurface properties (typically modeled by time-independent random fields) change with time and known uncertainty quantification and reduction methods may not be directly applicable. Our goal here is the development of a Bayesian modeling framework that allows for the characterization of time-dependent rock properties along with the prediction of multiphase flows in such formations. The proposed framework has performed well to characterize time-dependent porosity and permeability fields in single-phase flows in heterogeneous deformable media, considering the concept of rock compressibility. Despite its simplicity, this problem gathers several characteristics of more complex models currently employed in the coupling of fluid flow and mechanical response of the reservoir solid structure.

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Funding

This work is partially supported by grants from NSF-DMS1514808, the University of Texas at Dallas and CNPq - Brazil (237760/2012-6 and 400169/2014-2).

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Authors and Affiliations

  1. LNCC - National Laboratory for Scientific Computing, Av. Getulio Vargas, 333, Quitandinha - Petropolis, RJ, 25651-075, Brazil

    M. R. Borges

  2. UT Dallas - Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX, 75080, USA

    F. Pereira

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  1. M. R. Borges
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  2. F. Pereira
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Correspondence to M. R. Borges.

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Borges, M.R., Pereira, F. A novel approach for subsurface characterization of coupled fluid flow and geomechanical deformation: the case of slightly compressible flows. Comput Geosci 24, 1693–1706 (2020). https://doi.org/10.1007/s10596-020-09980-3

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