Up-Scaling Two-Phase Flow in Heterogeneous Reservoirs: Current Trends

Artus, Vincent; Nœtinger, B.

doi:10.2516/ogst:2004014

Cited by 22 publications

(14 citation statements)

References 59 publications

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“…Unfortunately the domains, on which these assumptions are valid, are generally unknown or limited to small parts of the reservoir (Virnovsky et al 2004). For a more detail description of dynamic upscaling methods, see e.g., Kyte & Berry (1975), Barker & Thibeau (1997), Christie (2001), Darman et al (2002), and Artus & Noetinger (2004), and for the steadystate techniques see e.g., Dale et al (1997), Ekrann & Aasen (2000), Pickup & Stephen (2000) and Virnovsky et al (2004).…”

Section: Single-and Two-phase Upscalingmentioning

confidence: 99%

Control-Relevant Upscaling

Vakili-Ghahani

2009

SPE Journal

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Summary The conventional reason for upscaling in reservoir simulation is the computational limit of the simulator. However, we argue that, from a system-theoretical point of view, a more fundamental reason is that there is only a limited amount of information (output) that can be observed from production data, while there is also a limited amount of control (input) that can be exercised by adjusting the well parameters; in other words, the input/output behavior is usually of much lower dynamical order than the number of grid-blocks in the model. Therefore, we propose an upscaling approach to find a coarse model that optimally describes the input/output behavior of a reservoir system. In this control-relevant method, the coarse-scale-model parameters are calculated as the solution of an optimization problem that minimizes the distance between the input/output behaviors of the fine- and coarse-scale models. This distance is measured with the aid of the Hankel or energy norms, in which we use Hankel singular values as a measure of the combined controllability and observability and Markov parameters as a measure of the response of the system, respectively. The method is particularly attractive to scale up simulation models in flooding-optimization or history-matching studies for a given configuration of wells. An advantage of our upscaling method is that it relies most heavily on those parameter values that directly influence the input/output behavior. It is a global method in the sense that it relies on the system properties of the entire reservoir. It does not, however, require any forward simulation, either of the full or of the upscaled model. It also does not depend on a particular control strategy but instead uses the dynamical system equations directly. Its dependency on well locations, however, implies that it should be (partially) repeated when those locations are changed. We tested the method on several examples and, for nearly all cases, obtained coarse-scale models with a superior input/output behavior compared to common upscaling algorithms.

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Section: Single-and Two-phase Upscalingmentioning

confidence: 99%

Control-Relevant Upscaling

Vakili-Ghahani

2009

SPE Journal

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“…This process is crucial because the geological models usually have too many grid blocks (e.g., 10 7 -10 8 ) for use in typical flow simulators [28]. Numerous upscaling methods have been mentioned in the literature [29][30][31][32][33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

“…The upscaled models with fewer grid blocks have higher computational speed, but less accurate results. The related error has its origin in 2 different sources; the numerical dispersion and the loss of some heterogeneity levels [31]. The former is reflected in replacing a continuous model with a discretized one to solve the governing flow equations.…”

Section: Introductionmentioning

confidence: 99%

Study of heterogeneity loss in upscaling of geological maps by introducing a cluster-based heterogeneity number

Ganjeh-Ghazvini

Masihi

Baghalha

2015

Physica A: Statistical Mechanics and its Applications

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“…In this approach, we solve the pressure equation on the coarse mesh (scale) using upscaled properties, while fine mesh (scale) is used during the saturation update. This technique improves the precision of fluid recovery estimates compared to the conventional coarse-grid simulation while using considerably less processing time and memory than a full fine-grid simulation [26][27][28].…”

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confidence: 96%

Improved upscaling of reservoir flow using combination of dual mesh method and vorticity-based gridding

et al. 2008

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International audienceA novel technique for upscaling of detailed geological reservoir descriptions is presented. The technique aims at reducing both numerical dispersion and homogenization error generated due to incorporating a coarse computational grid and assigning effective permeability to coarse-grid blocks, respectively. In particular, we consider implicit-pressure explicit-saturation scheme where homogenization error impacts the accuracy of the coarse-grid solution of the pressure equation. To reduce the homogenization error, we employ the new vorticity-based gridding that generates a non-uniform coarse grid with high resolution at high vorticity zones. In addition, to control numerical dispersion, we use dual mesh method (DMM) which uses different grids to solve pressure and saturation equations. The coarse grid generated from vorticity is used for computation of pressure, and the reference fine grid is used for updating saturation explicitly. The strongest point of the method is that dual mesh method has been incorporated onto non-uniform grid structure. This combination removes the need to solve the full fine grid for two-phase flow modeling, resulting in a less computationally demanding and more accurate upscaling technique. To evaluate the method, we run two-phase simulation using different 2D test cases. Our results indicate that the non-uniform DMM is more accurate than the uniform DMM due to using vorticity-based grids. The speedup achieved in the computation is significant depending on the complexity of model and degree of upscaling

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Up-Scaling Two-Phase Flow in Heterogeneous Reservoirs: Current Trends

Cited by 22 publications

References 59 publications

Control-Relevant Upscaling

Control-Relevant Upscaling

Study of heterogeneity loss in upscaling of geological maps by introducing a cluster-based heterogeneity number

Improved upscaling of reservoir flow using combination of dual mesh method and vorticity-based gridding

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