Accurate coarse modeling of well-driven, high-mobility-ratio displacements in heterogeneous reservoirs

Hui, Mun-Hong; Durlofsky, Louis J.

doi:10.1016/j.petrol.2005.07.004

Cited by 20 publications

(17 citation statements)

References 22 publications

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“…We employ the methodology presented in [20,24] to compute the upscaled single-and two-phase flow parameters in the near-well region. In regions away from wells, standard local permeability upscaling and a specialized local two-phase upscaling approach are applied.…”

Section: Flow-based Upscaling Proceduresmentioning

confidence: 99%

“…Well block relative permeabilities (k w rj ) * are then computed through an optimization procedure analogous to that outlined above. As described in [20], the optimization provides (k w rj ) * curves that ensure agreement in oil and water well rates on the fine and coarse scales. We denote as θ the set of coarse-scale well block relative permeability functions:…”

Section: Upscaling In Near-well Regionsmentioning

confidence: 99%

“…In [20], it was demonstrated that, for oil-water systems, the computation of (k w rj ) * was most important for injection well blocks, particularly for cases with high mobility ratios. Much less impact was observed when (k w rj ) * was computed for production well blocks.…”

Section: Upscaling In Near-well Regionsmentioning

confidence: 99%

“…The coarse-scale saturation S c is also computed by averaging the fine-scale saturations on the outlet face of the coarse block [20]. Upscaled relative perme-…”

Section: Upscaling In Inter-well Regionsmentioning

confidence: 99%

“…For Gaussian permeability fields, Hui and Durlofsky [20] showed that the combined use of the specialized near-well (k w rj ) * with EFBC k * rj in interwell regions provided accurate coarse-scale models for well-driven flow. In these upscaling calculations, the computation of the inter-well k * rj represents the most time-consuming part, as it entails solving timedependent two-phase flow for each coarse block (except the well blocks) in the entire domain, with each simulation repeated for flow driven in the x, y and z directions.…”

Section: Upscaling In Inter-well Regionsmentioning

confidence: 99%

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Statistical assignment of upscaled flow functions for an ensemble of geological models

2010

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Upscaled flow functions are often needed to account for the effects of fine-scale permeability heterogeneity in coarse-scale simulation models. We present procedures in which the required coarse-scale flow functions are statistically assigned to an ensemble of upscaled geological models. This can be viewed as an extension and further development of a recently developed ensemble level upscaling (EnLU) approach. The method aims to efficiently generate coarse-scale flow models capable of reproducing the ensemble statistics (e.g., cumulative distribution function) of finescale flow predictions for multiple reservoir models. The most expensive part of standard coarsening procedures is typically the generation of upscaled two-phase flow functions (e.g., relative permeabilities). EnLU provides a means for efficiently generating these upscaled functions using stochastic simulation. This involves the use of coarse-block attributes that are both fast to compute and correlate closely with the upscaled two-phase functions. In this paper, improved attributes for use in EnLU, namely the coefficient of variation of the fine-scale single-phase velocity field (computed during computation of upscaled absolute permeability) and the integral range of the fine-scale permeability variogram, are identified. Geostatistical simulation methods, which account for spatial correlations of Y. Chen (B) Chevron Energy Technology Company, the statistically generated upscaled functions, are also applied. The overall methodology thus enables the efficient generation of coarse-scale flow models. The procedure is tested on 3D well-driven flow problems with different permeability distributions and variable fluid mobility ratios. EnLU is shown to capture the ensemble statistics of fine-scale flow results (water and oil flow rates as a function of time) with similar accuracy to full flow-based upscaling methods but with computational speedups of more than an order of magnitude.

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Section: Flow-based Upscaling Proceduresmentioning

confidence: 99%

Section: Upscaling In Near-well Regionsmentioning

confidence: 99%

Section: Upscaling In Near-well Regionsmentioning

confidence: 99%

“…The coarse-scale saturation S c is also computed by averaging the fine-scale saturations on the outlet face of the coarse block [20]. Upscaled relative perme-…”

Section: Upscaling In Inter-well Regionsmentioning

confidence: 99%

Section: Upscaling In Inter-well Regionsmentioning

confidence: 99%

See 3 more Smart Citations

Statistical assignment of upscaled flow functions for an ensemble of geological models

2010

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Uncertainty Quantification for Subsurface Flow Problems Using Coarse-Scale Models

Durlofsky

Chen

2011

Lecture Notes in Computational Science and Engineering

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Near-well upscaling for three-phase flows

Nakashima

Durlofsky

2011

Comput Geosci

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Large-scale flow models constructed using standard coarsening procedures may not accurately resolve detailed near-well effects. Such effects are often important to capture, however, as the interaction of the well with the formation can have a dominant impact on process performance. In this work, a near-well upscaling procedure, which provides three-phase wellblock properties, is developed and tested. The overall approach represents an extension of a recently developed oil-gas upscaling procedure and entails the use of local well computations (over a region referred to as the local well model (LWM)) along with a gradient-based optimization procedure to minimize the mismatch between fine and coarse-scale well rates, for oil, gas, and water, over the LWM. The gradients required for the minimization are computed efficiently through solution of adjoint equations. The LWM boundary conditions are determined using an iterative local-global procedure. With this approach, pressures and saturations computed during a global coarse-scale simulation are interpolated onto LWM boundaries and then used as boundary conditions for the fine-scale LWM computations. In addition to extending the overall approach to the three-phase case, this work also introduces new treatments that provide improved accuracy in cases with significant flux from the gas cap into the well block. The near-well multiphase upscaling method is applied to heterogeneous reservoir models, with production from vertical and horizontal wells. Simulation results illustrate that the method is able to accurately capture key near-well effects and to provide predictions for component production rates that are in close agreement with reference fine-scale results. The level of accuracy of the procedure is shown to be significantly higher than that of a standard approach which uses only upscaled single-phase flow parameters.

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Accurate coarse modeling of well-driven, high-mobility-ratio displacements in heterogeneous reservoirs

Cited by 20 publications

References 22 publications

Statistical assignment of upscaled flow functions for an ensemble of geological models

Statistical assignment of upscaled flow functions for an ensemble of geological models

Uncertainty Quantification for Subsurface Flow Problems Using Coarse-Scale Models

Near-well upscaling for three-phase flows

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