共查询到20条相似文献，搜索用时 890 毫秒
1.
Statistical assignment of upscaled flow functions for an ensemble of geological models 总被引：1，自引：0，他引：1
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 fine-scale 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 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. 相似文献
2.
In subsurface flow modeling, compositional simulation is often required to model complex recovery processes, such as gas/CO 2 injection. However, compositional simulation on fine-scale geological models is still computationally expensive and even prohibitive. Most existing upscaling techniques focus on black-oil models. In this paper, we present a general framework to upscale two-phase multicomponent flow in compositional simulation. Unlike previous studies, our approach explicitly considers the upscaling of flow and thermodynamics. In the flow part, we introduce a new set of upscaled flow functions that account for the effects of compressibility. This is often ignored in the upscaling of black-oil models. In the upscaling of thermodynamics, we show that the oil and gas phases within a coarse block are not at chemical equilibrium. This non-equilibrium behavior is modeled by upscaled thermodynamic functions, which measure the difference between component fugacities among the oil and gas phases. We apply the approach to various gas injection problems with different compositional features, permeability heterogeneity, and coarsening ratios. It is shown that the proposed method accurately reproduces the averaged fine-scale solutions, such as component overall compositions, gas saturation, and density solutions in the compositional flow. 相似文献
3.
The paper is devoted to the upscaling method appropriate for single-phase flow in media with discontinuous permeability distribution.
The suggested algorithm is a modification of the iterative adaptive local–global upscaling developed by Chen and coauthors.
The key feature of this method is a consistency between local and coarse global calculated characteristics. In this work,
we apply a modified procedure to determine the boundary conditions used in the local fine-scale computation. To increase the
accuracy of these boundary conditions on each iteration, we involve an additional preliminary step based on the results of
coarse scale calculations from the previous iteration. Numerical tests show an essential improvement of the accuracy of upscaled
flow rates for most of the realizations of statistical permeability distribution. Although the developed method is universal,
its efficiency increases with increasing of permeability contrast. 相似文献
4.
5.
The use of limited global information in multiscale simulations is needed when there is no scale separation. Previous approaches entail fine-scale simulations in the computation of the global information. The computation of the global information is expensive. In this paper, we propose the use of approximate global information based on partial upscaling. A requirement for partial homogenization is to capture long-range (non-local) effects present in the fine-scale solution, while homogenizing some of the smallest scales. The local information at these smallest scales is captured in the computation of basis functions. Thus, the proposed approach allows us to avoid the computations at the scales that can be homogenized. This results in coarser problems for the computation of global fields. We analyze the convergence of the proposed method. Mathematical formalism is introduced, which allows estimating the errors due to small scales that are homogenized. The proposed method is applied to simulate two-phase flows in heterogeneous porous media. Numerical results are presented for various permeability fields, including those generated using two-point correlation functions and channelized permeability fields from the SPE Comparative Project (Christie and Blunt, SPE Reserv Evalu Eng 4:308–317, 2001). We consider simple cases where one can identify the scales that can be homogenized. For more general cases, we suggest the use of upscaling on the coarse grid with the size smaller than the target coarse grid where multiscale basis functions are constructed. This intermediate coarse grid renders a partially upscaled solution that contains essential non-local information. Numerical examples demonstrate that the use of approximate global information provides better accuracy than purely local multiscale methods. 相似文献
6.
Use of Border Regions for Improved Permeability Upscaling 总被引：1，自引：0，他引：1
A procedure for the improved calculation of upscaled grid block permeability tensors on Cartesian grids is described and applied. The method entails the use of a border region of fine-scale cells surrounding the coarse block for which the upscaled permeability is to be computed. The implementation allows for the use of full-tensor permeability fields on the fine and coarse scales. Either periodic or pressure–no flow boundary conditions are imposed over the extended local domain (target block plus border regions) though averaged quantities, used to compute the upscaled permeability tensor, are computed only over the target block region. Flow and transport results using this procedure are compared to those from standard methods for different types of geological and simulation models. Improvement using the new approach is consistently observed for the cases considered, though the degree of improvement varies for different models and flow quantities. 相似文献
7.
A multi-resolution workflow to generate high-resolution models constrained to dynamic data 总被引：2，自引：0，他引：2
Céline Scheidt Jef Caers Yuguang Chen Louis J. Durlofsky 《Computational Geosciences》2011,15(3):545-563
Distance-based stochastic techniques have recently emerged in the context of ensemble modeling, in particular for history
matching, model selection and uncertainty quantification. Starting with an initial ensemble of realizations, a distance between
any two models is defined. This distance is defined such that the objective of the study is incorporated into the geological
modeling process, thereby potentially enhancing the efficacy of the overall workflow. If the intent is to create new models
that are constrained to dynamic data (history matching), the calculation of the distance requires flow simulation for each
model in the initial ensemble. This can be very time consuming, especially for high-resolution models. In this paper, we present
a multi-resolution framework for ensemble modeling. A distance-based procedure is employed, with emphasis on the rapid construction
of multiple models that have improved dynamic data conditioning. Our intent is to construct new high-resolution models constrained
to dynamic data, while performing most of the flow simulations only on upscaled models. An error modeling procedure is introduced
into the distance calculations to account for potential errors in the upscaling. Based on a few fine-scale flow simulations,
the upscaling error is estimated for each model using a clustering technique. We demonstrate the efficiency of the method
on two examples, one where the upscaling error is small, and another where the upscaling error is significant. Results show
that the error modeling procedure can accurately capture the error in upscaling, and can thus reproduce the fine-scale flow
behavior from coarse-scale simulations with sufficient accuracy (in terms of uncertainty predictions). As a consequence, an
ensemble of high-resolution models, which are constrained to dynamic data, can be obtained, but with a minimum of flow simulations
at the fine scale. 相似文献
8.
We propose a methodology, called multilevel local–global (MLLG) upscaling, for generating accurate upscaled models of permeabilities
or transmissibilities for flow simulation on adapted grids in heterogeneous subsurface formations. The method generates an
initial adapted grid based on the given fine-scale reservoir heterogeneity and potential flow paths. It then applies local–global
(LG) upscaling for permeability or transmissibility [7], along with adaptivity, in an iterative manner. In each iteration of MLLG, the grid can be adapted where needed to reduce
flow solver and upscaling errors. The adaptivity is controlled with a flow-based indicator. The iterative process is continued
until consistency between the global solve on the adapted grid and the local solves is obtained. While each application of
LG upscaling is also an iterative process, this inner iteration generally takes only one or two iterations to converge. Furthermore,
the number of outer iterations is bounded above, and hence, the computational costs of this approach are low. We design a
new flow-based weighting of transmissibility values in LG upscaling that significantly improves the accuracy of LG and MLLG
over traditional local transmissibility calculations. For highly heterogeneous (e.g., channelized) systems, the integration
of grid adaptivity and LG upscaling is shown to consistently provide more accurate coarse-scale models for global flow, relative
to reference fine-scale results, than do existing upscaling techniques applied to uniform grids of similar densities. Another
attractive property of the integration of upscaling and adaptivity is that process dependency is strongly reduced, that is,
the approach computes accurate global flow results also for flows driven by boundary conditions different from the generic
boundary conditions used to compute the upscaled parameters. The method is demonstrated on Cartesian cell-based anisotropic
refinement (CCAR) grids, but it can be applied to other adaptation strategies for structured grids and extended to unstructured
grids. 相似文献
9.
The upscaling process of a high-resolution geostatistical reservoir model to a dynamic simulation grid model plays an important role in a reservoir study. Several upscaling methods have been proposed in order to create balance between the result accuracy and computation speed. Usually, a high-resolution grid model is upscaled according to the heterogeneities assuming single phase flow. However, during injection processes, the relative permeability adjustment is required. The so-called pseudo-relative permeability curves are accepted, if their corresponding coarse model is a good representation of the fine-grid model. In this study, an upscaling method based on discrete wavelet transform (WT) is developed for single-phase upscaling based on the multi-resolution analysis (MRA) concepts. Afterwards, an automated optimization method is used in which evolutionary genetic algorithm is applied to estimate the pseudo-relative permeability curves described with B-spline formulation. In this regard, the formulation of B-spline is modified in order to describe the relative permeability curves. The proposed procedure is evaluated in the gas injection case study from the SPE 10th comparative solution project’s data set which provides a benchmark for upscaling problems [1]. The comparisons of the wavelet-based upscaled model to the high-resolution model and uniformly coarsened model show considerable speedup relative to the fine-grid model and better accuracy relative to the uniformly coarsened model. In addition, the run time of the wavelet-based coarsened model is comparable with the run time of the uniformly upscaled model. The optimized coarse models increase the speed of simulation up to 90% while presenting similar results as fine-grid models. Besides, using two different production/injection scenarios, the superiority of WT upscaling plus relative permeability adjustment over uniform upscaling and relative permeability adjustment is presented. This study demonstrates the proposed upscaling workflow as an effective tool for a reservoir simulation study to reduce the required computational time. 相似文献
10.
Subsurface flow models can exhibit strong full-tensor anisotropy due to either permeability or grid nonorthogonality effects.
Upscaling procedures, for example, generate full-tensor effects on the coarse scale even for cases in which the underlying
fine-scale permeability is isotropic. A multipoint flux approximation (MPFA) is often needed to accurately simulate flow for
such systems. In this paper, we present and apply a different approach, nonlinear two-point flux approximation (NTPFA), for
modeling systems with full-tensor effects. In NTPFA, transmissibility (which provides interblock connections) is determined
from reference global flux and pressure fields for a specific flow problem. These fields can be generated using either fully
resolved or approximate global simulations. The use of fully resolved simulations leads to an NTPFA method that corresponds
to global upscaling procedures, while the use of approximate simulations gives a method corresponding to recently developed
local–global techniques. For both approaches, NTPFA algorithms applicable to both single-scale full-tensor permeability systems
and two-scale systems are described. A unified framework is introduced, which enables single-scale and two-scale problems
to be viewed in a consistent manner. Extensive numerical results demonstrate that the global and local–global NTPFA techniques
provide accurate flow predictions over wide parameter ranges for both single-scale and two-scale systems, though the global
procedure is more accurate overall. The applicability of NTPFA to the simulation of two-phase flow in upscaled models is also
demonstrated. 相似文献
11.
Modern geostatistical techniques allow the generation of high-resolution heterogeneous models of hydraulic conductivity containing millions to billions of cells. Selective upscaling is a numerical approach for the change of scale of fine-scale hydraulic conductivity models into coarser scale models that are suitable for numerical simulations of groundwater flow and mass transport. Selective upscaling uses an elastic gridding technique to selectively determine the geometry of the coarse grid by an iterative procedure. The geometry of the coarse grid is built so that the variances of flow velocities within the coarse blocks are minimum. Selective upscaling is able to handle complex geological formations and flow patterns, and provides full hydraulic conductivity tensor for each block. Selective upscaling is applied to a cross-bedded formation in which the fine-scale hydraulic conductivities are full tensors with principal directions not parallel to the statistical anisotropy of their spatial distribution. Mass transport results from three coarse-scale models constructed by different upscaling techniques are compared to the fine-scale results for different flow conditions. Selective upscaling provides coarse grids in which mass transport simulation is in good agreement with the fine-scale simulations, and consistently superior to simulations on traditional regular (equal-sized) grids or elastic grids built without accounting for flow velocities. 相似文献
12.
Machine-learning-based modeling of coarse-scale error,with application to uncertainty quantification
The use of upscaled models is attractive in many-query applications that require a large number of simulation runs, such as uncertainty quantification and optimization. Highly coarsened models often display error in output quantities of interest, e.g., phase production and injection rates, so the direct use of these results for quantitative evaluations and decision making may not be appropriate. In this work, we introduce a machine-learning-based post-processing framework for modeling the error in coarse-model results in the context of uncertainty quantification. Coarse-scale models are constructed using an accurate global single-phase transmissibility upscaling procedure. The framework entails the use of high-dimensional regression (random forest in this work) to model error based on a number of error indicators or features. Many of these features are derived from approximations of the subgrid effects neglected in the coarse-scale saturation equation. These features are identified through volume averaging, and they are generated by solving a fine-scale saturation equation with a constant-in-time velocity field. Our approach eliminates the need for the user to hand-design a small number of informative (relevant) features. The training step requires the simulation of some number of fine and coarse models (in this work we perform either 10 or 30 training simulations), followed by construction of a regression model for each well. Classification is also applied for production wells. The methodology then provides a correction at each time step, and for each well, in the phase production and injection rates. Results are presented for two- and three-dimensional oil–water systems. The corrected coarse-scale solutions show significantly better accuracy than the uncorrected solutions, both in terms of realization-by-realization predictions for oil and water production rates, and for statistical quantities important for uncertainty quantification, such as P10, P50, and P90 predictions. 相似文献
13.
Dmitry Kolyukhin Sylvie Schueller Magne S. Espedal Haakon Fossen 《Computational Geosciences》2010,14(2):231-248
Fault damage zones in highly porous reservoirs are dominated by deformation bands that generally have permeability-reducing
properties. Due to an absence of sufficiently detailed measurements and the irregular distribution of deformation bands, a
statistical approach is applied to study their influence on flow. A stochastic model of their distribution is constructed,
and band density, distribution, orientation, and flow properties are chosen based on available field observations. The sensitivity
of these different parameters on the upscaled flow is analyzed. The influence of a heterogeneous permeability distribution
was also studied by assuming the presence of high permeability holes within bands. The fragmentation and position of these
holes affect significantly the block-effective permeability. Results of local upscaling with a diagonal and full upscaled
permeability tensor are compared, and qualitatively similar results for the flow characteristics are obtained. Further, the
procedure of iterative local–global upscaling is applied to the problem. 相似文献
14.
Subsurface flows are affected by geological variability over a range of length scales. The modeling of well singularity in
heterogeneous formations is important for simulating flow in aquifers and petroleum reservoirs. In this paper, two approaches
in calculating the upscaled well index to capture the effects of fine scale heterogeneity in near-well regions are presented
and applied. We first develop a flow-based near-well upscaling procedure for geometrically flexible grids. This approach entails
solving local well-driven flows and requires the treatment of geometric effects due to the nonalignment between fine and coarse
scale grids. An approximate coarse scale well model based on a well singularity analysis is also proposed. This model, referred
to as near-well arithmetic averaging, uses only the fine scale permeabilities at well locations to compute the coarse scale
well index; it does not require solving any flow problems. These two methods are systematically tested on three-dimensional
models with a variety of permeability distributions. It is shown that both approaches provide considerable improvement over
a simple (arithmetic) averaging approach to compute the coarse scale well index. The flow-based approach shows close agreement
to the fine scale reference model, and the near-well arithmetic averaging also offers accuracy for an appropriate range of
parameters. The interaction between global flow and near-well upscaling is also investigated through the use of global fine
scale solutions in near-well scale-up calculations. 相似文献
15.
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 well-block 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. 相似文献
16.
Erick R. Burns Larry R. Bentley Rene Therrien Clayton V. Deutsch 《Hydrogeology Journal》2010,18(6):1357-1373
An upscaling algorithm has been developed that generates an irregular coarse grid that preserves flow connectivity by applying a rule-based upscaling algorithm to a fine-scale facies distribution. The algorithm is demonstrated using stochastically generated paleo-fluvial facies distributions. First, an irregular grid honoring the channel facies is created, followed by computation of effective anisotropic parameters for all coarse-grid cells. For the apparent layer-cake geometry of overbank deposits seen in outcrop, two local upscaling methods are compared: (1) the layered system approximation and (2) the mode. To assess upscaling performance, flow simulations for the original and upscaled grids are compared. The horizontal layered approximation (arithmetic mean) performs poorly, over-predicting lateral connectivity where even infrequent disconnection becomes important. Performance of the mode as an upscaling algorithm depends on the probability that a coarse-grid cell will be dominated by a single facies, and it performs surprisingly well because the upscaled grid-generation algorithm honors the channels, informing the upscaling process. Lastly, the irregular coarse grid was compared to a uniform coarse grid, showing superior performance with the irregular grid. The reduction in grid size achieved by irregular-grid generation will be a function of the geometrical complexity of the geologic objects to be honored. 相似文献
17.
The aim of upscaling is to determine equivalent homogeneous parameters at a coarse-scale from a spatially oscillating fine-scale parameter distribution. To be able to use a limited number of relatively large grid-blocks in numerical oil reservoir simulators or groundwater models, upscaling of the permeability is frequently applied. The spatial fine-scale permeability distribution is generally obtained from geological and geostatistical models. After upscaling, the coarse-scale permeabilities are incorporated in the relatively large grid-blocks of the numerical model. If the porous rock may be approximated as a periodic medium, upscaling can be performed by the method of homogenization. In this paper the homogenization is performed numerically, which gives rise to an approximation error. The complementarity between two different numerical methods – the conformal-nodal finite element method and the mixed-hybrid finite element method – has been used to quantify this error. These two methods yield respectively upper and lower bounds for the eigenvalues of the coarse-scale permeability tensor. Results of 3D numerical experiments are shown, both for the far field and around wells. 相似文献
18.
A method for multiscale parameter estimation with application to reservoir history matching is presented. Starting from a
given fine-scale model, coarser models are generated using a global upscaling technique where the coarse models are tuned
to match the solution of the fine model. Conditioning to dynamic data is done by history-matching the coarse model. Using
consistently the same resolution both for the forward and inverse problems, this model is successively refined using a combination
of downscaling and history matching until model-matching dynamic data are obtained at the finest scale. Large-scale corrections
are obtained using fast models, which, combined with a downscaling procedure, provide a better initial model for the final
adjustment on the fine scale. The result is thus a series of models with different resolution, all matching history as good
as possible with this grid. Numerical examples show that this method may significantly reduce the computational effort and/or
improve the quality of the solution when achieving a fine-scale match as compared to history-matching directly on the fine
scale. 相似文献
19.
This paper treats the upscaling of the absolute permeability in a heterogeneous reservoir. By replacing the fine scale permeability tensor with an upscaled, or effective permeability tensor, a modelling error is introduced. An a posteriori error estimate on this modelling error is formulated and tested. An implementation of the theory, based on domain decomposition coupled with a hierarchical representation of the absolute permeability field, is given. As hierarchical basis functions we have chosen the Haar system, which leads to a wavelet representation of the permeability. The wavelet representation offers a natural upscaling technique which resembles the highcut filters commonly used in signal analysis. This procedure represents an adaptive upscaling method. The numerical results show that this method conserves both the dissipation and the mean velocity in the problem fairly well. The a posteriori error estimate on the modelling error coupled with domain decomposition methods constitutes a powerful modelling tool. 相似文献
20.
Knut-Andreas Lie Jostein R. Natvig Stein Krogstad Yahan Yang Xiao-Hui Wu 《Computational Geosciences》2014,18(3-4):357-372
A Dirichlet–Neumann representation method was recently proposed for upscaling and simulating flow in reservoirs. The DNR method expresses coarse fluxes as linear functions of multiple pressure values along the boundary and at the center of each coarse block. The number of flux and pressure values at the boundary can be adjusted to improve the accuracy of simulation results and, in particular, to resolve important fine-scale details. Improvement over existing approaches is substantial especially for reservoirs that contain high-permeability streaks or channels. As an alternative, the multiscale mixed finite-element (MsMFE) method was designed to obtain fine-scale fluxes at the cost of solving a coarsened problem, but can also be used as upscaling methods that are flexible with respect to geometry and topology of the coarsened grid. Both methods can be expressed in mixed-hybrid form, with local stiffness matrices obtained as “inner products” of numerically computed basis functions with fine-scale sub-resolution. These basis functions are determined by solving local flow problems with piecewise linear Dirichlet boundary conditions for the DNR method and piecewise constant Neumann conditions for MsMFE. Adding discrete pressure points in the DNR method corresponds to subdividing faces in the coarse grid and hence increasing the number of basis functions in the MsMFE method. The methods show similar accuracy for 2D Cartesian cases, but the MsMFE method is more straightforward to formulate in 3D and implement for general grids. 相似文献