共查询到20条相似文献，搜索用时 31 毫秒
1.
Alexandre Boucher 《Mathematical Geosciences》2009,41(3):265-290
Super-resolution or sub-pixel mapping is the process of providing fine scale land cover maps from coarse-scale satellite sensor
information. Such a procedure calls for a prior model depicting the spatial structures of the land cover types. When available,
an analog of the underlying scene (a training image) may be used for such a model. The single normal equation simulation algorithm
(SNESIM) allows extracting the relevant pattern information from the training image and uses that information to downscale
the coarse fraction data into a simulated fine scale land cover scene. Two non-exclusive approaches are considered to use
training images for super-resolution mapping. The first one downscales the coarse fractions into fine-scale pre-posterior
probabilities which is then merged with a probability lifted from the training image. The second approach pre-classifies the
fine scale patterns of the training image into a few partition classes based on their coarse fractions. All patterns within
a partition class are recorded by a search tree; there is one tree per partition class. At each fine scale pixel along the
simulation path, the coarse fraction data is retrieved first and used to select the appropriate search tree. That search tree
contains the patterns relevant to that coarse fraction data. To ensure exact reproduction of the coarse fractions, a servo-system
keeps track of the number of simulated classes inside each coarse fraction. Being an under-determined stochastic inverse problem,
one can generate several super resolution maps and explore the space of uncertainty for the fine scale land cover. The proposed
SNESIM sub-pixel resolution mapping algorithms allow to: (i) exactly reproduce the coarse fraction, (ii) inject the structural
model carried by the training image, and (iii) condition to any available fine scale ground observations. Two case studies
are provided to illustrate the proposed methodology using Landsat TM data from southeast China. 相似文献
2.
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
3.
4.
The present paper proposes a new family of multiscale finite volume methods. These methods usually deal with a dual mesh resolution, where the pressure field is solved on a coarse mesh, while the saturation fields, which may have discontinuities, are solved on a finer reservoir grid, on which petrophysical heterogeneities are defined. Unfortunately, the efficiency of dual mesh methods is strongly related to the definition of up-gridding and down-gridding steps, allowing defining accurately pressure and saturation fields on both fine and coarse meshes and the ability of the approach to be parallelized. In the new dual mesh formulation we developed, the pressure is solved on a coarse grid using a new hybrid formulation of the parabolic problem. This type of multiscale method for pressure equation called multiscale hybrid-mixed method (MHMM) has been recently proposed for finite elements and mixed-finite element approach (Harder et al. 2013). We extend here the MH-mixed method to a finite volume discretization, in order to deal with large multiphase reservoir models. The pressure solution is obtained by solving a hybrid form of the pressure problem on the coarse mesh, for which unknowns are fluxes defined on the coarse mesh faces. Basis flux functions are defined through the resolution of a local finite volume problem, which accounts for local heterogeneity, whereas pressure continuity between cells is weakly imposed through flux basis functions, regarded as Lagrange multipliers. Such an approach is conservative both on the coarse and local scales and can be easily parallelized, which is an advantage compared to other existing finite volume multiscale approaches. It has also a high flexibility to refine the coarse discretization just by refinement of the lagrange multiplier space defined on the coarse faces without changing nor the coarse nor the fine meshes. This refinement can also be done adaptively w.r.t. a posteriori error estimators. The method is applied to single phase (well-testing) and multiphase flow in heterogeneous porous media. 相似文献
5.
In this paper, we present a numerical model for simulating two-phase (oil–water and air–water) incompressible and immiscible flow in porous media. The mathematical model which is based on a fractional flow formulation is formed of two nonlinear partial differential equations: a mean pressure equation and a water saturation equation. These two equations can be solved in a sequential manner. Two numerical methods are used to discretize the equations of the two-phase flow model: mixed hybrid finite elements are used to treat the pressure equation, h-based Richards' equation and the diffusion term in the saturation equation, the advection term in the saturation equation is treated with the discontinuous finite elements. We propose a better way to calculate the nonlinear coefficients contained in our equations on each element of the discretized domain. In heterogeneous porous media, the saturation becomes discontinuous at the interface between two porous media. We show in this paper how to use the capillary pressure–saturation relationship in order to handle the saturation jump in the mixed hybrid finite element method. The two-phase flow simulator is verified against analytical solutions for some flow problems treated by other authors. 相似文献
6.
Implementation of a Locally Conservative Numerical Subgrid Upscaling Scheme for Two-Phase Darcy Flow 总被引：1，自引：0，他引：1
Todd Arbogast 《Computational Geosciences》2002,6(3-4):453-481
We present a locally mass conservative scheme for the approximation of two-phase flow in a porous medium that allows us to obtain detailed fine scale solutions on relatively coarse meshes. The permeability is assumed to be resolvable on a fine numerical grid, but limits on computational power require that computations be performed on a coarse grid. We define a two-scale mixed finite element space and resulting method, and describe in detail the solution algorithm. It involves a coarse scale operator coupled to a subgrid scale operator localized in space to each coarse grid element. An influence function (numerical Greens function) technique allows us to solve these subgrid scale problems independently of the coarse grid approximation. The coarse grid problem is modified to take into account the subgrid scale solution and solved as a large linear system of equations posed over a coarse grid. Finally, the coarse scale solution is corrected on the subgrid scale, providing a fine grid representation of the solution. Numerical examples are presented, which show that near-well behavior and even extremely heterogeneous permeability barriers and streaks are upscaled well by the technique. 相似文献
7.
A multiscale method for the dynamic analysis of underground structures is proposed, which involves the concurrent discretization of the entire domain with both coarse‐scale and fine‐scale finite element meshes. The coarse‐scale mesh is employed to capture seismic response characteristics of the integral system, whereas the fine‐scale mesh describes in detail the dynamic response in positions of potential damage or interest. For both the coarse‐scale and fine‐scale meshes to overlap, a bridging scale term is introduced so that compatibility of dynamic behavior between the coarse‐ and fine‐scale models is enforced. Both material and contact nonlinearities are considered in the multiscale model. As an application, the model is used for large‐scale seismic response of a newly built long‐distance shield tunnel. Results show that this multiscale method does not have spurious wave reflections at the fine/coarse interface and does not need filtering procedures, which is an advantage compared with the displacement coupling method. Stress and deformation response in lining segments and their connecting bolts are investigated and analyzed within the fine‐scale model, and the capacity of critical structural components, such as bolts and joints is evaluated. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
8.
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
9.
In this paper we study the problem of determining the effective permeability on a coarse scale level of problems with strongly
varying and discontinuous coefficients defined on a fine scale. The upscaled permeability is defined as the solution of an
optimization problem, where the difference between the fine scale and the coarse scale velocity field is minimized. We show
that it is not necessary to solve the fine scale pressure equation in order to minimize the associated cost‐functional. Furthermore,
we derive a simple technique for computing the derivatives of the cost‐functional needed in the fix‐point iteration used to
compute the optimal permeability on the coarse mesh. Finally, the method is illustrated by several analytical examples and
numerical experiments.
This revised version was published online in July 2006 with corrections to the Cover Date. 相似文献
10.
The problem of multiphase phase flow in heterogeneous subsurface porous media is one involving many uncertainties. In particular, the permeability of the medium is an important aspect of the model that is inherently uncertain. Properly quantifying these uncertainties is essential in order to make reliable probabilistic-based predictions and future decisions. In this work, a measure-theoretic framework is employed to quantify uncertainties in a two-phase subsurface flow model in high-contrast media. Given uncertain saturation data from observation wells, the stochastic inverse problem is solved numerically in order to obtain a probability measure on the space of unknown permeability parameters characterizing the two-phase flow. As solving the stochastic inverse problem requires a number of forward model solves, we also incorporate the use of a conservative version of the generalized multiscale finite element method for added efficiency. The parameter-space probability measure is used in order to make predictions of saturation values where measurements are not available, and to validate the effectiveness of the proposed approach in the context of fine and coarse model solves. A number of numerical examples are offered to illustrate the measure-theoretic methodology for solving the stochastic inverse problem using both fine and coarse solution schemes. 相似文献
12.
Computational fluid dynamics and discrete element method (CFD–DEM) is extended with the volume of fluid (VOF) method to model free‐surface flows. The fluid is described on coarse CFD grids by solving locally averaged Navier–Stokes equations, and particles are modelled individually in DEM. Fluid–particle interactions are achieved by exchanging information between DEM and CFD. An advection equation is applied to solve the phase fraction of liquid, in the spirit of VOF, to capture the dynamics of free fluid surface. It also allows inter‐phase volume replacements between the fluid and solid particles. Further, as the size ratio (SR) of fluid cell to particle diameter is limited (i.e. no less than 4) in coarse‐grid CFD–DEM, a porous sphere method is adopted to permit a wider range of particle size without sacrificing the resolution of fluid grids. It makes use of more fluid cells to calculate local porosities. The developed solver (cfdemSolverVOF) is validated in different cases. A dam break case validates the CFD‐component and VOF‐component. Particle sedimentation tests validate the CFD–DEM interaction at various Reynolds numbers. Water‐level rising tests validate the volume exchange among phases. The porous sphere model is validated in both static and dynamic situations. Sensitivity analyses show that the SR can be reduced to 1 using the porous sphere approach, with the accuracy of analyses maintained. This allows more details of the fluid phase to be revealed in the analyses and enhances the applicability of the proposed model to geotechnical problems, where a highly dynamic fluid velocity and a wide range of particle sizes are encountered. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
13.
Multiscale mixed/mimetic methods on corner-point grids 总被引：1，自引：0，他引：1
Multiscale simulation is a promising approach to facilitate direct simulation of large and complex grid models for highly
heterogeneous petroleum reservoirs. Unlike traditional simulation, approaches based on upscaling/downscaling, multiscale methods
seek to solve the full flow problem by incorporating subscale heterogeneities into local discrete approximation spaces. We
consider a multiscale formulation based on a hierarchical grid approach, where basis functions with subgrid resolution are
computed numerically to correctly and accurately account for subscale variations from an underlying (fine-scale) geomodel
when solving the global flow equations on a coarse grid. By using multiscale basis functions to discretise the global flow
equations on a (moderately sized) coarse grid, one can retain the efficiency of an upscaling method and, at the same time,
produce detailed and conservative velocity fields on the underlying fine grid. For pressure equations, the multiscale mixed
finite-element method (MsMFEM) has been shown to be a particularly versatile approach. In this paper, we extend the method
to corner-point grids, which is the industry standard for modelling complex reservoir geology. To implement MsMFEM, one needs
a discretisation method for solving local flow problems on the underlying fine grids. In principle, any stable and conservative
method can be used. Here, we use a mimetic discretisation, which is a generalisation of mixed finite elements that gives a
discrete inner product, allows for polyhedral elements, and can (easily) be extended to curved grid faces. The coarse grid
can, in principle, be any partition of the subgrid, where each coarse block is a connected collection of subgrid cells. However,
we argue that, when generating coarse grids, one should follow certain simple guidelines to achieve improved accuracy. We
discuss partitioning in both index space and physical space and suggest simple processing techniques. The versatility and
accuracy of the new multiscale mixed methodology is demonstrated on two corner-point models: a small Y-shaped sector model
and a complex model of a layered sedimentary bed. A variety of coarse grids, both violating and obeying the above mentioned
guidelines, are employed. The MsMFEM solutions are compared with a reference solution obtained by direct simulation on the
subgrid. 相似文献
14.
Luz Angélica Caudillo-Mata Eldad Haber Christoph Schwarzbach 《Computational Geosciences》2017,21(5-6):963-980
In order to reduce the computational cost of the simulation of electromagnetic responses in geophysical settings that involve highly heterogeneous media, we develop a multiscale finite volume method with oversampling for the quasi-static Maxwell’s equations in the frequency domain. We assume a coarse mesh nested within a fine mesh that accurately discretizes the problem. For each coarse cell, we independently solve a local version of the original Maxwell’s system subject to linear boundary conditions on an extended domain, which includes the coarse cell and a neighborhood of fine cells around it. The local Maxwell’s system is solved using the fine mesh contained in the extended domain and the mimetic finite volume method. Next, these local solutions (basis functions) together with a weak-continuity condition are used to construct a coarse-mesh version of the global problem. The basis functions can be used to obtain the fine-mesh details from the solution of the coarse-mesh problem. Our approach leads to a significant reduction in the size of the final system of equations and the computational time, while accurately approximating the behavior of the fine-mesh solutions. We demonstrate the performance of our method using two 3D synthetic models: one with a mineral deposit in a geologically complex medium and one with random isotropic heterogeneous media. Both models are discretized using an adaptive mesh refinement technique. 相似文献
15.
The reduction in volume for unsaturated soils wetted at constant total stress is indicated as capillary collapse. Several studies conducted on standard laboratory specimens (macro-scale) outlined the role of initial void ratio, confining pressure and matric suction on collapse onset. Conversely, few observations were made at grain scale, although an important influence of soil structure has been supposed since years. This paper investigated the collapse of coarse and fine sands derived from a pyroclastic soil of Southern Italy. The X-ray computed tomography was used to identify the mechanisms acting at grain scale and to measure the local variations of soil structure. The experimental procedure consisted in preparing remoulded unsaturated specimens and reducing the matric suction until the collapse occurred under self-weight. At different stages of the process, the sample was imaged by X-ray tomography. The experimental results provided original insight into: (1) transformation of soil structure during the wetting tests; (2) variation of porosity, water content and degree of saturation for the whole specimen; and (3) local variations of those variables in several representative sub-volumes. It is worth noting that collapse of coarse sand specimen occurred before saturation. This was also emphasized by the presence of macro-voids at collapse. 相似文献
16.
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
17.
The hydro-mechanical behaviour of a clay-based buffer material for nuclear waste disposal has been investigated in a laboratory program. In this program, the main focus was on the influence of confinement on water uptake and swelling pressure during suction decrease. The laboratory program and some of the results are presented by Dueck [Dueck, A., 2006. Laboratory results from hydro-mechanical tests on a water unsaturated bentonite. submitted for publication.].
The results from the laboratory tests were used to find a relationship between water content, void ratio, swelling pressure and suction. Two equations for swelling pressure represent the outline of the model.
In the first equation, the swelling pressure developed during water uptake is normalised by a pressure corresponding to the swelling pressure at saturation. This is done in order to be independent of void ratio. A relationship between the normalised swelling pressure and the degree of saturation is suggested.
The second equation describes a relationship between the swelling pressure, the water content and the actual suction (or relative humidity). The equation is based on a thermodynamic relationship and includes the retention curve (i.e. water content vs. suction under free swelling conditions).
The model can be used for a state where two of the four variables; water content, void ratio, swelling pressure and suction are known and can thus be useful to evaluate field measurements and model late stages of the wetting process. An example of an application is given. The equations are mainly based on results from tests with increasing degrees of saturation under constant void ratio but are also suggested for use with increasing void ratio. 相似文献
18.
19.
The prediction of fluid flows within hydrocarbon reservoirs requires the characterization of petrophysical properties. Such characterization is performed on the basis of geostatistics and history-matching; in short, a reservoir model is first randomly drawn, and then sequentially adjusted until it reproduces the available dynamic data. Two main concerns typical of the problem under consideration are the heterogeneity of rocks occurring at all scales and the use of data of distinct resolution levels. Therefore, referring to sequential Gaussian simulation, this paper proposes a new stochastic simulation method able to handle several scales for both continuous or discrete random fields. This method adds flexibility to history-matching as it boils down to the multiscale parameterization of reservoir models. In other words, reservoir models can be updated at either coarse or fine scales, or both. Parameterization adapts to the available data; the coarser the scale targeted, the smaller the number of unknown parameters, and the more efficient the history-matching process. This paper focuses on the use of variational optimization techniques driven by the gradual deformation method to vary reservoir models. Other data assimilation methods and perturbation processes could have been envisioned as well. Last, a numerical application case is presented in order to highlight the advantages of the proposed method for conditioning permeability models to dynamic data. For simplicity, we focus on two-scale processes. The coarse scale describes the variations in the trend while the fine scale characterizes local variations around the trend. The relationships between data resolution and parameterization are investigated. 相似文献
20.
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