... tetrahedral grid grid discretization representation transmissibility modeling & simulation reservoir simulation tetrahedral mesh cartesian grid freedom unstructured grid petroleum engineer Introduction Numerical simulations of multiphase flow and transport in porous media are essential...

... systems. enhanced recovery reservoir characterization subsurface storage reservoir simulation climate change scientific computing information representation petroleum engineer library coupling lawrence livermore national laboratory modeling & simulation structural geology co 2...

... Abstract We present a deep learning architecture for efficient reduced-order implementation of ensemble data assimilation. Specifically, deep learning is used to improve two important aspects of data assimilation workflows: (i) low-rank representation of complex reservoir property distributions...

... challenges to achieve improved upscaled models for immiscible and miscible gas displacement conditions with a stepwise workflow. We first identify the need for a special permeability upscaling technique to improve the representation of the main reservoir heterogeneities and sub-grid features, smoothed during...

... propagation. This extends the capabilities of many legacy reservoir simulators to handle more physics. Artificial Intelligence complex reservoir scientific computing Fluid Dynamics hydraulic fracturing concentration reservoir simulator geomechanics representation fracture network velocity...

... matching using DFO. A multilevel strategy lends itself quite naturally to PCA-based parameterizations because the PCA representation can be ordered from most-important to least-important principal component. Thus PCA parameters can be determined sequentially, level by level (in groups), rather than all...

.... Building on the work of Afra and Gildin (2013) ; Afra et.al. (2014) ; Afra and Gildin (2016) , permeability fields of multiple model realizations are collected in a tensor form which is subsequently decomposed to derive a low-dimensional representation of the dominant spatial structures in the models...

... of coarser models to improve the run-time of forward solution without significant reduction in accuracy. We applied coarsening in time, space, and chemical representation, and quantify errors introduced at each coarsening level. In conclusion, we provided recommendations for large scale modeling of in-situ...

... of a simulation problem, which is similar to an approximate representation of space and time discretization performed in conventional simulation. Maintaining control of the error in approximate physics, we perform an adaptive parametrization to improve the performance of the method and adaptive coarsening...

... the tensor-based techniques that are presently used to find compact representations of high-dimensional data structures. We discuss visualization techniques for high dimensional data and give an overview of a technique for production optimization under uncertainty. Classical Singular Value Decomposition...

... + 1 − Λ ¯ n + 1 Abstract We present a new, high-order, control-volume-finite-element (CVFE) method with discontinuous Nth-order representation for pressure and (N+1)th-order for velocity. The method conserves mass and ensures that the extended Darcy equations for multi-phase...

...-assisted optimisation technique with three novel aspects: (1) it relies on an ANOVA-like decomposition termed High-Dimensional Model Representation; (2) component-wise interactions are approximated with adaptive sparse grid interpolation; and (3) the surrogate is adaptively partitioned closer...

... reservoir simulation symposium workflow Artificial Intelligence real space conceptual region geological modeling Upstream Oil & Gas truncation Reservoir Characterization continuous space simulation grid geometry complexity geologic complexity structural framework representation...

.... In ( Khaninezhad et al., 2012a ), we introduced the concept of sparse geologic dictionaries for flexible and compact representation of prior models with complex geologic connectivity patterns. Such dictionaries are learned from a collection of prior models and are sparse. In here, sparsity of the dictionary...

..., but can otherwise be treated within a similar framework. We utilize the framework for permeability representation from Müller et al. (2011) with analytical expressions for λ n and f n ( x ) for the covariance function (3). In cases where analytical expressions are not available, one has to compute...

... to convert the discrete natural/hydraulic fractures into a data set to be used by the simulator, which allows more realistic representation of fractured reservoirs. Compared to previous studies, the developed preprocessing code introduces additional features to better represent structural properties...

..., POD or DEIM acts as a data filter that additionally aids at designing a more compact RBF network representation suitable for targeting fast reservoir predictions. Numerical results show significant accelerations with respect to running the original simulation model on a set of field-motivated cases...

... as a numerical absorption term with coupled FE and CV representation of the nonlinear convolution of saturation, relative permeabilities, and permeability tensor fields, which is piecewise constant within each FE and is obtained via basis functions local to each CV within each FE. Although this approach...

... method is used with an extended multipoint flux approximation to completely decouple the parameterisation of structural features from their representation on the grid. Using this new technique, we are easily able to history match a 2D synthetic case where we simultaneously vary the top and bottom...

.... This section reviews the fundamental ideas behind polyhedral grid representations and describes the compression strategy that enables us to work with high resolution grids. We begin with the terminology that we use to describe 3D polyhedral grids. Abstract Effective workflows for translating earth...