Fault-related displacements impact oil and gas flow predictions at reservoir scales. We have integrated a quantitative description of fault-related deformation directly embedded into the st...

/pdf/a-parametric-fault-displacement-model-to-introduce-kinematic-1diezrww8w.pdf

A parametric fault displacement model to introduce kinematic control into modeling faults from sparse data

Subsurface sedimentary structure identification using deep learning: A review

A novel method for simulating multi-phase flow in porous media is presented. The approach is based on a control volume finite element mixed formulation and new force-balanced finite element pairs. The novelty of the method lies in (i) permitting both continuous and discontinuous description of pressure and saturation between elements; (ii) the use of arbitrarily high-order polynomial representation for pressure and velocity and (iii) the use of high-order flux-limited methods in space and time to avoid introducing non-physical oscillations while achieving high-order accuracy where and when possible. The model is initially validated for two-phase flow. Results are in good agreement with analytically obtained solutions and experimental results. The potential of this method is demonstrated by simulating flow in a realistic geometry composed of highly permeable meandering channels.

https://www.onlinelibrary.wiley.com/doi/pdf/10.1002/fld.4275

A force-balanced control volume finite element method for multi-phase porous media flow modelling

Control volume finite element methods (CVFEM) have been proposed to simulate flow in heterogeneous porous media because they are better able to capture complex geometries using unstructured meshes. However, producing good quality meshes in such models is non-trivial and may sometimes be impossible, especially when all or parts of the domains have very large aspect ratio. A novel CVFEM is proposed here that uses a control volume representation for pressure and yields significant improvements in the quality of the pressure matrix. The method is initially evaluated and then applied to a series of test cases using unstructured (triangular/tetrahedral) meshes, and numerical results are in good agreement with semi-analytically obtained solutions. The convergence of the pressure matrix is then studied using complex, heterogeneous example problems. The results demonstrate that the new formulation yields a pressure matrix than can be solved efficiently even on highly distorted, tetrahedral meshes in models of heterogeneous porous media with large permeability contrasts. The new approach allows effective application of CVFEM in such models. This article is protected by copyright. All rights reserved.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/fld.4381

Improving the robustness of the control volume finite element method with application to multiphase porous media flow

Accurate simulation of multiphase flow in fractured porous media remains a challenge. An important problem is the representation of the discontinuous or near discontinuous behaviour of saturation in real geological formations. In the classical continuum approach, a refined mesh is required at the interface between fracture and porous media to capture the steep gradients in saturation and saturation-dependent transport properties. This dramatically increases the computational load when large numbers of fractures are present in the numerical model. A discontinuous finite element method is reported here to model flow in fractured porous media. The governing multiphase porous media flow equations are solved in the adaptive mesh computational fluid dynamics code IC-FERST on unstructured meshes. The method is based on a mixed control volume – discontinuous finite element formulation. This is combined with the PN+1DG-PNDG element pair, which has discontinuous (order N+1) representation for velocity and discontinuous (order N) representation for pressure. A number of test cases are used to evaluate the method's ability to model fracture flow. The first is used to verify the performance of the element pair on structured and unstructured meshes of different resolution. Multiphase flow is then modelled in a range of idealised and simple fracture patterns. Solutions with sharp saturation fronts and computational economy in terms of mesh size are illustrated.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/gfl.12129

Multiphase flow simulation through porous media with explicitly resolved fractures

Constructing or refining complex reservoir models at the appraisal, development, or production stage is a challenging and time-consuming task that entails a high degree of uncertainty. The challenge is significantly increased by the lack of modeling, simulation and visualization tools that allow prototyping of reservoir models and development concepts, and which are simple and intuitive to use. Conventional modeling workflows, facilitated by commercially available software packages, have remained essentially unchanged for the past decade. However, these are slow, often requiring many months from initial model concepts to flow simulation or other outputs; moreover, many model concepts, such as large scale reservoir architecture, become fixed early in the process and are difficult to retrospectively change. Such workflows are poorly suited to rapid prototyping of a range of reservoir model concepts, well trajectories and development options, and testing of how these might impact on reservoir behavior. We present a new reservoir modeling and simulation approach termed Rapid Reservoir Modeling (RRM) that allows such prototyping and complements existing workflows. In RRM, reservoir geometries that describe geologic heterogeneities (e.g. faults, stratigraphic, sedimentologic and/or diagenetic features) are modelled as discrete volumes bounded by surfaces, without reference to a predefined grid. These surfaces, and also well trajectories, are created and modified using intuitive, interactive techniques from computer visualization, such as Sketch Based Interfaces and Modeling (SBIM). Input data can be sourced from seismic, geocellular or flow simulation models, outcrop analogues, conceptual model libraries or blank screen. RRM outputs can be exported to conventional workflows at any stage. Gridding or meshing of the models within the RRM framework allows rapid calculation of key reservoir properties and dynamic behaviors linked with well trajectories and development plans. We demonstrate here a prototype of the RRM workflow using a number of examples. The work is significant because it allows, for the first time, application of rapid prototyping methods in reservoir modeling and simulation. Such methods are widely used in other fields of engineering design and allow improved scoping of concepts and options prior, or in addition, to detailed modeling. Moreover, SBIM can be used on a range of hardware architectures, including table tops and surface PCs, fostering collaboration within integrated asset teams. Introduction Hydrocarbon reservoirs typically contain an array of complex geologic heterogeneities that are at, or below, the resolution of seismic data, so their geometry and spatial distribution is uncertain. These heterogeneities may be structural, stratigraphic, sedimentologic and/or diagenetic in origin, and often impact on flow behavior and hydrocarbon recovery; hence, they must be captured in reservoir models (e.g. Jones et al., 1994; 1995; Kjønsvik et al., 1994; White and Barton, 1999; Jackson et al., 2003; 2005; 2009; White et al., 2004; Matthäi et al., 2007a; Geiger et al., 2009; Sech et al., 2009; Choi et al., 2011; Deveugle et al., 2011). Reservoir modeling workflows have remained essentially unchanged for the past decade, facilitated by commercially available software packages such as Petrel and IRAP RMS (see Jackson et al., 2013 for an overview). These workflows begin with the construction of a geo-cellular reservoir model, in which a largely deterministic structural and stratigraphic framework is used to define the overall reservoir volume, and also compartments and zones within the reservoir. A grid is then constructed within each zone, typically using pillars that are continuous from the top to the base of the modelled volume, and

Rapid Reservoir Modeling: Prototyping of Reservoir Models, Well Trajectories and Development Options using an Intuitive, Sketch-Based Interface

A Discontinuous Overlapping Control Volume Finite Element Method for Multi-Phase Porous Media Flow Using Dynamic Unstructured Mesh Optimization

Surface-based modelling provides a computationally efficient approach for generating geometrically realistic representations of heterogeneity in reservoir models. However, conditioning Surface-Based Geological Models (SBGMs) to well data can be challenging because it is an ill-posed inverse problem with spatially distributed parameters. To aid fast and efficient conditioning, we use here SBGMs that model geometries using parametric, grid-free surfaces that require few parameters to represent even realistic geological architectures. A neural network is trained to learn the underlying process of generating SBGMs by learning the relationship between the parametrized SBGM inputs and the resulting facies identified at well locations. To condition the SBGM to these observed data, inverse modelling of the SBGM inputs is achieved by replacing the forward model with the pre-trained neural network and optimizing the network inputs using the back-propagation technique applied in training the neural network. An analysis of the uncertainties associated with the conditioned realisations demonstrates the applicability of the approach for evaluating spatial variations in geological heterogeneity away from control data in reservoir modelling. This approach for generating geologically plausible models that are calibrated with observed well data could also be extended to other geological modelling techniques such as object- and process-based modelling.

/pdf/conditioning-surface-based-geological-models-to-well-data-3nejp1ux96.pdf

Conditioning surface-based geological models to well data using artificial neural networks

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Papers

Rapid Reservoir Modeling: Prototyping of Reservoir Models, Well Trajectories and Development Options using an Intuitive, Sketch-Based Interface

A Discontinuous Overlapping Control Volume Finite Element Method for Multi-Phase Porous Media Flow Using Dynamic Unstructured Mesh Optimization

Conditioning surface-based geological models to well data using artificial neural networks