On the impact of heterogeneity-aware mesh partitioning and non-contributing computation removal on parallel reservoir simulations

Parallel computations have become standard practice for simulating the complicated multi-phase flow in a petroleum reservoir. Increasingly sophisticated numerical techniques have been developed in this context. During the chase of algorithmic superiority, however, there is a risk of forgetting the ultimate goal, namely, to efficiently simulate real-world reservoirs on realistic parallel hardware platforms. In this paper, we quantitatively analyse the negative performance impact caused by non-contributing computations that are associated with the “ghost computational cells” per subdomain, which is an insufficiently studied subject in parallel reservoir simulation. We also show how these non-contributing computations can be avoided by reordering the computational cells of each subdomain, such that the ghost cells are grouped together. Moreover, we propose a new graph-edge weighting scheme that can improve the mesh partitioning quality, aiming at a balance between handling the heterogeneity of geological properties and restricting the communication overhead. To put the study in a realistic setting, we enhance the open-source Flow simulator from the OPM framework, and provide comparisons with industrial-standard simulators for real-world reservoir models.

OPTIMIZATION OF MESH PARTITIONING FOR PARALLEL COMPUTATIONS IN THE SIBCIOM MODEL

Numerical models develop with development of computational technique, and this development can include either creation of new models, or modification, improvement of existing ones. Modifications can concern both mathematical part, for example, change of numerical schemes, parameterization of various physical processes, and technical part, for example, adaptation of algorithms for use on other computer systems or parallelization of algorithms. The paper considers the issue of optimization of parallel computations for the ice and ocean model SibCIOM. Optimization consists in constructing a mesh partitioning for which the nodes are evenly distributed across the computational cores and the time spent on exchanges is minimal. The METIS package is used to implement such a mesh partitioning. A conceptual description of the implementation of exchange processes for such partitioning is presented.

A Framework for Curvature-Based CAD Mesh Partitioning

In ISO Geometrical Product Specifications and Verification Standards (GPS) [1], partition is one of the fundamental operations used to obtain ideal or non-ideal features of a product. The operation of partition produces independent geometrical features by decomposing the object. A curvature-based CAD mesh partitioning framework is proposed in this paper. The framework combines several key steps including curvature-based attribute calculation, local shape type refinement, region growing, slippage analysis and statistical modeling. The partitioned features are classified into seven invariance classes of surface in the context of ISO GPS. A case study shows that not only appropriate partitioning but also accurate invariance class recognition for GPS are achieved by the proposed framework.

HIGH QUALITY TEXTURE MAPPING PROCESS AIMED AT THE OPTIMIZATION OF 3D STRUCTURED LIGHT MODELS

<p><strong>Abstract.</strong> This article presents the evaluation of a pipeline to develop a high-quality texture mapping implementation which makes it possible to carry out a semantic high-quality 3D textured model. Due to geometric errors such as camera parameters or limited image resolution or varying environmental parameters, the calculation of a surface texture from 2D images could present several color errors. And, sometimes, it needs adjustments to the RGB or lightness information on a defined part of the texture. The texture mapping procedure is composed of mesh parameterization, mesh partitioning, mesh segmentation unwraps, UV map and projection of island, UV layout optimization, mesh packing and mesh baking. The study focuses attention to the mesh partitioning that essentially assigns a weight to each mesh, which reveals a mesh’s weight calculated by considering the flatness and distance of the mesh with respect to a chart. The 3D texture mapping has been developed in <i>Blender</i> and implemented in <i>Python</i>. In this paper we present a flowchart that resumes the procedure which aims to achieve a high-quality mesh and texture 3D model starting from the 3D <i>Spider</i> acquire, integrated with the <i>SfM</i> texture and using the texture mapping to reduce the color errors according to a semantic interpretation.</p>