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The Visual Computer

, Volume 35, Issue 6–8, pp 837–848 | Cite as

Multiresolution visualization of massive black oil reservoir models

  • Frederico AbrahamEmail author
  • Waldemar Celes
Original Article
  • 119 Downloads

Abstract

Recent advances in parallel architectures for numerical simulation of natural black oil reservoirs have allowed the use of very discretized domains. As a consequence, these simulations produce an unprecedented volume of data, which must be visualized in 3D environments for careful analysis and inspection. Conventional scientific visualization techniques are not viable on such large models, creating a demand for the development of scalable visualization solutions. In this paper, we propose a hierarchical multiresolution technique to render massively large black oil reservoir meshes. A new simplification algorithm specialized for such models is presented, which accurately represents boundary surfaces, while keeping the hexahedral mesh with good quality. Original model properties, wireframe and surface normals are mapped onto the simplified meshes through texture mapping. This allows the system to reuse the structure for different simulations that use the same geometry model. The viewer application is designed to guarantee a minimum refresh rate, allocating geometric detail where it is most needed, given the available hardware. Experimental results, considering up to 1.2 billion cell models, demonstrate the effectiveness of the proposed solution.

Keywords

Real-time rendering Reservoir model rendering Mesh simplification algorithm Multiresolution rendering Massive model visualization 

Notes

Acknowledgements

Tecgraf/PUC-Rio is a research institute mainly funded by Petrobras. This research was initiated during the Doctoral Program of the first author, financially supported by CNPq (Brazilian National Research and Development council).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

Supplementary material 1 (avi 47813 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Computer Science Department, Tecgraf/PUC-Rio InstitutePontifical Catholic University of Rio de JaneiroRio de JaneiroBrazil

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