Name
Title | ||
|---|---|---|
Visualizing 3D Flow of Black-Oil Reservoir Models on Arbitrary Surfaces Using Projected 2D Line Integral Convolution |
Abstract | ||
|---|---|---|
In the oil industry, clear and unambiguous 3D flow visualization techniques are very important to inspect the results of numerical simulation of black-oil reservoir models. In this paper, we revisit the use of line integral convolution (LIC) for imaging 3D vector fields on arbitrary surfaces and apply it to reservoir visualization. We use a GPU-based method to image the tangential component using the conventional 2D LIC in projected screen space and propose the use of color to encode the normal component. To attach the flow imaging to the 3D surfaces, avoiding image flickering while manipulating the model, we propose a simple scheme based on randomly generated texture coordinate, avoiding the use of a solid 3D texture noise. For animation, we adjust the use of filters to ensure that the animation speed varies in accordance to the field magnitude. We also explore the visualization of multiphase (oil, gas, and water) flow. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/SIBGRAPI.2011.45 | SIBGRAPI |
Keywords | Field | DocType |
black-oil reservoir models,gpu-based method,hydrocarbon reservoirs,multiphase flow visualization,image flickering,projected screen space,black-oil reservoir visualization,graphics processing units,flow imaging,numerical analysis,convolution,oil industry,black-oil reservoir model,texture noise,petroleum industry,tangential component,line integral convolution,flow visualization technique,reservoir visualization,projected 2d line integral convolution,flow visualisation,normal component,solid modelling,animation speed,image texture,3d flow visualization,3d vector field imaging,solid 3d texture noise,numerical simulation,flow visualization,vector field | Computer vision,Euclidean vector,Computer graphics (images),Computer simulation,Image texture,Computer science,Convolution,Visualization,Tangential and normal components,Artificial intelligence,Flow visualization,Line integral convolution | Conference |
ISBN | Citations | PageRank |
978-1-4577-1674-4 | 1 | 0.35 |
References | Authors | |
13 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thiago Toledo | 1 | 1 | 0.35 |
| Waldemar Celes | 2 | 141 | 15.93 |