Name
Abstract | ||
|---|---|---|
Seismic interpretation is a vital step in oil and gas industry. Choosing proper drilling locations is a major challenge to the interpreters, since an ultra-deep water oil well located below 2500 meters of water can cost dozens of millions of dollars. Volumetric curvature attributes are widely used to visualize folds, faults, among other key structures that define a possible reservoir. However, volumetric curvature estimate is very compute-intensive and can take several hours. The main goal of this paper is to present a GPGPU implementation that perform volumetric curvature estimate at interactive real-time, for a single volume slice. We show an implementation that maximizes memory access, loading necessary data to GPU shared memory using a circular buffer. The most compute demanding kernel achieved 56% of GPU peak performance and 1.676 instructions per clock out of theoretical maximum 2. Our results show an average speed-up of 12 times compared to CPU with OpenMP. In addition, the application fits really well on GPUs, due to the high number of registers available plus programmable cache (CUDA shared memory). The GPU performance gains enabled on-the-fly calculations during visualization at interactive real-time, instead of waiting time of hours for the whole volume. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/SBAC-PAD.2014.11 | SBAC-PAD |
Keywords | DocType | ISSN |
cache storage,curve fitting,data visualisation,drilling (geotechnical),graphics processing units,mechanical engineering computing,parallel architectures,petroleum industry,real-time systems,seismology,shared memory systems,vibrations,3D seismic data,CPU,CUDA shared memory,GPGPU,GPU performance,GPU shared memory,OpenMP,circular buffer,data loading,drilling locations,gas industry,general purpose computing on graphics processing unit,interactive real-time,interpreters,memory access,oil industry,programmable cache,seismic interpretation,single volume slice,ultra-deep water oil well,visualization,volumetric curvature attributes,volumetric curvature estimate | Conference | 1550-6533 |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leonardo de Oliveira Martins | 1 | 27 | 2.54 |
| Silva Marco A | 2 | 3 | 1.16 |
| Marcelo Arruda | 3 | 1 | 0.36 |
| Joner Duarte | 4 | 1 | 0.36 |
| Pedro Mario Silva | 5 | 2 | 1.39 |
| Roberto Beauclair Seixas | 6 | 1 | 0.36 |
| Marcelo Gattass | 7 | 382 | 48.43 |
| Goncalves da Silva, M.A. | 8 | 1 | 0.36 |