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Integrated seismic texture segmentation and clustering analysis to improved delineation of reservoir geometry |
| ID |
44 |
| Title |
Integrated seismic texture segmentation and clustering analysis to improved delineation of reservoir geometry |
| Authors |
Sipuikinene Miguel Angelo*, Marcilio Matos, Kurt J. Marfurt |
| Authors detail |
ConocoPhillips School of Geology & Geophysics, The University of Oklahoma, Norman, Oklahoma |
| Publication |
SEG Expanded Abstract |
| Publication Detail |
|
| Volume |
Nov-09 |
| Year |
2009 |
| Abstract |
In recent years, 3D volumetric attributes have gained wide acceptance by geosciences interpreters. The early introduction of single-trace complex trace attributes was quickly followed by seismic sequence attribute mapping workflows. 3D geometric attributes such as coherence and curvature are also widely used. Most of these attributes correspond to a very simple easy-to-understand measures of a waveform or surface morphology. However, not all geologic features can be so easily quantified. For this reason, simple statistical measures of the seismic waveform such as RMS amplitude prove to be quite valuable in delineating more chaotic stratigraphy. In this paper, we show how modern texture analysis based on the gray-level co-occurrence matrix, when coupled with recent developments in self-organizing maps clustering technology, extends such statistical measures to delineate features that geoscientists can see, but not easily describe. |
| Keywords |
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| Status |
Accepted |
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