APPLICATION OF GRAY LEVEL CO-OCCURENCE MATRIX (GLCM) TO DELINIATE DISTRIBUTION OF SANDSTONE
Interpretation of seismic data for the ultimate objective of finding hydrocarbons has always been driven by pattern recognition, which yield information about subsurface geology. However, not all geologic features can be so easily interpreted directly from seismic amplitude information because it is...
Saved in:
| Main Author: | |
|---|---|
| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/23772 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Interpretation of seismic data for the ultimate objective of finding hydrocarbons has always been driven by pattern recognition, which yield information about subsurface geology. However, not all geologic features can be so easily interpreted directly from seismic amplitude information because it is very sensitive to local distortions. In this study, we try to use gray-level co-occurrence matrix (GLCM) method that routinely used in remote sensing applications to delineate distribution of sandstone. GLCM is a tabulation of how often different combinations of pixel brightness values (gray levels) occur in a sub-image window. We generate synthetic data to study the relationship between GLCM parameters and results from computation of GLCM. After that, we apply this method in seismic data to extract the information of sandstone distribution. The result of this study shows GLCM allows the recognition of patterns significantly more complex than simple edges and able to delineate distribution of sandstone in seismic data. |
|---|