Title :
New Method of Horizon Recognition in Seismic Data
Author :
Lili Li ; Guoqing Ma ; Xiaojuan Du
Author_Institution :
Coll. of Geo-Exploration Sci. & Technol., Jilin Univ., Changchun, China
Abstract :
Horizon recognition is a valuable tool in the interpretation of seismic data. In this letter, we present a new method which uses the combination of horizontal derivative and mathematical morphology to identify horizons. We first use a threshold value to filter the horizontal derivative of seismic data and then use the ratio of the erosion of the filtered derivative to the dilation of the filtered derivative to balance the amplitudes of strong and weak horizons. Finally, we move the strong amplitude to the position of the actual horizon. This method is demonstrated on both synthetic and real data. The resolving power of the new method is evaluated by comparing the results with those obtained by other similar methods. The new method can display the horizons more clearly.
Keywords :
geophysical techniques; seismology; erosion ratio; filtered derivative dilation; horizon recognition method; horizontal derivative morphology; mathematical morphology; seismic data; Cellular neural networks; Image edge detection; Morphology; Multiresolution analysis; Robustness; System-on-a-chip; Horizon recognition; horizontal derivatives; mathematical morphology; seismic data;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2012.2190039