Title :
SEISIS: a rule-based system for segmentation of a seismic section based on texture
Author :
Simaan, Marwan A. ; Zhang, Zhen
Author_Institution :
Dept. of Electr. Eng., Pittsburgh Univ., PA, USA
Abstract :
SEISIS is a knowledge-based system for the automatic segmentation of seismic sections into large regions of common textural properties. Such regions are believed to contain geologic information which can be related to large scale tectonic events, such as salt diapirs and shale ridges, or to different depositional environments of the constituent sediments. Human expert knowledge is introduced in SEISIS in order to resolve uncertainties in the numerical data and to help in making segmentation decisions. This domain-dependent knowledge, however, maybe stated using terms having imprecise or fuzzy meanings, such as “unlikely”, “usually”, “seldom”, etc. Furthermore, the conditions in the IF part of expert rules normally refer to and should-be matched with the information/facts collected during the segmentation process. These facts generally are associated with certain types of “uncertainties” to reflect their relative truthfulness. How to integrate all this information and knowledge, which is typically of diverse sources and with different scales, to reach a final classification decision is a crucial problem in the development and actual implementation of SEISIS´s knowledge-based segmentation process
Keywords :
expert systems; fuzzy logic; geology; geophysical prospecting; geophysical signal processing; image classification; image segmentation; image texture; seismology; tectonics; IF part; SEISIS; classification decision; depositional environments; domain-dependent knowledge; expert rules; fuzzy meanings; geologic information; imprecise meanings; knowledge-based system; rule-based system; salt diapirs; segmentation; seismic section; shale ridges; tectonic events; texture; truthfulness; Earth; Geologic measurements; Geology; Humans; Image segmentation; Knowledge based systems; Large-scale systems; Seismic measurements; Sensor arrays; Signal processing;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International
Conference_Location :
Firenze
Print_ISBN :
0-7803-2567-2
DOI :
10.1109/IGARSS.1995.520309