DocumentCode :
2684937
Title :
Wavelets and neural nets for stratigraphic analysis
Author :
Rehmeyer, Daran L. ; Aravena, Jorge L.
Author_Institution :
Quaternary Resource Investigations Inc., Baton Rouge, LA, USA
Volume :
4
fYear :
1994
fDate :
8-12 Aug 1994
Firstpage :
2117
Abstract :
The paper describes a hybrid ground penetrating radar (GPR) system developed by Quaternary Resource Investigations, Inc., of Baton Rouge, La. The system is designed to tradeoff on the vertical resolution of standard GPR while improving the depth of penetration. It is designed primarily for stratigraphical analysis which does not, typically, require the finer vertical resolution that standard GPR provides. The problem motivating the design of this equipment is the non-invasive identification of geologic contaminant traps and migration paths
Keywords :
feedforward neural nets; geophysical signal processing; geophysical techniques; pollution measurement; radar applications; radar detection; radar imaging; remote sensing; soil; terrestrial electricity; wavelet transforms; GPR; Quaternary Resource Investigations; geoelectric terrestrial electricity; geologic contaminant trap; geology; geophysical measurement technique; ground penetrating radar; migration path; neural net; penetration depth; sedimentary rock; soil pollution; stratigraphic analysis; stratigraphy; vertical resolution; Conductivity; Data acquisition; Geology; Ground penetrating radar; Neural networks; Signal processing; Signal resolution; Soil; Standards development; Wavelet analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1994. IGARSS '94. Surface and Atmospheric Remote Sensing: Technologies, Data Analysis and Interpretation., International
Conference_Location :
Pasadena, CA
Print_ISBN :
0-7803-1497-2
Type :
conf
DOI :
10.1109/IGARSS.1994.399668
Filename :
399668
Link To Document :
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