DocumentCode
3008777
Title
Pattern recognition in hydrocarbon exploration
Author
Sriram, K.P. ; Stoessel, E.T. ; Kowalski, B.R.
Author_Institution
Shell Development Company, Houston, Texas
fYear
1975
fDate
10-12 Dec. 1975
Firstpage
118
Lastpage
119
Abstract
The problem of pattern recognition is, simply stated, that of assigning a classification to members of a set of objects based on measurements made on the objects. In a typical application problem, the relationship between the various possible classifications of a given object and the measurements is unknown or is very complex. In such instances, we turn to machines to examine the measurements and assist us in making the classification or to help us unravel the complex relationships between the classifications and measurements on a set of objects whose classifications are known a priori. In the context of hydrocarbon exploration, we have tried to answer the question: Is a particular portion of the earth´s subsurface in a favorable situation for hydrocarbons to occur? The measurements to be used must be made on geophysical data observable at the surface of the earth. We have restricted the study to the use of only seismic reflection data for measurements.
Keywords
Area measurement; Chemistry; Earth; Geophysical measurements; Hydrocarbons; Pattern recognition; Seismic measurements; Supervised learning; Time measurement; Unsupervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control including the 14th Symposium on Adaptive Processes, 1975 IEEE Conference on
Conference_Location
Houston, TX, USA
Type
conf
DOI
10.1109/CDC.1975.270660
Filename
4045387
Link To Document