A new system was developed to extrapolate the maximum amount of information from the image logs by considering not only the surfaces that cut the borehole but also the textural features of the images. The main objective of developing this system was to reduce the subjectivity and the time of interpretation tasks by largely automating the log interpretation, although some level of human interaction and correction is still necessary. This approach exploits image processing algorithms to analyze borehole images and artificial intelligence techniques to classify them. The resulting implemented system produces a semi-automatic interpretation of the image logs. This software was used over the FMI logs of four wells from the north African region in order to test the validity of the results.

Validation of a Semi-automatic Interpretation of Image Logs Using Two Wells from a North Africa Sandstone Reservoir

FERRARETTI, Denis;GAMBERONI, Giacomo;
2009

Abstract

A new system was developed to extrapolate the maximum amount of information from the image logs by considering not only the surfaces that cut the borehole but also the textural features of the images. The main objective of developing this system was to reduce the subjectivity and the time of interpretation tasks by largely automating the log interpretation, although some level of human interaction and correction is still necessary. This approach exploits image processing algorithms to analyze borehole images and artificial intelligence techniques to classify them. The resulting implemented system produces a semi-automatic interpretation of the image logs. This software was used over the FMI logs of four wells from the north African region in order to test the validity of the results.
Intelligenza Artificiale; Immagini; Geologia; Idrocarburi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/534791
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