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[FTB00] Use of neural networks in log's data processing: prediction and rebuilding of lithologic facies
Conférence Internationale avec comité de lecture : Petrophysics meets Geophysics, Paris, 2000., January 2000,
motcle:
Résumé:
When a log is missing in a drilling hole, geologists hope to deduce it
from others logs available in another part of the hole or in a
neighbouring hole, in order to define the lithologic facies of the hole.
This paper presents a neural network method to predict the missing log's
measure from the other available log's measures. This method, based on
Multi-Layer Perceptron (MLP) acts as a non linear regression method for
the prediction task and as a probability density distribution
approximation for the outlier rejection task. The result obtained when
applied to actual log's data for prediction and rejection are presented
in a separate section. The last section is dedicated to a non supervised
neural method in order to reconstruct the lithologic facies of the
concerned hole. This last experiment allows to validate and interpret
the different results of the proposed methods.
Collaboration:
UPMC
BibTeX
| @inproceedings { | |||
| FTB00, | |||
| title | = | "{Use of neural networks in log's data processing: prediction and rebuilding of lithologic facies }", | |
| author | = | " D. Frayssinet and S. Thiria and F. Badran and L. Briqueu ", | |
| booktitle | = | "{Petrophysics meets Geophysics, Paris, 2000.}", | |
| year | = | 2000, | |
| month | = | "January", | |
| } | |||
