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P.M. Granitto, P.F. Verdes, H.D. Navone, H.A. Ceccatto D. Curia and C....  Home/Search
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Abstract: We present an exploratory use of neural network ensembles in the modeling of oil well logs. These records are frequently used to determine the mineralogy and physical properties of potential reservoir rocks, and the nature of the fluids they contain. In particular, we consider the possibility of developing nonlinear local models relating Sonic logs (transit time of compressional waves) with other commonly measured properties such as Resistivity and Natural Formation Radioactivity Level... (Update)
Context of citations to this paper: More
...involved usually lead to linear correlation coefficients between measured and predicted Sonic values as low as 0.2. Recently[17] we explored the possibility of developing nonlinear local models relating Sonic logs with other commonly measured quantities, such as...
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BibTeX entry: (Update)
P.M. Granitto, P.F. Verdes, H.D. Navone, H.A. Ceccatto, D. Curia and C. Larriestra, "Modeling of Sonic Logs in Oil Wells with Neural Network Ensembles", Argentine Symposium on Artificial Intelligence (ASAI'01) (Bs. As., September 12-13, 2001). http://citeseer.ist.psu.edu/granitto01modeling.html More
@misc{ granitto01modeling,
author = "P. Granitto and P. Verdes and H. Navone and H. Ceccatto and D. Curia and
C. Larriestra",
title = "Modeling of Sonic Logs in Oil Wells with Neural Network Ensembles",
text = "P.M. Granitto, P.F. Verdes, H.D. Navone, H.A. Ceccatto, D. Curia and C.
Larriestra, Modeling of Sonic Logs in Oil Wells with Neural Network Ensembles,
Argentine Symposium on Artificial Intelligence (ASAI'01) (Bs. As., September
12-13, 2001).",
year = "2001",
url = "citeseer.ist.psu.edu/granitto01modeling.html" }
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