Details zur Publikation

Referenztyp Tagungsbeiträge
DOI / URL Link
Titel (primär) 2D probabilistic prediction of sparsely measured geotechnical parameters constrained by tomographic ambiguity and measurements errors
Titel (sekundär) 78th EAGE Conference and Exhibition, Vienna, Austria, 30 May - 2 June 2016
Autor Asadi, A.; Dietrich, P.; Paasche, H.;
Erscheinungsjahr 2016
Department MET;
Sprache englisch;
POF III (gesamt) T53;
Abstract We present a new approach for 2 D probabilistic prediction of sparsely measured target parameters, e.g.,
measured by direct push technology or borehole logging. Geophysical tomography is used to constrain the
prediction. The presented approach fully accounts for tomographic ambiguity and transduces it into
prediction uncertainty. Furthermore, errors of the logging data can be considered to avoid overfitting when
learning the optimal link between tomograms and logging data by means of Artificial Neural Networks.
Consideration of errors results in improved predictions, which we exemplary illustrate here by 2D sleeve
friction prediction.
ID 18165
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=18165
Asadi, A., Dietrich, P., Paasche, H. (2016):
2D probabilistic prediction of sparsely measured geotechnical parameters constrained by tomographic ambiguity and measurements errors
78th EAGE Conference and Exhibition, Vienna, Austria, 30 May - 2 June 2016
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