Publication Details

Reference Category Conference contributions
DOI / URL link
Title (Primary) About data-driven integration of ill-posed geophysical tomography and geotechnical logging data
Title (Secondary) 78th EAGE Conference and Exhibition, Vienna, Austria, 30 May - 2 June 2016
Author Paasche, H.;
Year 2016
Department MET;
Language englisch;
POF III (all) T31;
UFZ wide themes RU5;
Abstract We employ a recently developed data-driven approach to exemplary infer a probabilistic 2D sleeve friction
model constrained by ill-posed geophysical tomographic imaging and laterally sparse cone penetration
logging data. The integration and inference approach is based on fuzzy concepts and can fully cope with
unknown and even non-unique inter-relations between geotechnical parameters, such as sleeve friction,
and multiple physical properties imaged by fully non-linear geophysical tomography, e.g. ensembles of
equivalent seismic or radar velocity models. Such data-driven integration and inference approaches can be
applied to complex databases and do not require the a priori selection of tomographic data sets believed to
be particularly closely linked to the target parameter, e.g., sleeve friction and seismic shear wave velocity
tomograms. However, in the sense of error propagation incorporation of all available tomographic data
sets may inflate the range of the final probabilistic prediction, which is not desirable. In turn, discarding
data sets not expected to be physically linked to the target parameter may hamper predictions and
potentially result in overseeing weak and yet unrecognized, but eventually existing, physical links, which
could have improved the inference of probabilistic geotechnical target parameter models.
ID 18164
Persistent UFZ Identifier http://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=18164
Paasche, H. (2016):
About data-driven integration of ill-posed geophysical tomography and geotechnical logging data
78th EAGE Conference and Exhibition, Vienna, Austria, 30 May - 2 June 2016
p. 1 - 5