Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1190/1.3374411
Titel (primär) Automated integration of partially colocated models: subsurface zonation using a modified fuzzy c-means cluster analysis algorithm
Autor Paasche, H.; Tronicke, J.; Dietrich, P. ORCID logo
Quelle Geophysics
Erscheinungsjahr 2010
Department MET
Band/Volume 75
Heft 3
Seite von P11
Seite bis P22
Sprache englisch
Keywords geophysical techniques; geophysics computing; pattern clustering; seismic waves; seismology
Abstract Partitioning cluster analyses are powerful tools for rapidly and objectively exploring and characterizing disparate geophysical databases with unknown interrelations between individual data sets or models. Despite its high potential to objectively extract the dominant structural information from suites of disparate geophysical data sets or models, cluster-analysis techniques are underused when analyzing geophysical data or models. This is due to the following limitations regarding the applicability of standard partitioning cluster algorithms to geophysical databases: The considered survey or model area must be fully covered by all data sets; cluster algorithms classify data in a multidimensional parameter space while ignoring spatial information present in the databases and are therefore sensitive to high-frequency spatial noise (outliers); and standard cluster algorithms such asfuzzy c-means (FCM) or crisp k-means classify data in an unsupervised manner, potentially ignoring expert knowledge additionally available to the experienced human interpreter. We address all of these issues by considering recent modifications to the standard FCM cluster algorithm to tolerate incomplete databases, i.e., survey or model areas not covered by all available data sets, and to consider spatial information present in the database. We have evaluated the regularized missing-value FCM cluster algorithm in a synthetic study and applied it to a database comprising partially colocated crosshole tomographic P- and S-wave-velocity models. Additionally, we were able to demonstrate how further expert knowledge can be incorporated in the cluster analysis to obtain a multiparameter geophysical model to objectively outline the dominant subsurface units, explaining all available geoscientific information.
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=10380
Paasche, H., Tronicke, J., Dietrich, P. (2010):
Automated integration of partially colocated models: subsurface zonation using a modified fuzzy c-means cluster analysis algorithm
Geophysics 75 (3), P11 - P22 10.1190/1.3374411