Domaining by clustering multivariate geostatistical data - Mines Paris Accéder directement au contenu
Communication Dans Un Congrès Année : 2012

Domaining by clustering multivariate geostatistical data

Thomas Romary
Jacques Rivoirard
Jacques Deraisme
  • Fonction : Auteur
Cristian Quinones
  • Fonction : Auteur
Xavier Freulon


Domaining is very often a complex and time-consuming process in mining assessment. Apart from the further delineation of envelopes, a significant number of parameters (lithology, alteration, grades?) are to be combined in order to characterize domains or sub domains. This rapidly leads to a huge combinatory. Hopefully the number of domains should be limited, while ensuring their connectivity as well as the stationarity of the variables within each domain. In order to achieve this goal, different methods for the spatial clustering of multivariate data are explored and compared. A particular emphasis is placed on the ways to modify existing procedures of clustering in non spatial settings to enforce the spatial connectivity of the resulting clusters. K-means, spectral methods and EM-based algorithms are reviewed. The methods are illustrated on mining data.
Fichier principal
Vignette du fichier
paper_oslo.pdf (2.19 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-00776725 , version 1 (16-01-2013)


  • HAL Id : hal-00776725 , version 1


Thomas Romary, Jacques Rivoirard, Jacques Deraisme, Cristian Quinones, Xavier Freulon. Domaining by clustering multivariate geostatistical data. Ninth International Geostatistics Congress,, 2012, Norway, France. pp.455-466. ⟨hal-00776725⟩
213 Consultations
1306 Téléchargements


Gmail Facebook Twitter LinkedIn More