MULTI-RESOLUTION GRAPH-BASED CLUSTERING

摘要

Apparatus and method for obtaining fades of geological formations for identifying mineral deposits. Logging instruments (16) are moved in a borehole (10) to produce log measurements at successive levels of the borehole. The set of measurements at each such level of the borehole interval is associated with reference sample points within a multidimensional space. The multidimensional scatter of sample points is analyzed to determine a set of characteristic modes. The sample points associated with characteristic modes are grouped to identify clusters. A fades is designated for each of the clusters and a graphic representation of the succession of facies as a function of the depth is thus obtained. To identify the clusters, a "neighboring index" of each log measurement point in the data set is calculated (510). Next, small natural groups of points are formed (515) based on the use of the neighboring index to determine a K-Nearest-Neighbor (KNN) attraction for eac h point. Independently of the natural group formation, an optimal number of clusters is calculated (520) based on a Kernel Representative Index (KRI) and based on a user-specified resolution. Lastly, based on the data calculated from the prior steps, final clusters are formed (530) by merging the smaller clusters.