T111 From Outcrops to the Base of the Crust: Integrated Geophysical and Geological Illumination of Earth’s Tectonic Fabrics to Refine Understanding of Crustal Evolution and Natural Resources
Monday, 10 October 2022
1:30 PM - 5:30 PM
504
AN EIGENVALUE BASED K-MEANS APPROACH TO GEOLOGIC CLUSTER ANALYSIS
Paper number: T111-15
Program: Technical Sessions
Time: 4:45 PM – 5:00 PM
Authors
Abstract
The present approach maximizes the sum of an eigenvalue, or resultant vector, index over the clusters. This allows weighting, and is implemented for axis, vector, and girdle distributions. Cluster centers are seeded using random rotation matrices, from which iterative solutions converge by minimizing a cost function. This requires selection of the number of clusters, k, which can be subjective, so methods are given for the evaluation of k. A scalar distance-based minimization is also implemented, where cluster centers are found by minimizing the sum of spherical distances from the data. This is less flexible, but is more stable for large k and small n. Finally, a density-based cluster analysis is implemented.
Three data sets illustrate these methods. The first is fracture data from the San Manual copper mine, Arizona. Contouring the data on a Schmidt plot suggests k=3 clusters. The second are magnetic remanence vectors, which on theoretical grounds should have k=4 clusters. A third example is fault slip partitioning. Slip partitioning has been suggested to occur on transpressional fault systems, such as the Denali fault, and is a well established tenet of plate tectonic theory along extensional plate boundaries, such as the Mid-Atlantic Ridge (MAR). This example uses k=3 to distinguish three fault slip modes along the southern MAR using cluster analysis.
These implementations are available in the free Orient software.
Geological Society of America Abstracts with Programs. Vol. 54, No. 6
doi: 10.1130/abs/2022AM-383667
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