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Statistical Analysis of Igneous Complexes and Kimberlites

Explore spatial distribution and structural control of magmatic activity using Monte Carlo simulations and point feature analysis. Investigate magma transport mechanisms, stress fields, and anisotropies in lithosphere. Compare filtering methods for identifying spatial trends. Applications in tectonics, mineral resources, and hazards prediction. Conclusions on trends correlation with known geologic structures.

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Statistical Analysis of Igneous Complexes and Kimberlites

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  1. Structural control of igneous complexes and kimberlites: a new statistical method Dazheng Zhang and Lutz, T., 1989.

  2. Spatial distribution of magmatic activity • transport through the lithosphere • mechanical properties of the lithosphere • zones of weakness • associated with deep crustal fractures • linear outcrop patterns

  3. Monte Carlo simulations • null model • anisotropies • evaluated on a statistical basis

  4. Geologic point features • earthquake epicenters • kimberlites • igneous complexes • distribution random • controlled by geologic structures

  5. Magma transport control • pre-existing zones of weakness • stress fields during ascent • epeirogenic faults • transform fault extensions

  6. Anisotropic point feature distribution • Chapman (1968) alkaline igneous complexes • lattice nodal points • intersecting sets of crustal fractures • grid lines could be constructed • complexes located at nodal positions • Thompson and Hager (1979) • intuitive perceptions

  7. Lutz (1986) Monte Carlo simulations • line azimuth method • spatial anisotropy • shape of the region • azimuths of lines

  8. Filtering method (Strip method) • convex bounding polygon • parallel strips • equal number of strips • width of the strips • areal point density • vary the orientation

  9. Filtering method continued • limiting value arbitrary • false positive • false negative • signal to noise ratio

  10. Comparison of methods • should yield same anisotropies • different measures of spatial organization • line azimuth distribution (smaller scale) • point density (regional scale)

  11. Applications • theoretical tectonics • mineral resources location • geologic hazards

  12. Studies • Ring complexes • Kimberlite pipes

  13. Conclusions • In neither case can a convincing connection be shown between the directions of the trends indicated by the analysis and the trends of known geologic structures • located at depth and have no known surface expression • basis for predicting the locations of undiscovered or future events

  14. Thank You

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