T108 Geologic Maps, Digital Geologic Maps, and Derivatives from Geologic and Geophysical Maps (Posters)

Monday, 1 November 2010
8:00 AM - 6:00 PM
Hall D

IMPROVING ROCK COMPOSITION QUERIES OF GEOSPATIAL GEOLOGIC MAPS IN ARCGIS BY USING CHEMICALLY-DEFINED ROCK NAMES

Paper number: T108-4
Program: Technical Sessions
Time: 8:00 AM – 6:00 PM

Authors

Abstract

A geospatial geologic map database for the Central Colorado Project (CCAP) has been compiled at a nominal 1:100,000 scale and is linked to an extensive database of more than 10,000 geochemical samples from all available sources. To optimize use of these data, GIS techniques commonly employed in geospatial problems are applied to literally “map” the analytical data onto rock classification diagrams. Geologic information on the diagrams, such as rock name, descriptive terms, and tectonic settings of rock units, is determined for each sample, returned to the chemical database, and then linked to the geologic map. For instance, major-element analysis data for a sample can define the R1-R2 rock name (diorite, granite, etc), whether the rock is calc-alkalic or alkalic, peraluminous or metaluminous, Fe- or Mg-rich, and potassic or sodic. Minor-element data can suggest tectonic settings of mafic volcanic rocks (arc, plume, etc.) and felsic plutonic rocks (within-plate, convergent margin) from published binary or ternary diagrams. Incorporation of searchable terms allows the user to make complex queries, such as the location of all samples of metaluminous dioritic rocks that are strongly potassic, from the database and to view the spatial distribution of the queried samples as points.

The utility of this geospatial database is significantly improved by providing similar searchable terms for polygons of rocks instead of individual samples. As an example, a Tertiary pluton, such as the Montezuma stock, is represented on the map by six similarly coded polygons (Timz). There are as many as thirty geochemical samples among those six polygons. The sample information is spatially joined to the geologic map so that samples in the targeted polygons or within 300 m can be used to calculate the most common rock composition (granodiorite) and the range of compositions (diorite to granite). Information also is summarized for the A/CNK ratio, alkalinity, Fe-enrichment, and K-enrichment of each rock unit (polygon). Linking the CCAP database with the geologic map allows the user to consider detailed geochemical information spatially, and to query the map using geologic terms typically reserved for rock classification diagrams.