CALL FOR PROPOSALS:

ORGANIZERS

  • Harvey Thorleifson, Chair
    Minnesota Geological Survey
  • Carrie Jennings, Vice Chair
    Minnesota Geological Survey
  • David Bush, Technical Program Chair
    University of West Georgia
  • Jim Miller, Field Trip Chair
    University of Minnesota Duluth
  • Curtis M. Hudak, Sponsorship Chair
    Foth Infrastructure & Environment, LLC

 

Paper No. 2
Presentation Time: 9:15 AM

AN IMPROVED NUMERICAL MODEL OF CONGLOMERATE PROVENANCE


HEYDWEILLER, Erich C., Department of Geology and Geological Engineering, Colorado School of Mines, 1516 Illinois Street, Golden, CO 80401 and ASCHOFF, Jennifer, Dept. Geology and Geological Engineering, Colorado School of Mines, 1516 Illinois St, Colorado School of Mines, Golden, CO 80401, eheydwei@mines.edu

We present a new numerical model (coined CP1D) that improves existing conglomerate provenance models. Conglomerate provenance modeling is a powerful and inexpensive technique that yields valuable information about the uplift and unroofing history of structures. The underlying concept in numerical provenance models is that each clast potentially reveals two related, but distinct, pieces of information: (1) the lithology of the source unit, and (2) the stratigraphic interval that produced the clast. Existing conglomerate provenance models focus either on general clast lithology because it is easily and reliably determined, or on specific source formations when they are unambiguous. Although previous modelers intuitively evaluated model results using both pieces of information, there was no systematic way to integrate lithology and known source formations in numerical models. Our new model, implemented in Octave (an open-source MatlabTM clone), bridges this gap and uses both lithology and stratigraphic source unit data for model calibration. The modeling process consists of three steps: (1) user input of clast count data and a stratigraphic source section, (2) simulation of hundreds of possible unroofing scenarios that yield a range of possible conglomerate compositions, and (3) determination of the best-fit scenario by comparison of simulated compositions to actual compositions. The best-fit scenario minimizes the sum of squared errors (SSE) between actual and predicted compositions. CP1D was initially developed using a dataset from the Cretaceous Baseline Formation in the Valley of Fire, Nevada. For this dataset, stratigraphic source interval can be confidently assigned for most clasts; CP1D reproduced the known data more accurately (lower SSE in all trials) than existing provenance models. Further testing at two well known localities (Sphinx Mtn., Montana, and the Beartooth Uplift, Wyoming) confirmed the advantage of the new approach. Given the insight that conglomerate provenance can provide into the uplift and unroofing histories of basin-bounding structures, this new model is potentially quite useful for interpreting the tectonic significance of synorogenic conglomerates.

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