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Use of Raster to Vector Image Analysis Technology to Rapidly and Accurately Digitize Historical Seismograms

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-FG02-09ER85419
Agency Tracking Number: 91557
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: 61 a
Solicitation Number: DE-PS02-08ER08-34
Timeline
Solicitation Year: 2008
Award Year: 2009
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
104 1/2 Calle La Pena, Santa Fe, NM, 87505
DUNS: 166694484
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Andrew Bartlett
 Dr.
 () -
 andy@retrievertech.com
Business Contact
 Andrew Bartlett
Title: Dr.
Phone: () -
Email: andy@retrievertech.com
Research Institution
N/A
Abstract
Large stores of unique seismic information ¿ generated from earthquakes, nuclear tests, and oil and gas exploration ¿ exist in both public and private repositories. However, much of this data exists as optically scanned images that are not useful for further analysis. In order to access and analyze these records, it is critically important to develop automated and accurate image analysis techniques to extract useful data. This project will apply a unique method whereby rasterized images will be intelligently converted to vectorized images. The underlying properties of the vectorized images will be utilized to create accurate traces and digital outputs in formats that can subsequently be analyzed with modern tools. Commercial Applications and other Benefits as described by the awardee Beyond the application to DOE¿s nonproliferation responsibilities, the technology could be customized for commercialization for the oil exploration industry as a tool for analyzing seismographs and geological data, with the goal of pinpointing mineral deposits. In addition, this product could aid earthquake researchers in analyzing past seismic events, with the goal of better understanding geophysics and hazard prediction

* Information listed above is at the time of submission. *

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