Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
ASEG Extended Abstracts ASEG Extended Abstracts Society
ASEG Extended Abstracts
RESEARCH ARTICLE

Bigger, better, smarter; high performance computers applied to Government geophysics

Ned Stolz

ASEG Extended Abstracts 2013(1) 1 - 4
Published: 12 August 2013

Abstract

Government Geological Surveys study the Earth at the regional, province or national scale, and acquire vast volumes of technically complex data. These data must be high quality, fit for purpose, durable, and readily accessible and usable by industry. Increasingly, users require the geological information contained within the data as well as the data itself. High performance computers facilitate a step-change in advanced processing and modelling of large, complex data, and will help Government deliver more sophisticated products to industry. Data enhancement and manipulation are no-longer limited by the computational effort required, and there are no artificial limits to the size of the data or model, or the data resolution that can be processed. Geoscience Australia is collaborating with the National Computational Infrastructure facility (NCI) at the Australian National University to develop advanced methods for extracting the maximum geological information from large data volumes. The new methods include: Modelling of potential-field data in spherical coordinates to create continental-scale reference models of density and magnetic susceptibility; Inversion of magnetotelluric tensor data to a full 3D mesh of resistivities, and; Monte Carlo inversions of AEM responses to assess the reliability and sensitivity of conductivity-depth images. These algorithms are being implemented in a new Virtual Geophysical Laboratory where Government data and advanced processing methods are brought together in a single high performance computer environment.

https://doi.org/10.1071/ASEG2013ab197

© ASEG 2013

PDF (592 KB) Export Citation

Share

Share on Facebook Share on Twitter Share on LinkedIn Share via Email

View Dimensions