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    ECloud – Magnetotelluric Webapp

    Access Status
    Fulltext not available
    Authors
    Pethick, A.
    Harris, Brett
    Lebedev, P.
    Date
    2018
    Type
    Conference Paper
    
    Metadata
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    Citation
    Pethick, A. and Harris, B. and Lebedev, P. 2018. ECloud – Magnetotelluric Webapp, Australasian Exploration Geoscience Conference.
    Source Conference
    Australasian Exploration Geoscience Conference
    DOI
    10.1071/ASEG2018abT7_2H
    Additional URLs
    https://doi.org/10.1071/ASEG2018abT7_2H
    School
    WASM: Minerals, Energy and Chemical Engineering (WASM-MECE)
    URI
    http://hdl.handle.net/20.500.11937/68817
    Collection
    • Curtin Research Publications
    Abstract

    Geophysical web applications are highly underrated. There are many potential benefits for transitioning to a cloud based web applications including compatibility improvement, low on-going operating costs and better access to existing third-party code and tools for facilitating rapid development. For users, time spent on installation, general IT maintenance such license management and upgrading is minimized. While web applications for business style applications are deeply established, scientific applications on the web are only just emerging. This research builds upon our previous feasibility study (Pethick and Harris 2015), which was the development of a 1D MT web application. This is to be redevelop into a commercial grade cloud hosted geophysical inversion web app that can cooperatively invert seismic and magnetotelluric (MT) data. Our software, ECloud, is designed to be user friendly where geoscientists and drillers can upload MT field data directly from their laptop, tablet or mobile to obtain subsurface geo-electrical distributions quickly with minimal input. This application is designed to be scalable, suiting cloud environments and is currently hosted on an Amazon EC2 instance. The preconceived notion that web applications are slow will be challenged. The purposefully designed MT algorithm and software structure will hopefully result in lower computation times while minimizing restrictions based on hardware requirements (i.e., primary memory).

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