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pyDFERM - Towards a Versatile and Efficient Environment for ERT Monitoring Data Management and ProcessingNormal access

Authors: O. Kaufmann and A. Watlet
Event name: Near Surface Geoscience 2016 - 22nd European Meeting of Environmental and Engineering Geophysics
Session: Monitoring and Characterization II
Publication date: 04 September 2016
DOI: 10.3997/2214-4609.201601945
Organisations: EAGE
Language: English
Info: Extended abstract, PDF ( 1.4Mb )
Price: € 20

We developed a Data Format for Electrical Resistivity Monitoring alongside a Python package (pyDFERM) as a novel approach for managing long-term ERT monitoring experiments. Large datasets produced in such experiments are indeed quickly difficult to handle with conventional data storing techniques. In parallel, long-term experiments are subject to changes in experimental conditions that are not always easy to report. Our approach covers 4 aspects that aim at improving the management and processing of ERT monitoring measurements. These can be listed as (1) checking and logging data acquisition job status, (2) structuring, documenting and storing incoming data, (3) efficiently retrieving and processing subsets of stored data, (4) structuring, documenting and storing processed results. Current developments show the added value of the project for subsurface imaging and data management in long-term ERT monitoring.

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