Participants in the DASDAE code sprint event at Mines in December 2022.

Posted by Eileen Martin

A major challenge for small R&D teams as they begin working with fiber-optic distributed acoustic sensing (DAS) is that DAS systems can easily collect large amounts of data, and there is little standardization of data formats across equipment manufacturers. This often leads each team to ‘reinvent the wheel’ and invest substantial time into writing similar basic codes for reading, pre-processing and visualization that are needed by many DAS users. Additionally, when advanced DAS processing techniques are shared as open source, the research community lacks a shared common set of data structures and basic codes for DAS data, making it difficult to ‘glue together’ different existing codes that make up full DAS processing workflows.

To address these challenges, Eileen Martin (PI) and Ge Jin (co-PI) are leading a team of students, postdocs, research associates, and other scientists in developing a collection of open-source Python packages, known as the DAS Data Analysis Ecosystem (DASDAE, which is pronounced like DAS-day). DASDAE is a collection of Python packages sharing a common code base found in the DASCore package. So far, the team is composed of people from multiple research areas at Mines, including from geophysics, hydrology, applied math and CIARC, as well as students from other universities including Rice University and University of Washington. CWP members involved include Derrick Chambers (lead developer of DASCore), Abdul Hafiz Issah, Eileen Martin, and Aaron Girard. In December ’22 we held an all-day code sprint to get more people started with contributions to DASCore and its documentation, and we plan to do similar events in the future. If you are interested in using or helping develop DASDAE packages, you can find out more at dascore.org.

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