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Machine learning-based DAS data processing for geotechnical site characterisation of challenging soils

Project description

New methods to improve soil geotechnical site characterisation

Researching soils and their geotechnical site characterisations is key across many sectors, as it can provide valuable insights that could significantly affect agriculture, construction, preservation efforts, and even research initiatives. However, the geotechnical characterisation of challenging soils can prove significantly difficult, requiring advanced tools, methodologies, and so forth. With the support of the Marie Skłodowska-Curie Actions programme, the GEOTECH-OPT-DAS project aims to address these key challenges by developing novel methodologies to exploit surface waves from distributed acoustic sensors and enabling the use and repurposing of long fibre-optic cables to support geotechnical site characterisation of challenging soils. Fibre-optic surface monitoring will provide key data, enabling higher-accuracy models and more reliable findings.

Objective

The project will establish methodologies to exploit surface waves from Distributed Acoustic Sensing (DAS), making it possible to utilise and repurpose long fibre optic cables for geotechnical characterisation. DAS has been applied so far mostly inside boreholes, for VSP analysis and the surface waves components are not involved in the analysis. However, fibre-optics surface monitoring can provide loads of data to be inverted for 1D Vs-depth models. The combination of borehole DAS testing too, will provide essential information to be used in the building of the a-priori model, requirement for seismic surface waves inversion and hence will contribute to the reliable estimate of Vs variability over depth in questionable soils.
Furthermore, in terms of field testing, spiked geophones and active shooting will also be done in parallel to the DAS surveys, to get robust seismograms of the subsurface and distinguish which type of source creates each soil’s response. Overall, the innovation of field and lab testing relies in the fact that data will be acquired through both cutting-edge technologies (such as fibre-optics) and traditional geophysical seismic prospecting methods to combine these and explore how they can be bridged to soil mechanics laboratory testing too. The vision is to bridge geophysics for soil's mechanical properties and lab testing for small strain shear modulus to identify elements of agreement around soil’s strength and hence be able to eliminate borehole drilling for sampling and instead rely on surface seismic testing that is more environment friendly and in line with European Union’s priorities. In terms of data analysis, this relies on the application of machine learning to train models and develop toolboxes for automatic data processing that can be used for real-time soil characterisation through continuous monitoring.

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

UPPSALA UNIVERSITET
Net EU contribution

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€ 252 180,00
Address
VON KRAEMERS ALLE 4
751 05 Uppsala
Sweden

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Region
Östra Sverige Östra Mellansverige Uppsala län
Activity type
Higher or Secondary Education Establishments
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Total cost

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