Fully Funded PhD in Characterising flow properties of faults on Malta

Location: United Kingdom
Application Deadline: 27 November 2024
Published: 8 months ago

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Description

Predicting flow properties of faults in the subsurface is challenging.  Although there are predictive tools applicable to siliciclastic lithologies, there remains a data and knowledge gap for carbonate lithologies, particularly those containing marl layers.  This project aims to fill this knowledge gap and improve our understanding and ability to predict whether aquifers within carbonate lithologies in Malta are acting as a homogeneous mass or are compartmentalised due to the faulting.

We will use field data collection, consisting of detailed structural maps of several faults across Malta and Gozo and sample collection for further analysis.  Fault rock samples from the blue clay smears will be measured for porosity, permeability and composition using X-ray diffraction analysis.

Further, a 3D geological framework model of Malta and Gozo will be created for predictions of fault behaviour in the subsurface, along with feeding into groundwater flow modelling.  Known aquifer properties will be used to perform hydrogeological modelling to quality control predicted fault behaviour, to modify and improve algorithms developed during this project using outcrop results.  Results will be used to assess the groundwater structure of Malta.

Results from this project will not only benefit groundwater management for the Maltese Islands but can also be used for groundwater systems elsewhere in similar lithologies, as well as being used for predictions of fault behaviour for CO2 storage sites that contain marl interbeds.

This project is fully funded through the Energy and Water Agency, Malta.  We are looking for a PhD student to start ASAP.

Your Qualifications:

A minimum of 2:1 BSc in a geological degree.

Background knowledge / experience preferable in: structural geology, fault analysis, carbonate petrography, microstructural analysis (optical / SEM), laboratory analysis.

A strong numerical background is encouraged.

Strong fieldwork experience essential.

Familiarity with industry software will be useful, but not essential.

 

Please contact Dr Emma Michie for further information: emma.michie@liverpool.ac.uk

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