Photo of Dr Emma Michie

Dr Emma Michie PhD. MGeoSci. BSc

Lecturer in Geology Earth, Ocean and Ecological Sciences


Research Overview

I research into all things faulty, specifically aimed towards improving our ability to accurately assessing the integrity of potential CO2 storage sites. I examine the sealing potential of faults cutting a variety of sedimentary lithologies, including being one of few researchers actively working towards creating a predictive tool for carbonate fault seal potential.

Some examples of my research area are detailed below.

Carbonate Fault Seal

This is still a largely unknown topic with limited research and limited data. However, with collaboration with the University of Leeds, we have begun to fill this knowledge gap, and create a predictive algorithm for carbonate fault seal.
Utilising this knowledge, I also research into the impact of faults on groundwater flow, where some faults have shown to bound aquifers hosted in carbonate lithofacies.
This research involves understanding how different carbonate lithofacies deform, their fracture patterns, and resulting microstructures. This data can be used predictively to assess resulting permeability values.
As part of this research I also have begun to examine scenarios for which a permeability anisotropy may (or may not) occur within the carbonate fault rocks.

Fault Growth History

Important for derisking faults for CCS technologies, it is crucial to understanding how faults have grown, and where there may be high risk for across or up fault fluid flow. Breached relays may prove to be areas of high risk for CO2 storage within a site that is bound or cut by faults.

Seismic Interpretation Uncertainty

Peforming fault analysis in the subsurface relies on an accurate geological model, often utilising seismic data. However, there is a high degree of uncertainty when performing seismic interpretation. This research topic aims to reduce this uncertainty, by creating a best method practices for seismic interpretation of faults, which increases confidence when performing subsequent analyses such as fault growth analysis, fault seal or fault reactivation potential. This includes both manual seismic interpretation, and automated methods such as those utilising machine learning technologies.

Research Grants

Faulting in siliciclastic - carbonate sequences; an improved characterization for de-risking faulted CCS sites


September 2023 - May 2024