Quantitative Palaeogeography and Source-to-Sink Modelling of the UK Triassic, East Irish Sea Basin

About the Project

Use cutting-edge numerical landscape evolution modelling to reconstruct Triassic sediment routing systems across the UK and predict reservoir and seal heterogeneity in the East Irish Sea Basin. Running the open-source goSPL model on regional palaeogeographic maps, and integrating provenance and denudation data, this quantitative PhD is ideal for a numerate geoscientist keen to develop coding and forward modelling skills.

Background and context

Predicting where good reservoirs and effective seals will be found in any sedimentary basin depends ultimately on understanding where sediment came from, how it travelled, and what controlled its composition and variability along the way. For the East Irish Sea Basin, that means understanding the Triassic source-to-sink system: the upland source areas, transport pathways and depositional basins that together determined what kinds of rock were laid down, and how heterogeneous they are.

Traditional palaeogeographic analysis addresses these questions qualitatively. Recent work by the supervisory team has demonstrated that quantitative methods can go substantially further, using numerical modelling to test competing source-to-sink scenarios against real observations and generate predictive maps of reservoir and seal heterogeneity. This PhD builds directly on that foundation, applying the latest generation of landscape evolution models to reconstruct Early and Late Triassic sediment routing across the UK and northwest Europe, with a particular focus on implications for the East Irish Sea.

What you will do

The core tool is goSPL, an open-source, Python-based landscape evolution model capable of simulating sediment routing at regional to global scales. You will run goSPL on reconstructed Triassic palaeogeographic maps, incorporating constraints on the denudation history of source areas and sediment provenance to generate quantitative predictions of what reached the East Irish Sea Basin and in what form. Multiple scenario models will be combined using established methods to produce common risk segment maps focused on reservoir and seal prediction.

The project spans both Early and Late Triassic, allowing comparison of the two systems and assessment of how changes in palaeogeography through time affected basin-fill character. Where the standard goSPL framework needs adapting to the specific demands of the problem, there is scope to develop and modify the code, making this a genuinely creative as well as analytical project.

You will work closely with published sedimentological, stratigraphic and provenance datasets and will engage with well log and seismic data from the East Irish Sea to ground-truth and calibrate your model outputs. The end-product will be a quantitative, predictive palaeogeographic framework with direct application to subsurface exploration and storage in UK and northwest European Triassic basins.

Training and collaboration

The project is based at Liverpool and supervised jointly by Peter Burgess and Richard Worden at Liverpool, with Stuart Jones at Durham contributing regional stratigraphic and provenance expertise. You will gain training in source-to-sink analysis, palaeogeographic reconstruction and numerical forward modelling, as well as developing coding skills in Python and the quantitative analytical methods needed to work with large-grid parallel model outputs. These are highly transferable skills across academic research, consultancy and the energy industry.

No prior experience with goSPL or landscape evolution modelling is required: training in these areas is built into the project from the start. A strong quantitative background and some coding experience are advantageous, but the supervisory team is well placed to bring a motivated geoscience graduate up to speed.

Project structure

The first year is focused on training in palaeogeographic reconstruction methods, goSPL fundamentals, and the regional Triassic geology of the study area, alongside initial model scoping runs. Years two and three move into full scenario modelling, calibration against observational data, and development of predictive maps. The final year is dedicated to synthesis and thesis writing. By the end of the project you will have a rare combination of deep geological understanding and quantitative modelling capability, positioning you well for research or applied roles in basin analysis, exploration geoscience and subsurface energy.

Candidates wishing to apply should complete the University of Liverpool application form to apply for a PhD in Earth Science. Please ensure you include the project title and reference number ENVI001 when applying.