Palaeo-Earth systems models (PESMs) calculating palaeoclimate, denudation and palaeo-oceanic tides and currents could potentially provide important input parameters useful for process-based forward modelling approaches to reservoir prediction. Earth systems models are based on the computation of physical processes that operate in the atmosphere and oceans. Although limited by grid size and cell size, combined tidal, palaeoclimate and denudation, these models provide a very broad spectrum of useful palaeoenvironment information for many areas globally where observational and/or proxy data are difficult or impossible to obtain directly from data. If properly derived and validated such models may provide the only effective way of deriving consistent, digital palaeoenvironmental parameters globally, which can provide significant predictive power for hydrocarbon exploration (e.g. Harris et al., 2017).
PESMs are founded on robust plate tectonic models that reconstruct the past positions and geometries of rigid and deformable tectonic plates of the Earth. These plate reconstructions control the spatial distribution of sea, land and mountains, forming the palaeotopographic and bathymetric boundary conditions in the creation of palaeo-digital elevation models (DEMs). These DEMs can be coupled with a PESM (UK Met Office HadCM3) and a palaeotide model (Imperial College, UK, ICOM) to provide quantitative palaeoenvironmental information for key Phanerozoic time slices.
Key outputs that can be derived from palaeogeography and PESMs include tectono-eustasy, tectonic uplift and tilting that controls denudation rates and drainage network development, continental hypsometry and including shelf width, surface air temperature, precipitation and resultant run-off used to predict siliciclastic sediment flux (e.g. Syvitski and Millman, 2007), sea-surface temperature that influences the distribution of hermatypic corals and calcareous green algae, ocean currents that control transport and deposition of suspended/bedload sediments, tidal range and flow velocities, and wind strength that controls wave regime and associated sediment transport rates. Many of these outputs are key parameters in the production of numerical or stratigraphic forward models (SFM). SFM is used to produce fully quantitative 3D deterministic stratigraphic and facies models that replicate and predict the stratal geometries, stratal architecture, sediment grain size, sedimentary thickness and facies formed under a set of predefined conditions, including those mentioned above. By integrating SFM with the parameters defined by PESMs as inputs to SFMs it is possible to convert 2D palaeogeographic maps into 3D palaeodepositional models, with potential predictive power.
The objective of this PhD is to use output from PESMs to produce integrated 3D palaeodepositional models using SFM software such as GPM, DionisosFlow and or CarboCAT, which can be compared against offshore subsurface data, e.g. 2D and 3D seismic imaging constrained by well data, to determine how robust the PESMs are. This will be done following a simple workflow:
Select consecutive time slices to test that are of interest to petroleum system development and have reasonable constraints on key data, e.g. a robust plate reconstruction with reliable continental DEM, and relatively high resolution palaeoclimate reconstructions
Calculate sediment supply to continental margins from the PESMs, and other key parameters e.g. water temperature, ocean current distribution, following Syvitski and Miliman (2007).
Construct a large-scale (grid cell size 10-50km) but simple SFM able to run for the time interval between the PESM time slices for the whole continental margin and distribute the supplied sediment using a simple down-slope diffusive sediment transport algorithm, combined with ocean current reworking using a simple link between current velocity, shear stress and sediment entrainment and deposition rates.
Compare the resulting large-scale stratal patterns with several seismic sections from the margin, and iterate both models until a reasonable fit is achieved.
Zoom-in on areas if key interest and construct smaller-scale Dionisos, GPM or CarboCAT models, as appropriate, using input parameters and boundary conditions from the large-scale model and the PESMs.
Compare smaller-scale SFM output with seismic data sets, refine input parameters as required and iterate to produce an optimal fit between seismic, well data and models, for example using available subsurface data sets from the Barents Sea or the Gulf of Mexico.
Analyse model output for predictions e.g. use multiple non-unique best-fit models to construct reservoir presence probability maps using the conditional frequency map approach from Burgess et al. (2006).
The student will spend 1 month per year working with the PESM development team in the CGG Robertsons office in North Wales.
Full funding (fees, stipend, research support budget) is provided by the University of Liverpool. Formal training is offered through partnership between the Universities of Liverpool and Manchester in both subject specific and transferable skills to the entire PhD cohort and at each University through local Faculty training programmes.
Burgess, P.M., Lammers, H., van Oosterhout, C., and Granjeon, D, 2006, Multivariate sequence stratigraphy: Tackling complexity and uncertainty with stratigraphic forward modeling, multiple scenarios, and conditional frequency maps, Bulletin AAPG, v. 90, p. 1883–1901.
Harris, J., Ashley, A., Otto, S., Valdes, P., Crossley, R., Preston, R., Watson, J., Goodrich, M. and the Merlin+ Project Team, 2017. Palaeogeography and palaeo-earth systems in the modelling of marine palaeoproductivity: a prerequisite for the prediction of petroleum source rocks. In: Mahdi A. AbuAli, Isabelle Moretti and Hege M. Nordgård Bolås (Eds.), Pteroleum Systems Analysis – Case Studies: AAPG Memoir 114, p. 37-60.
Syvitski, J.P.M. and Millman, J.D., 2007. Geology, geography, and humans battle for dominance over the delivery of fluvial sediment to the coastal ocean. Journal of Geology, 115, p. 1-19