Triassic reservoirs form one of the last remaining exploration targets and an important secondary objective across much of the UK and Norwegian North Sea. However poor seismic resolution, lack of age control and reliance on lithostratigraphic correlation schemes have hindered attempts to understand and predict these reservoirs.
Utilising a multidisciplinary approach including sedimentology, interpretation of seismic reflection data, biostratigraphy and heavy mineral analysis, coupled with AI and machine learning applied to Triassic strata of the Norwegian sector a new, high resolution stratigraphic scheme will be developed.
Work will combine palynology from mudstones and heavy mineral, geochemical and detrital zircon data from sandstones. These datasets will be used to establish the highest available temporal and spatial framework for the North Sea Triassic to date.
Utilising this framework, a core-based sedimentological scheme combined with analysis of seismic data to identify structural and halokinetic controls will novel neural network methodologies for facies identification in uncored intervals will allow regional mapping of discrete fluvial depositional systems.