Evolution, Architecture and Hierarchy of Submarine Lobe Deposits: A High-Resolution Investigation from the Tanqua and Laingsburg Depocentres, SW Karoo Basin, South Africa

Amandine Prelat, David Hodgson, and Steve Flint
Earth and Ocean Sciences, University of Liverpool, Liverpool, United Kingdom

Terminal submarine lobes are the down-dip depositional record of sediments transported by density flows through continental margins. Modern and shallow seismic datasets provide excellent images of planform timeslices but limited information on the internal architecture, lithofacies, and depositional elements that comprise lobe deposits. Well exposed lobe deposits in the Tanqua and Laingsburg depocentres, Karoo Basin, South Africa were investigated to improve understanding of the evolution and architecture of deep-water distributive systems.

In the Tanqua study area, the results show that Fan 3 (lobe complex) is composed of six distinctive fine-grained sandstone packages (lobes). The lobes display compensational stacking patterns over scales of several kilometres. Intervals between lobes are thin-bedded and silt-prone; they do not change facies over several kilometres, and are therefore identified as a different architectural element. Each lobe consists of one to eight lobe elements, which also display evidence of compensational stacking patterns, which is interpreted to be driven by depositional topography and distributary channel avulsion. Thickness variations of lobe elements can be extremely abrupt, particularly in distal areas where isopach maps reveal a finger-like fringe to lobes comparable to those imaged on the modern seabed. Lobe deposits, therefore, are not simple radial sheet-dominated systems as commonly envisaged. The hierarchy of depositional elements developed in the Tanqua study has been successfully applied to Fan A in the Laingsburg depocentre, which is characterised by greater sediment supply and deposition on a deformed basin floor. This indicates that the hierarchy developed can be exported to subsurface datasets.

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