UNIVERSAL REGIMES OF SUBMARINE FANS CONTROLLED BY GRADIENT, GRAIN SIZE AND MUD CONTENT: COMPARISON WITH HIGH RESOLUTION FIELD DATA (Invited Presentation)

Since self-formed channelization has proved difficult to reproduce in turbidity current experiments except over small windows of parameter space, a full investigation of submarine fan complexity requires high-resolution physics-based numerical models of submarine fan growth. For the first time, these models enable the quantification of autogenic growth patterns as a function of extrinsic forcing, and the evolution of the deposit itself, to predict stratigraphic patterns and reservoir properties. Such models illustrate interesting and universal morphodynamic regimes which can only be validated by comparison to high-resolution field data like shallow seismic, bathymetric data, and field process measurements.

By applying the depth-averaged approach EMURC has developed a fast (parallelized) simulator that provides sufficient speed and complex stratigraphic development (over millennia in model time with continuous flow), enabling the study of self-organization, pattern formation, and stratal architecture of submarine fan deposits at field scale. We test the hypothesis that the aforementioned processes are organized into distinct morphodynamic regimes controlling fan growth pattern, avulsion behavior, the hierarchy of lobes and channels, and stacking patterns. Regimes are mapped onto a 3D parameter space based on gradient, grain size, and mud content which control respectively the hydraulic mode (Froude number), sediment transport mode (Rouse number or particle Reynolds number), and bed cohesion.

Results indicate that while smaller coarse-grained fans on high gradients tend to be supercritical, larger finer-grained mud-rich fans on lower gradients tend to have predominately subcritical behavior. The most dynamically rich category are transcritical fans, oscillating between supercritical and subcritical flow because flow hydraulics can change rapidly around the Froude critical gradient.

In this presentation, we compare the stratal architecture of multiscale hierarchical channel and lobe patterns to field data from high-resolution seismic and bathymetric data. The results indicate that the model, while not perfect, is able to capture the basic architectural and autogenic regimes following similar trends to the field data, making it an excellent tool to generate scenarios for reservoir simulation.