Modelagem física de correntes de turbidez : descrição do processo e implicações no estudo dos depósitos turbidíticos

Abstract

The turbidity currents are responsible for the formation of the major hydrocarbon reservoirs around the world; however the fundamentals of such currents, both in theory and practice, are still unexplored to exhaustion nowadays. The description of initialization, transportation and deposition mechanisms of this process is surrounded by uncertainty. These uncertainties had inspired the accomplishment of a three series of experiments, in order to investigate it using two different physicals models. It were analyzed the geometrical, dynamical and depositional features of a turbidity current attempting to match the results of physical modeling to those found in natural outcrop. Granular materials are tested and grain size ranges for simulation are evaluated. Density currents with different densities, grain sizes, fluid injection rate and volume were generated. Therefore density current evolution, current velocity, geometric features, and bed forms were registered. The results show that velocity increases for larger current densities or smaller grain sizes and that the height of the current head increases when the current density decreases. The deposition volumes present a general tendency of exponential decline; the grain size range of the deposits decreases towards the distal portion of the channel. The results also show that advancing velocity and bed forms (it was observed the successive development of planar upper flow regime surfaces, low sinuous-ripples, middle sinuous-ripples, meandering channels and linear channels) depend basically of the flow oscillations identified in the fluid injection rate. The simulations presented intended to collaborate with the understanding of the natural phenomena, relating the current behaviour (flow parameters) with the generated deposit (turbidites), as well as indicated the applicability of physical modelling on the field of deep-water sedimentation and its reliability as a tool for hydrocarbon reservoir prediction.