Slurry transport modelling and applications in the gravel packing process

A three-layer model for solid-liquid flow in inclined pipes is developed. The steady-state model predicts the frictional pressure loss, critical velocity, concentration profile in the heterogeneous layer, mean heterogeneous layer and moving bed layer velocities, and bed layer heights for each set of parameters. We propose a modified correlation for the turbulent solids diffusivity, and include appropriate closures for forces and stresses attributed to the solids and liquid phases in the different layers. The proposed turbulent solids diffusivity correlation and the steady-state model predictions show a good agreement with experimentally measured results in the literature: for concentration profiles in the heterogeneous layer, pressure losses and critical (deposition) velocity, both over a wide range of parameters and for different regimes. We also define a critical Peclet number based on which, a transition boundary between bed-load and heterogeneous regimes can be found. Furthermore, we extend the three-layer model to annular geometry and utilize it for developing another model for gravel packing applications in oil & gas industry. In this operation, kilometers of sand can be successfully placed in horizontal wells, in what is called alpha-beta packing. We explain how bed height is selected via coupling between the inner and outer annuli and from the combined hydraulic relations of inner and outer annuli. We investigate the effects of important parameters such as the slurry flow rate, mean solids concentration, wash pipe diameter, leak-off rate, etc, on gravel packing flows, to give a fluid mechanics framework within which this process can be easily understood and analyzed. For improving the accuracy of the slurry flow predictions in different operating flow regimes we also develop a robust integrated method consisting artificial neural network (ANN) and support vector regression (SVR) to estimate the critical velocity, slurry flow regime change, and ultimately, the frictional pressure drop for a solid-liquid slurry flow in a horizontal pipe, covering wide ranges of flow and geometrical parameters. The prediction results of the developed integrated method show that it significantly outperforms those of the widely used existing correlations and models in the literature.