Colloquium: Graduate Portfolio in Scientific Computation

The Spring Research Colloquium for Graduate Portfolio in Scientific Computation is scheduled for Tuesday, May 1, 9:30-10:30 AM in GDC 4.302






Gajanan Choudhary Tuesday, May 1 9:30–10:00 AM GDC 4.302  "Verification and Validation of Coupled 2D-3D Shallow Water Finite Element Models"
Chu-Hsiang Wu Tuesday, May 1 10:00–10:30 AM GDC 4.302  "Predicting Sand Production Through Gravel Packs"

Gajanan Choudhary 

(PhD, Engineering Mechanics, Cockrell School of Engineering, supervised by Dr. Clint Dawson)

Title: "Verification and Validation of Coupled 2D-3D Shallow Water Finite Element Models"

Abstract: Baroclinicity in oceans may necessitate the use of 3D shallow water (SW) models for accurate description of physics. Particularly for baroclinic flows near coastal areas where frequent wetting and drying occurs due to tides and wind, we need a 3D SW model that can handle wetting and drying. Various methods for wetting and drying are available for 2D SW models, but it remains a challenge for 3D SW models. We propose using non-overlapping coupled 2D-3D models for taking advantage of well-tested 2D wetting-drying techniques and 3D baroclinic transport, while avoiding the complexities of 3D wetting and drying. Previously, we developed a theory for algebraic coupling of 2D and 3D SW models in a conforming, continuous Galerkin finite element framework, with mass and momentum conservation across the 2D-3D interface built into the coupling. We now verify 2D-3D coupling against two test cases with known analytical solutions and also compare the results with those of equivalent full-2D and full-3D SW models. We validate our model against two test cases for which experimental data are available. We demonstrate an application of the 2D-3D coupled model on a Galveston Bay test case.

Chu-Hsiang Wu

(PhD, Petroleum Engineering, Cockrell School of Engineering, supervised by Dr. Mukul Sharma)

Title: "Predicting Sand Production Through Gravel Packs"

Abstract: A new approach for estimating sand production through gravel packs is presented in this paper. The approach involves two steps: (a) evaluating the pore throat size distribution (PoSD) of a gravel pack using a discrete element method (DEM), and (b) estimating sand production through the gravel pack using an analytical model. Results of the analytical model are compared with sand production data obtained from lab experiments and Monte Carlo simulations.

Results from DEM simulations show that the smallest and largest pore throats in a gravel pack are typically sized around 1/9 and 1/4.8 to 1/5.5 of the effective gravel diameter (Deff), respectively. These observations suggest that any formation sand grains larger than 1/5.5 Deff  will be retained near the sand-gravel interface, i.e. within 10 layers of gravel from the sand-gravel interface. Furthermore, the gravel pack alone cannot retain any formation sand smaller than 1/9 Deff for a typical thickness of the gravel pack. A secondary pack formed by retained formation sand is essential for effective sand retention in such cases. Increasing gravel packing thickness primarily improves the retention of sand sized between 1/5.5 to 1/9 Deff, and the effect is insignificant for sand out of this size range. Finally, the analytically estimated sand production using DEM-evaluated PoSDs agrees reasonably well with sand production data obtained from lab experiments and Monte Carlo simulations.

The proposed approach provides a time and cost-efficient way to predict the effectiveness of a gravel pack for any given formation sand size distribution. The approach accounts for the gravel particle size distribution and the thickness of the annular gravel pack. Application of this new approach can improve the reliability of sand control completions by better justifying a gravel design, specifically in reservoir sands with poor uniformity (i.e., high-fines).