AN X-RAY IMAGING AND NUMERICAL SIMULATION MODELLING OF DIFFERENT IMMISCIBLE WATER ALTERNATING GAS INJECTION SCHEMES FOR OPTIMUM DISPLACEMENT EFFICIENCY

• Main Author: MIRKALAEI, SEYED MOUSA MOUSAVI
• Format: Thesis
• Language: English
• Published: 2012
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://utpedia.utp.edu.my/21684/1/2012%20-PETROLEUM-AN%20X-RAY%20IMAGING%20AND%20NUMERICAL%20SIMULATION%20MODELLING%20OF%20DIFFERENT%20IMMISCIBLE%20WATER%20ALTERNATING%20GAS%20INJECTION%20SHEMES%20FOR%20OPTIMUM%20DISPLACEMENT%20EFFICIENCY.pdf; http://utpedia.utp.edu.my/21684/

Water Alternating Gas (WAG) injection is a well-known Enhanced Oil Recovery process to improve sweep and displacement efficiency by gas trapping and controlling the mobility of gas. The main aim of the WAG injection is to maximize the three�phase flow region in the reservoir and minimize non-swept areas. The physics of the displacement processes during WAG injection is, however, complex due to three�phase flow in porous media. In this research, to better understand the active mechanisms of immiscible WAG (I-WAG), a series of visual experiments has been conducted on a 2-D sand pack using an X-Ray image technique with an industrial type of CT-Scan-high resolution�machine. The sand-pack is designed to simulate different schemes of I-WAG with considering the effects of viscous, gravity, and capillary forces in different injection orientations (horizontal and tilted) under ambient and elevated pressure and temperature conditions. The experiments are conducted in up-dip and down-dip orientations for injection. 2-D dynamic injection front profiles are captured that help to understand the swept area, three phase flow region, and mechanisms of I-WAG under the different schemes were studied. Simulation studies are also conducted based on the physical parameters of the sand-pack to simulate the experiments and to be able to run more sensitivity analysis. The trained simulation parameters were validated against the experimental results guide the field simulation of the same process.