Texas A&M Research Improves Underground Visualization
Accurately monitoring the flow rate of fluids injected downhole to enhance oil recovery is critical to improving the efficiency of reservoir production methods. Current software uses streamlined calculations to visualize flow numerically, but simplified calculations assume constant fluid velocity.
Texas A&M University researcher Dr. Hongquan Chen is leading a two-year project to upgrade the software with trajectory calculation visualizations, which can show how changing conditions underground affect speed and velocity. direction of fluids.
Since no cameras exist underground to show detailed reservoir activity, tracking the movement of the injected fluid is a matter of data-driven math and the laws of physics to visually render or create simulations of the reservoir. ‘flow. The Streamline software is fast enough to render an instant stream field, like a snapshot. Yet it cannot keep up with flow changes, especially when reservoir pressures drop or rise with starts or stops in adjacent wells. Trajectory calculations consider the fluid to be made up of individual particles, and all instances of each fluid particle’s movements are tracked and combined into a tracking stream, like a video.
“Think of the buildings on the Texas A&M campus as the underground geological structure and the students moving between them as individual fluid particles,” Chen explained. “The Streamlines would be the timed snapshots of security cameras tracking students exiting or entering buildings. Pathlines would track each student’s phone by GPS location as they walked their entire route to class. Thus, the streamlines assume a steady walk between buildings, and the trajectory lines indicate whether they ran, walked, or stopped to talk.
Chen improves software architecture to accommodate a robust parallel computing process while developing algorithms to plot the positions of fluid particles, or path segments, across time steps. Ultimately, all segments of the trajectory will be chain-linked in a time-flow video. Since particle locations are captured frame by frame, any changes in the flow field that disrupt particle motion will show up in the video.
The project currently focuses on fluid flow in conventional oil and gas reservoirs, but Chen said the trajectories could also reflect fluid migration in more complex reservoirs. The calculations could also work with gas injections, making it easy to track and display whether carbon dioxide or hydrogen is going deep into a storage tank or migrating to a high-risk leak location.
“We could even extend this to geothermal issues,” Chen said. “Like fluids, thermal energy can also be traced, although heat flow is more intangible. This could visualize any subsurface flow, whether fluid or heat. The potential is there.”
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