Research improves visualization of the basement | Eurek alert!
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 simplified 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.
Advanced work is funded by a $328,000 grant from Saudi Aramco.
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 plotted 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 holds a Ph.D. from Texas A&M, and his research topic was advanced streamlining techniques, geologic model calibration, and rate optimization. In fact, he developed the streamlining software currently in use as part of his PhD project, so it seemed logical to provide the upgrade.
The software upgrade means Chen is improving the 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 linked into a chain in a video that unfolds in time, like a computer-animated film. Since particle locations are captured frame by frame, any changes in the flow field that disrupt particle motion will show up in the video.
Upgrading is a huge undertaking. Fortunately, Chen made a hobby of learning computer science and parallel computing during his graduate years, noting that these tools are extremely helpful in solving engineering problems. He puts this training to good use while designing the software architecture and algorithms to be efficient and practical enough for field application. However, the software must handle models with billions of cells in minutes and display near real-time motion video to be useful on site.
According to Chen, several aspects of the project are ready – the high-performance computing strategy, the hierarchy of functional modules and the data structures to be used as critical designs in the software. The project is progressing smoothly, but Chen mentioned caveats.
“Other challenges await us in the testing and debugging phase,” Chen said. “Most software engineers say to spend 20% of your time on implementation and 80% on testing and debugging. We face the challenge of large-scale models and time-consuming calculations, which makes debugging even more difficult. »
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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