Supercomputing Improves Predictions of Fluid Flow in Rock

Reports on the use of supercomputers in the field of geology. The effort to collect and analyze data for a range of geologic materials is time consuming and leaves researchers with only static images of the dynamic process of fluid flow. From 2014 to 2018, researchers led by computational scientist James McClure of Virginia Tech used the 27-petaflop Cray XK7 Titan supercomputer at the US Department of Energy’s (DOE’s), Oak Ridge National Laboratory (ORNL) to advance the team’s computational code for modeling fluid flow in complex, porous geometries. Guided by synchrotron data, McClure’s team models the complex geometries of rocks, then simulates fluid flow based on fundamental physics principles. By combining modeling and simulation with in situ (or real-time) analysis, the team can predict the properties important to large-scale modeling of reservoirs.
Source: Computing in Science and Engineering - Category: Information Technology Source Type: research