Simulation Improves Oil Shale Formation CharacterizationEngineering360 News Desk | February 13, 2017
Rice University engineers in Texas are using nanoscale science to improve hydrocarbon extraction via hydraulic fracking.
The research team combines nuclear magnetic resonance (NMR) and molecular dynamics simulations to characterize the amount of oil present and the difficulty involved in extraction.
Energy prospectors already use NMR to determine whether oil and/or gas are present in a shale formation. This method forces hydrogen atoms to align in response to an external magnetic field. Radio-frequency electromagnetic pulses are used to force the atoms to “relax” to their prior orientations. By measuring relaxation times, engineers can determine whether oil, gas, or water exists and how large the pores are that contain them.
This method works well in conventional reservoirs: the difference in relaxation times for water and the trapped hydrocarbon (T1 and T2) are distinct. In unconventional reservoirs, the relaxation times of the fluids are shorter, and they overlap. Determining contents of nanoscale rock pores is difficult.
The Rice team developed a computer simulation that mimic water, oil, and gas molecules’ relaxation properties and model how the molecules move in the highly restricted, “tight” pore formations. This information is matched with NMR results obtained from samples of kerogen—an organic component of shale—that is pumped out with fracking liquid when a well is drained. The modeling combined with NMR results enables more accurate identification of well contents.
One goal for the research team is to incorporate simulations into into iSAFT — inhomogeneous Statistical Associating Fluid Theory, a method developed by project engineer Walter Chapman. The research could also lead to improved fracking liquids.
“Our results challenge approximations in models that have been used for over 50 years to interpret NMR and MRI (magnetic resonance imaging) data,” Chapman says. “Now that we have established the approach, we hope to explain results that have baffled scientists for years.”