The symposium will discuss the benefits and potential for HPC modeling and simulation in three sectors of North Dakota energy policy:
1. Oil and Gas Production. The endowment of conventional oil and gas resources provides new opportunities for growth and expansion. As the state has begun to produce additional barrels from CO2 enhanced oil recovery, substantial opportunities emerged in the form of residual oil zone (ROZ) production. Moreover, new geophysical and computational technologies hold the promise of retrieving ever increasing volumes from existing fields. These technologies include stochastic reservoir characterization, data mining, uncertainty quantification, and matched-field processing.
2. Wind Energy. Limitations on our ability to accurately predict wind reduces the profitability and output from wind farms and often cuts the longevity of the facilities by as much as 75%. Better wind power prediction from HPC systems has begun to increase the output from wind farms already and further HPC modeling and simulation could increase production by another 20-30%. Additionally, HPC modeling can better predict the availability of wind helping to stabilize grid transmission networks and improve export from remote areas to market.
3. Transmission. North Dakota will increasingly export electricity to nearby states, but will need to build and manage new transmission lines in order to do so. The North Dakota Transmission Authority, established in 2005, is looking to increase the state's energy export capacity to 7,500 megawatts by 2020. HPC can help the state address various challenges related to planning and building new transmission systems across a complicated multistate network. For example, HPC predictive modeling can facilitate the integration of renewable energy sources, often intermittent and produced in remote areas, into a larger grid system.
This symposium will help identify near-term opportunities in government and industry to accelerate energy technology development. The event will showcase the abilities of North Dakota State University's Center for Computationally-Assisted Science and Technology (CCAST) and as well as the enormous HPC capabilities of our national laboratories. This will provide North Dakota energy leaders with the opportunity to highlight their leadership in energy and create a blueprint for action in the State and at the national level.