Date: May 12, 2014

Time: 4:30 pm -

Location: Computer Science 104

Professor Christine Shoemaker, of Cornell University, will discuss “Using Monitoring and Optimization for Managing Environmental Risks Including Applications to Geological Carbon Sequestration” as part of the Andlinger Center’s 2013-2014 Highlight Seminar Series.

ABSTRACT
Geological Carbon Sequestration (GCS) involves the injection of pressurized CO2  over 1000m underground, to reduce atmospheric carbon.  Accurate estimation of CO2 plume development and pressure response can greatly enhance the safety of geological carbon sequestration (GCS) by indicating where to search for possible breaches in the integrity of the system, which might cause environmental damage. Unfortunately, few monitoring sites are feasible.  Our goal is to demonstrate an efficient computational process by which a combination of reservoir modeling, optimization, and uncertainty analysis can assess alternative sparse monitoring plans in terms of their ability to give an accurate estimate of current plume and forecast future plumes. The example application mimics a CO2 sequestration pilot test at Frio with saline aquifer injection. The TOUGH2 multiphase simulator takes 2 hours/simulation. We developed a method for lumping parameters, which is essential since the limited number of monitoring wells means that relatively few parameters can be estimated from available data. The plume position could be determined with an average correlation coefficient of up to R²=0.92 (for current plume) and R²=0.8 (for plume forecasted 5 years in future). These results were obtained using only pressure measurements, two monitoring wells, and a modest number of simulations. The speaker will also briefly describe two current energy-related studies using optimization a) for controlling hydropower and wind production at the 17 reservoir BPA system and b) for estimating parameters for the CLM 4.5, a major module in global climate models.

BIO
Christine Shoemaker’s research focuses on finding cost-effective, robust solutions for environmental problems by using optimization, modeling and statistical analyses. This includes development of general purpose, numerically efficient nonlinear and global optimization algorithms utilizing high performance computing (including asynchronous parallelism) and applications to data on complex, nonlinear environmental systems. Her algorithms address local and global continuous and integer optimization, stochastic optimal control, and uncertainty quantification problems. In her recent research, algorithm efficiency is improved with the use of surrogate response surfaces iteratively built during the research process and with intelligent algorithms that effectively utilize parallel and distributed computing. Her application areas include physical and biological groundwater remediation, carbon sequestration, pesticide management, ecology, and calibration of climate and watershed models. The optimization and uncertainty quantification effort is used to improve model forecasts, to evaluate monitoring schemes and to have a tool for comparing alternative water and environmental management practices. Algorithms that are efficient because they require relatively few simulations are essential for doing calibration and uncertainty analysis on computationally expensive engineering simulation models. Professor Shoemaker has also been involved in multidisciplinary international outreach/research efforts for protecting groundwater resources from contamination and in helping to bring more women in engineering and computational mathematics. Professor Shoemaker is a member of the National Academy of Engineering and is a Fellow in AGU, SIAM, INFORMS and Distinguished Member of ASCE.