摘要

The risk and environmental impact assessments required for geological CO2 storage projects will have to rely on different types of numerical models, which will have to be calibrated and validated against measurements. Available measurements from ongoing demonstration projects are limited, hence it is necessary to turn to analog processes or laboratory experiments to estimate model parameters. In any case, parameter estimates will have uncertainties that will be important to assess when predicting future scenarios. %26lt;br%26gt;We study a model for the rise velocity of droplets in the ocean, an important process sub-model for simulating gas seeps into marine waters. As the origin we use the parameters estimation study by Bigalke et al. (2010) based on a tank experiment. We illustrate how Linearized Covariance Analysis (LCA) can be used to assess the parameter uncertainties, and how to design a similar experiment that reduces these uncertainties. The linearity assumption underlying LCA is assessed using curvature measures. It is shown that up to similar to 63% reduction in uncertainties is achieved by choosing the right droplet size distribution; by extending the range of droplet sizes to include larger droplets the uncertainties are reduced by another similar to 88%.

  • 出版日期2012-11