Characterization of Petroleum-Hydrocarbon Fate and Transport in Homogeneous and Heterogeneous Aquifers Using a Generalized Uncertainty Estimation Method

by Li He, (corresponding author), (M.ASCE), Professor; Research Academy of Energy and Environmental Studies, North China Electric Power University, Beijing, China 102206; and Assistant Professor, Dept. of Civil Engineering, Ryerson Univ., Toronto, ON, Canada M5B 2K3, li.he@iseis.org,
Guo H. Huang, Professor; Research Academy of Energy and Environmental Studies, North China Electric Power University, Beijing, China 102206; and Professor, Environmental Systems Engineering Program, Faculty of Engineering, Univ. of Regina, Regina, SK, Canada S4S 0A2.,
H. W. Lu, Ph.D., (M.ASCE), Professor; Research Academy of Energy and Environmental Studies, North China Electric Power University, Beijing, China 102206.,


Serial Information: Issue 1, Pg. 1-8


Document Type: Journal Paper

Abstract: This paper presents a generalized uncertainty estimation method (GUEM) to characterize the fate and transport of petroleum-hydrocarbon contaminants in subsurface environments. Compared to the conventional methods, GUEM employs the Metropolis-Hastings sampling algorithm to replace the conventional Monte Carlo algorithm; this algorithm has the advantage of reducing computational cost in obtaining realizations of uncertain parameters. The GUEM method is applied to a hypothetical homogenous and a real-world heterogonous site for demonstration studies. The first demonstration shows that GUEM generates outputs with wider bounds than conventional uncertainty characterization methods. This avoids overestimation of lower bounds and underestimation of upper bounds of resulting modeling outputs. Results from the second demonstration implied that the groundwater would not be suitable for the drinking water source after three years of natural attenuation and remediation actions should be taken to guarantee the groundwater safety. Even after taking a three-year pump-and-treat remediation action, it would pose risks as one can conclude that the benzene concentrations would violate the regulated environmental guideline with a possibility of over 0.9, and enhanced remediation actions are still desired to be taken for improving the groundwater quality. Despite the advantages in characterizing the fate and transport of contaminants, GUEM could be improved by introducing two correlated random variables in the sampling process for enhancing simulation accuracy. It is also expected to be integrated with traditional methods such as Monte Carlo method and generalized likelihood uncertainty estimation method to deal with hybrid fuzzy-random and interval-random inputs, respectively.

Subject Headings: Uncertainty principles | Petroleum | Hydrocarbons | Aquifers | Homogeneity | Heterogeneity | Hybrid methods | Remediation | Algorithms | Monte Carlo method | Europe | Monaco | Monte Carlo

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