Modeling Multiphase Contaminant Transport In Groundwater Systems Under Uncertainty

With the highly development of the petroleum industry, the environmental problems caused by petroleum leakage have become severe, and the key to the problem is simulation and prediction of contaminant transport and migration in subsurface environment. A foxy stochastic modeling system (FSMS) and a fuzzy-parameterized stochastic modeling system (FPSMS) were proposed in this study, which were based on multiphase numerical simulator, linear regression, Monte Carlo simulation technique and fuzzy transformation method. These two developed methods could be used to predict process of NAPL transport in the subsurface and access the impacts of uncertainties in it. Porosity and logarithmic value of intrinsic permeability in an experimental-scale spill event of light non-aqueous phase liquid (LNAPL) were used to demonstrate the applicability of the proposed methods. The study results proved that FSMS and FPSMS could be used to evaluate the joint impacts of highly uncertain inputs on the predictions of multiphase, which are good references for supporting risk assessment and remediation design for petroleum-contaminated sites.