Dense nonaqueous phase liquid (DNAPL) source zone characterization: Influence of hydraulic property correlation on predictions of DNAPL infiltration and entrapment

Abstract

[1] The influence of aquifer property correlation on multiphase fluid migration and entrapment was explored through the use of correlated and uncorrelated porosity, permeability, and capillary pressure-saturation (P c -Sat) parameter fields in a crosssectional numerical multiphase flow model. Data collected from core samples in a nonuniform sandy aquifer were used to generate three-dimensional aquifer parameter fields. Porosity was assumed to be uniform or simulated using sequential Gaussian simulation (SGS). Permeability (k) was modeled independently of porosity using SGS as well as simulated geostatistical indicator classes derived from measured grain size distribution curves. Retention characteristics were assigned employing Leverett scaling of a representative P c -Sat curve to the geostatistical k fields or, alternatively, on the basis of simulated indicator classes and porosity values. Ensemble dense nonaqueous phase liquid (DNAPL) infiltration and entrapment behavior for a hypothetical tetrachloroethylene (PCE) spill was simulated in four sets of two-dimensional profiles extracted from these realizations. Comparisons of saturation profiles and spatial moments from point source DNAPL infiltration simulations suggest that choices involving the geostatistical algorithm used to model k and the incorporation of variable versus uniform porosity have a smaller influence than choices involving the scaling of capillary retention properties to k. From these simulations it is apparent that the degree of spatial correlation in P c -Sat parameters exerts a controlling influence on predicted DNAPL spreading and redistribution in saturated aquifers. The resultant distribution of mass within a DNAPL source zone will have implications for DNAPL recovery and subsequent mass fluxes in remediation operations.

Lab Testing and Field Implementation of Soil Flushing

“…Since DNAPL ganglia were depleted and DNAPL pools were accumulated through the flushing following each spill, the ratio of PCE mass present in DANPL pools to that in DNAPL ganglia became higher and higher. Lemke et al (2005) also found out through numerical modeling that as PCE dissolved, the ganglia depleted much faster than the pools, the percentage of PCE mass in ganglia decreased and the DNAPL distribution became pool-dominated. PCE dissolution from the ganglia contributes more to the source strength; therefore, a slight reduction of PCE in the ganglia would result in a significant reduction in PCE effluent concentration.…”

“…The residual saturation values, S N , within the DNAPL columns were lower than S N in the DNAPL pools. The former are generally referred to as fingers or ganglia (Butcher and Gauthier, 1994;Lemke et al, 2005). At injection port 3, the pool spread from the up-gradient edge of the barrier and sank to the lower part of the domain and formed another pool on top of the next fine layer.…”

“…Both numerical modeling and intensive data collection have been conducted at the field and laboratory scales. These studies generally examine the reduction in mass flux in response to reduction in DNAPL mass (Falta et al, 2005b;Lemke et al, 2005). However, most DNAPL sites have evolved since the first spill event.…”

“…In the latter case, the site remediation goal is to remove sufficient DNAPL mass from the source zone to achieve the desired reduction in source strength, which results in either stabilization or shrinkage of the dissolved plume . The relationship between the amount of DNAPL mass depleted in the source and the resulting reduction in source strength is receiving increasing attention as a performance metric (Falta et al, 2005a;ITRC, 2004;Jawitz et al, 2005;Lemke et al, 2005;Rao et al, 2001;Rao and Jawitz, 2003;Sale and McWhorter, 2001). It is generally recognized that this relationship is a function of several parameters, including the aquifer hydrodynamic heterogeneity, the non-uniformity of DNAPL distribution, the correlation between hydraulic conductivity and DNAPL content, the DNAPL architecture, and the age of the site (the time since contamination event) (Jawitz et al, 2005;Rao et al, 2001;Rao and Jawitz, 2003).…”

Metric Identification and Protocol Development for Characterizing DNAPL Source Zone Architecture and Associated Plume Response

“…Experimental (e.g., Suchomel and Pennell (2006)) and numerical modeling studies have confirmed that even minor changes in subsurface characteristics (e.g., hydraulic conductivity distribution) can result in substantial changes to commonly employed metrics, such as the maximum organic saturation or the organic saturation spatial moments. Thus, NAPL properties, release characteristics and subsurface hydrogeology largely govern the resulting SZA (i.e., local scale DNAPL distribution) observed at field sites (Lemke et al 2004a;Lemke et al 2004b). …”