Dense Non-aqueous Phase Liquid Source Zone Research Articles

Mapping and monitoring dense non-aqueous phase liquid source zone by fused surface and cross-borehole electrical resistivity tomography

Effective characterization of dense non-aqueous phase liquid (DNAPL) source zones is crucial for remediating polluted sites. DNAPL often reside as residuals or pools within high-permeability lenses and above impermeable layers due to soil heterogeneity, gravity, and capillary barriers. Given the high cost of drilling, electrical resistivity tomography (ERT) techniques—including surface ERT and cross-borehole ERT, are commonly used for DNAPL source zone mapping and monitoring. However, the low spatial resolution of ERT increases uncertainty in source zone investigations. This study proposes a method for improving DNAPL mapping and monitoring by fusing surface and cross-borehole ERT data. Sandbox experiments were conducted to simulate a heterogeneous DNAPL source zone, employing both ERT methods for static mapping and dynamic monitoring. Reflective light imaging (RLM) was used to visualize DNAPL migration and provide saturation data, allowing for the quantification of ERT's effectiveness in characterizing DNAPL distribution. The results indicate that individual ERT methods face significant challenges in DNAPL source zone mapping due to background interference. Surface ERT alone tends to underestimate the extent of deeper DNAPL source zones. However, fusing surface and cross-borehole ERT results in a complementary enhancement of vertical spatial resolution, thereby improving the characterization of DNAPL source zones. The fusion of static and time-lapse ERT data substantially enhances DNAPL source zone mapping and monitoring capabilities. By calculating the ratio of the ERT-monitored area to the actual area using resistivity change contours (5 %, 10 %, 15 %), it was found that fusing surface and cross-borehole ERT data improved monitoring resolution by 50.48 % compared to surface ERT alone and by 22.95 % compared to cross-borehole ERT. Principal component analysis (PCA) was effective in fusing time-lapse data, while the weighted average method (WAM) outperformed PCA for static resistivity data fusion.

Improved ERT imaging with 3-D surface-to-horizontal borehole configurations: relevance to dense non-aqueous phase liquids

SUMMARY Accurate characterization and monitoring strategies are essential for designing and implementing remedial programs for sites polluted with dense non-aqueous phase liquids (DNAPLs). Electrical resistivity tomography (ERT) is a widely used geophysical technique for mapping subsurface features and processes of interest, and exhibits desirable characteristics for DNAPL sites due to its ability to gather large volumes of continuous subsurface information in a non-invasive, cost-effective and time-efficient manner. However, ERT measured only from the surface suffers from poor imaging quality with depth. Enhanced ERT imaging can be obtained via electrodes deployed on the surface and within horizontal boreholes, but so far it has only been investigated for 2-D imaging. This study evaluates the potential of 3-D surface-to-horizontal borehole (S2HB) ERT configurations for imaging 3-D DNAPL source zones. Laboratory tank experiments were first conducted with a 3-D S2HB ERT configuration, which consisted of a surface grid and a single borehole line of electrodes, being used to monitor DNAPL migration within porous media. Results demonstrate that 3-D S2HB ERT with a single borehole provides improved sensitivity at depth, and therefore enhanced imaging compared to conventional 3-D surface ERT. Further tank experiments were performed to assess the performance of single borehole S2HB ERT when (i) the distance between surface and borehole is increased, and (ii) additional horizontal boreholes are included. The S2HB ERT with a single borehole significantly outperforms surface ERT at larger depths, and performs comparably to S2HB ERT using multiple boreholes. This study suggests that 3-D S2HB ERT with a single borehole can provide the enhanced imaging ability needed to map DNAPLs, while also being relatively practical for implementation at field sites.

Rock core VOC profiles diagnostic of aquitard occurrence and integrity in a multi-layered sedimentary rock aquifer flow system

Aquitard assessment poses a challenge for practitioners and researchers managing dense non-aqueous phase liquid (DNAPL) contaminants in sedimentary rock aquifer systems. Within these systems, DNAPL migration and bulk hydraulic properties are controlled by fracture networks which are difficult to characterize at relevant scales with conventional methods. A previous study at a DNAPL contaminated site used contrasts in high-resolution vertical gradients to delineate four aquitards and two surfaces with poor vertical connectivity within a thick (>200 m) sedimentary rock aquifer system primarily composed of layered sandstones. In this study, we corroborate that method by using the existing DNAPL contamination as a tracer to identify and characterize the aquitards in the sequence and assess aquitard integrity. Closely spaced samples of rock from four continuous cores were collected and analyzed for volatile organic compounds (VOCs). The cores were collected along a transect perpendicular to groundwater flow and 75 m downgradient of the DNAPL source zone. Dissolved phase contaminant concentrations were collected using high-resolution multilevel systems placed along the plume centerline, downgradient from the source. The rock core and groundwater VOC concentration profiles suggest a primary aquitard limits vertical migration of both DNAPL and the associated dissolved phase contaminants, despite relatively large, downward gradients across its lower boundary. A calibrated, three-dimensional numerical groundwater flow model indicates an anisotropy factor of 1,000 for this aquitard. The Kv values for all four aquitards are only slightly lower than the values for the aquifers. However, the aquitard Kv values are 1–3 orders of magnitude less than their Kh values, and the aquitard Kh values are often similar to or even greater than the Kh values for the aquifers. Therefore, large anisotropy, rather than exceptionally low Kv values, distinguish the aquitards from the aquifers in this system. Fracture network characterization of nearby outcrops showed the anisotropy of the aquitards can be attributed to laterally extensive, bedding parallel partings coupled with short, frequently terminating, and poorly connected vertical fractures. In addition, the rock VOC profiles combined with fracture network data show that fracture termination surfaces can be powerful inhibitors of downward DNAPL migration providing additional evidence for the importance of these features in sedimentary rock flow systems. Ultimately, this study reveals the important influence of anisotropic aquitards on DNAPL migration, accumulation, and persistence, as well as associated plume migration. Furthermore, it demonstrates that subtle contrasts critical to aquitard integrity may be easily missed with long screened wells and other conventional, low resolution site characterization methods.

Characterization of DNAPL source zones in clay-sand media via joint inversion of DC resistivity, induced polarization and borehole data

Toxic organic contaminants in groundwater are pervasive at many industrial sites worldwide. These contaminants, such as chlorinated solvents, often appear as dense non-aqueous phase liquids (DNAPLs). To design efficient remediation strategies, detailed characterization of DNAPL Source Zone Architecture (SZA) is required. Since invasive borehole-based investigations suffer from limited spatial coverage, a non-intrusive geophysical method, direct current (DC) resistivity, has been applied to image the DNAPL distribution; however, in clay-sand environments, the ability of DC resistivity for DNAPLs imaging is limited since it cannot separate between DNAPLs and surrounding clay-sand soils. Moreover, the simplified parameterization of conventional inversion approaches cannot preserve physically realistic patterns of SZAs, and tends to smooth out any sharp spatial variations. In this paper, the induced polarization (IP) technique is combined with DC resistivity (DCIP) to provide plausible DNAPL characterization in clay-sand environments. Using petrophysical models, the DCIP data is utilized to provide tomograms of the DNAPL saturation (SN) and hydraulic conductivity (K). The DCIP-estimated K/SN tomograms are then integrated with borehole measurements in a deep learning-based joint inversion framework to accurately parameterize the highly irregular SZA and provide a refined DNAPL image. To evaluate the performance of the proposed approach, we conducted numerical experiments in a heterogeneous clay-sand aquifer with a complex SZA. Results demonstrate the standalone DC resistivity method fails to infer the DNAPL in complex clay-sand environments. In contrast, the combined DCIP technique provides the necessary information to reconstruct the large-scale features of K/SN fields, while integrating DCIP data with sparse but accurate borehole data results in a high resolution characterization of the SZA.

Numerical investigations of influence on thermal conductive heating in DNAPL-impacted soils by heterogeneity

The treatment of dense non-aqueous phase liquid (DNAPL) source zones is challenging, particularly in heterogeneous media. Thermal conductive heating (TCH) has the potential to treat DNAPL source zones for its ability to enhance mass transfer. This study uses numerical modeling combined with Monte Carlo simulation to examine the influence of heterogeneity of the permeability field on the DNAPL distribution and TCH remediation. It is found that the longer horizontal correlation length of high-permeable clay lens would contribute to accelerate multiphase convection and then heat conduction in horizontal direction. The presence of DNAPL (both in NAPL phase and dissolved), pressure, and permeability are all contributory factors to phase change. Realizations with shorter horizontal correlation lengths always have a larger vertical spreading of DNAPL. As a shallow vapor extraction well was applied in this study, higher TCE removal rate can be obtained in the realizations with a shorter horizontal correlation length when NAPL phase of TCE is existed in the domain.

Mass-flux Reduction and Mass Removal Relationships (MFR-MR) of Pool-dominated Multicomponent DNAPLs in Heterogeneous Geological System

<p>Contamination of groundwater by chlorinated solvents such as trichloroethylene (TCE, tetrachloroethylene (PCE), and 1,1-dichloroethylene (1,1DCE) is a widespread problem that can seriously threaten human health and the environment. These compounds are often present as dense nonaqueous phase liquid (DNAPL) mixtures in the subsurface that serve as a long-term groundwater contamination sources. The objective of this study is to test the effectiveness of different in-situ flushing agents (SDS, Tween 80, MCD, and water) for the recovery of DNAPL mixtures (TCE, PCE, 1,1DCE) entrapped in heterogeneous aquifer media. A series of batch tests were first performed to assess the multiphase behavior of water-DNAPL mixture-reagent system. Intermediate scale tank experiments were then performed to compare the performance of the reagent solutions. The flushing breakthrough curves were also used to investigate the impact of solubilization agents on mass-flux reduction/mass-removal behavior relationships. Performance of agents on DNAPL mixture source zone remediation was found to be in the following order: Tween 80>SDS>MCD>>Water. Individual DNAPL constituents exhibited transient effective solubilities that depend on the reagent contents and DNAPL compositions. Although high fractions of DNAPL source zones in heterogeneous porous media were removed through chemical flushing (SDS, Tween 80, MCD, and water), the heterogeneous system exhibited an extended multi-step concentration behavior. The results emphasized that in the early stage, some portion of the organic liquid is hydraulically accessible (matrix) whereas the later stage of mass removal was controlled by the more poorly accessible mass (pool) associated with higher-saturation zones. Our results also showed that the distribution and the emplacement of organic liquid, flow-field heterogeneity, sorption and desorption, and flushing solution all influenced the DNAPL mixture removal. The results from this study underline the need for understanding the multiphase behaviour of a system, particularly when DNAPL mixtures are present, prior to field-scale remediation implementation.</p>

An approach for quantification of the heterogeneity of DNAPL source zone geometries

Many studies have investigated the migration and entrapment processes of source zones from dense non-aqueous phase liquid (DNAPL) contamination under different conditions. However, the characterization of occupying area by source zone (or source shape) in water-saturated aquifers is still rudimentarily considered. In this study, we demonstrated this issue (1) by providing a brief review of existing approaches for source shape consideration, (2) by proposing an approach with simple shape parameters based on the non-uniformity of source widths, and (3) by providing exemplary applications of our proposed approach on shapes already published in previous research works. Our literature review suggested that the source zone in mathematical approaches is generally characterized as simple geometrical shapes (arbitrary lines or rectangles) or system-defined parameters that contrast to complex and discontinuous shapes observed in the real world. But the characterization of such complex shapes is still not possible with acceptable efforts. Therefore, we proposed an approach to parameterize the source shape by considering the variation of width and midpoints over the depth of the entire source zone and formulate four parameters based on population statistics (mean, standard deviation). To illustrate the suitability of our approach, we applied it to the results of lab experiments, and by analyzing these complex shapes, we highlighted the potential for improving the characterization techniques of non-uniformity of the source zones.

Deep learning based optimization under uncertainty for surfactant-enhanced DNAPL remediation in highly heterogeneous aquifers

The optimization for surfactant-enhanced aquifer remediation (SEAR) of dense non-aqueous phase liquid (DNAPL)-contaminated aquifers is usually accompanied by uncertainties, which may arise from the characterization of complex aquifer heterogeneity and DNAPL source zone architecture (SZA) due to measurement sparsity. Optimization under uncertainty is computationally expensive as it involves an enormous number of model runs. The huge computational burden can be alleviated by utilizing a surrogate model for repeated model evaluations. However, most of the developed surrogates are often limited to low-dimensional optimization problems that only consider simplified aquifer heterogeneity. In this study, we developed a multi-objective simulation-optimization framework to optimize the SEAR schemes considering the characterization uncertainties from both highly heterogeneous aquifer permeability and complex SZA. A fast-to-run convolutional neural network (CNN)-based surrogate model was developed to approximate the high-dimensional and highly complex input-output mapping of the DNAPL multiphase flow simulation model. We first used the rejection sampling strategy to generate random realizations of permeability and SZA conditioning on their limited measurements and then formulated a multi-objective optimization under uncertainty problem based on these realizations. The developed 3-D CNN was trained and used as the surrogate for repeated model runs in optimization to identify the optimal SEAR schemes under uncertainty. A 3-D numerical experiment was used to test the performance of the CNN-based simulation-optimization framework. Comprehensive analysis on the obtained Pareto fronts demonstrates that the proposed framework can efficiently identify reliable Pareto-optimal solutions with a 99.8% speedup compared to the traditional optimization coupled with the forward model. Moreover, the optimization considering multiple realizations enables us to perform the risk assessment to locate the risk zone where the NAPL phase possibly exists after remediation, which provides useful information for decision-making.

Mapping and Monitoring of DNAPL Source Zones With Combined Direct Current Resistivity and Induced Polarization: A Field‐Scale Numerical Investigation

AbstractDirect current (DC) resistivity has been widely investigated for non‐invasive mapping of dense non‐aqueous phase liquids (DNAPLs); however, due to its difficulty in distinguishing DNAPLs from adjacent soils, the DC method is limited for static detection of DNAPLs and more often employed for monitoring DNAPL changes over time. Time‐domain induced polarization (IP) can provide complementary information to better discriminate between DNAPL, water and surrounding soils. Since highly resistive DNAPLs tend to laterally spread and pool on polarizable (chargeable) clay lenses, combined DC and IP (DCIP) has the potential to enhance static detection, and also monitoring of DNAPL source zones (SZs). The objective of this study is to assess DCIP for characterizing and monitoring DNAPL SZs at the field‐scale. A new DNAPL‐DCIP numerical model was first developed that couples a 3D multiphase flow model, which simulates DNAPL release and remediation scenarios, with a 3D DCIP model, which calculates the corresponding resistivity and chargeability response. The sensitivity of the DCIP response to key DNAPL and soil properties was then analyzed at a single subsurface location, closely matching previous theoretical and experimental observations. Finally, a field‐scale simulation of DNAPL release and remediation was conducted, with simultaneous mapping by DCIP surveys. Results demonstrate that chargeability can provide enhanced understanding of the lithological distribution that controls the variability in the DNAPL SZ, with time‐lapse resistivity being used to monitor DNAPL mass changes during SZ remediation. This numerical study suggests that combined DCIP can be valuable for site characterization and time‐lapse monitoring performance at DNAPL‐impacted sites.

Evaluation of the benefits of improved permeability estimation on high-resolution characterization of DNAPL distribution in aquifers with low-permeability lenses

High-resolution characterization of dense non-aqueous phase liquid (DNAPL) source zone architecture (SZA) is crucial for developing remediation strategies. Inverse modeling approaches are widely used to characterize DNAPL SZA. However, unknown parameters (permeability and DNAPL saturation) are usually assumed as Gaussian distribution in traditional geostatistical inverse methods (e.g., ensemble smoother with multiple data assimilation, ESMDA). This assumption may not be true in channels of fluvial deposits. The presence of clay lenses will bring significant challenges in reconstructing the DNAPL SZA using geostatistical inverse methods based on the Gaussian assumption. Moreover, the DNAPL characterization also suffers from a limited number of borehole data in the field. In this study, we use ESMDA's variant, ensemble smoother with multiple data assimilation-direct sampling (ESMDA-DS), to improve the estimation of non-Gaussian permeability field and evaluate the benefits of improved permeability estimation on the reconstruction of DNAPL source zone. The inversion technique is based on the iterative inversion framework to incorporate the clay content information into the DNAPL characterization. The performance of our proposed framework is examined and discussed through a numerical synthetic case with challenging pool-dominated SZA. To overcome data scarcity, we integrated hydrogeological and geophysical (electrical resistance tomography) datasets. Results show that the permeability is characterized well using ESMDA-DS method compared with ESMDA method. With the improved permeability estimation, the DNAPL source zone can be characterized in higher resolution. Compared with ESMDA method, the root mean square error (RMSE) of permeability is reduced by 38.5% using the ESMDA-DS method. Then the estimation RMSE of DNAPL saturation is reduced by 24.9% by improved permeability estimation. We also demonstrated the significant benefits of improved permeability estimation on DNAPL depletion behavior and plume evolution. Numerical simulations demonstrate with the improved permeability estimation, the DNAPL depletion prediction is highly improved, the prediction RMSE of the DNAPL dissolved plume is reduced by 34.5% after 50 years.

Integrating deep learning-based data assimilation and hydrogeophysical data for improved monitoring of DNAPL source zones during remediation

Data assimilation techniques allow the integration of multi-source data with physical modeling of dense nonaqueous phase liquid (DNAPL) source zones to monitor their evolution in time and thereby improve remediation efforts. The DNAPL source zone is governed by multiphase physics and its architecture is usually highly irregular and nonstationary. Traditional data assimilation methods use stationary models to describe these nonstationary DNAPL saturation fields, leading to significant errors in the estimation of unknown source zone architectures (SZAs). In this study, we propose a geostatistical data assimilation method to improve performance monitoring of DNAPL remediation. We estimate the DNAPL SZA after parameterizing the DNAPL saturation field using a deep learning method instead of a stationary statistical model. First, we train a convolutional variational autoencoder (CVAE) network to capture the physics of DNAPL infiltration and depletion. Then, we incorporate the CVAE network within the Ensemble Kalman filter (EnKF) to resolve the evolving DNAPL SZA by assimilating time-lapse hydrogeophysical measurements (i.e., oscillatory hydraulic tomography, downgradient dissolved DNAPL concentration, and electrical resistivity tomography). To assess the proposed CVAE-EnKF framework's performance, we conducted numerical experiments with evolving DNAPL SZAs in a 2D heterogeneous aquifer. Results show that the proposed framework significantly improved DNAPL saturation estimates throughout the source zone over time, compared to the standard EnKF method. CVAE-EnKF reduced the estimation error of DNAPL mass remediated by 51% from EnKF, along with better predictions of source zone longevity. It also better captured the morphology and center/spread of mass of the evolving remediated portions of the source zone and provided better estimates of pooled-DNAPL mass. Furthermore, the CVAE-EnKF method is more stable and converges faster than EnKF alone. Overall, the proposed data assimilation framework can improve real-time monitoring of DNAPL remediation and risk analysis.

Integrating hydraulic tomography, electrical resistivity tomography, and partitioning interwell tracer test datasets to improve identification of pool-dominated DNAPL source zone architecture

High-resolution characterization of complex dense non-aqueous phase liquid (DNAPL) contaminated sites is crucial for developing effective remediation strategies. The DNAPL source zone is usually characterized by hydraulic/partitioning tracer tomography (HPTT). However, the HPTT method may fail to capture the highly saturated pool-dominated DNAPL source zone architecture (SZA), because partitioning tracers tend to bypass the low-permeability zones where the pool DNAPL accumulates, resulting in a low-resolution DNAPL estimation. With a limited number of measurements, the estimation errors may be significant. To overcome these difficulties, time-lapse electrical resistivity tomography (ERT) was integrated with the partitioning interwell tracer test (PITT) and hydraulic tomography (HT) to characterize the pool-dominated DNAPL SZA. Herein, we proposed an iterative joint inversion framework coupling the multiphase flow model with the ERT forward model to estimate the heterogeneous permeability distribution and DNAPL SZA. Under this framework, permeability was estimated using the hydraulic head data from HT in stage 1, and the DNAPL SZA was subsequently estimated by assimilating both the PITT and ERT observations in stage 2. The permeability estimated from stage 1 was used as prior information for stage 2, and the DNAPL saturation estimated from stage 2 was served as prior information for stage 1 in the next loop to form an iterative loop to improve the estimation of both permeability and DNAPL SZA. The iterative joint inversion framework was evaluated in two numerical experiments with different heterogeneous structures by assimilating multi-source datasets, including hydraulic head, partitioning interwell tracer concentration, and electrical resistivity. Results show that with limited measurements of HPTT method, one can roughly capture the DNAPL distribution, missing the fine structure of the DNAPL SZA. In contrast, by incorporating multi-source datasets, the heterogeneous permeability and DNAPL SZA can be reconstructed with a higher resolution. Furthermore, the inversion accuracy of the DNAPL SZA improves progressively as the iteration proceeds, which demonstrates the advantage of utilizing complementary information from permeability and DNAPL distribution through the iteration framework. Comparing with the results without loop iteration, the estimation error is reduced by 17.3% for permeability and 8.6% for DNAPL saturation in Experiment 1; by 14.7% for permeability and 11.2% for DNAPL saturation in Experiment 2 through the iterative framework. To further evaluate our framework, we preformed the prediction of the depletion process of the DNAPL source zone and plume based on the estimated DNAPL SZA. Results show that using the iterative framework, the prediction of the SZA depletion is greatly improved, i.e., the estimation error of the dissolved downstream plume from the DNAPL source zone after 3 years is reduced by 20.9% in Experiment 1, and by 43.2% in Experiment 2, respectively, through the iterative framework. This significant improvement is because the iterative method can better capture the spread of DNAPL pool.

Hydrogeophysical Characterization of Nonstationary DNAPL Source Zones by Integrating a Convolutional Variational Autoencoder and Ensemble Smoother

AbstractDetailed characterization of dense nonaqueous phase liquid (DNAPL) source zone architecture (SZA) is essential for designing efficient remediation strategies. However, it is difficult to characterize a highly irregular and localized SZA, because traditional drilling investigations provide limited information. With limited data, the estimation accuracy of traditional geostatistical methods is strongly affected by the parameterization of the prior description of the SZA. To improve characterization performance, we parameterized the DNAPL saturation field using a physics‐based approach. We trained a convolutional variational autoencoder (CVAE) using data from multiphase modeling that captures the physics of DNAPL infiltration. The trained CVAE network was used in SZA inversion to obtain an improved prior DNAPL saturation field, instead of the typical stationary prior covariances. We then integrated the CVAE network into an iterative ensemble smoother (ES), to formulate a joint inversion framework. To overcome difficulties from limited/sparse data, we incorporated hydrogeological and geophysical datasets in the proposed inversion framework. To evaluate the performance of our method, we conducted numerical experiments in a hypothetical heterogeneous aquifer with an intricate SZA. The results show that the CVAE was an effective and efficient parameterization method which can capture the DNAPL infiltration patterns better than a Gaussian prior. The improved prior, combined with multisource datasets, can result in better resolution, and overall improved SZA characterization. In contrast to the standard ES method, the proposed framework reconstructed the SZA more accurately. We also demonstrated that DNAPL depletion behavior and dissolved concentration profiles can be predicted accurately using the estimated SZA.

Towards predicting DNAPL source zone formation to improve plume assessment: Using robust laboratory and numerical experiments to evaluate the relevance of retention curve characteristics

We conducted multiple laboratory trials in a robust and repeatable experimental layout to study dense non-aqueous phase liquid (DNAPL) source zone formation. We extended an image processing and analysis framework to derive DNAPL saturation distributions from reflective optical imaging data, with volume balance deviations < 5.07%. We used a multiphase flow model to simulate source zone formation in a Monte Carlo approach, where the parameter space was defined by the variation of retention curve parameters. Integral and geometric measures were used to characterize the source zones and implemented into a multi-criteria objective function. The latter showed good agreement between observation data and simulation results for effective DNAPL saturation values > 0.04, especially for early stages of DNAPL migration. The common hypothesis that parameters defining the DNAPL-water retention curves are constant over time was not confirmed. Once DNAPL pooling started, the optimal fit in the parameter space was significantly different compared to the earlier DNAPL migration stages. We suspect more complex processes (e.g., capillary hysteresis, adsorption) to become relevant during pool formation. Our results reveal deficits in the grayscale-DNAPL saturation relationship definition and laboratory estimation of DNAPL-water retention curve parameters to overcome current limitations to describe DNAPL source zone formation.

Improved Characterization of DNAPL Source Zones via Sequential Hydrogeophysical Inversion of Hydraulic‐Head, Self‐Potential and Partitioning Tracer Data

AbstractHigh‐resolution characterization of hydraulic properties and dense nonaqueous phase liquid (DNAPL) contaminant source is crucial to develop efficient remediation strategies. However, DNAPL characterization suffers from a limited number of borehole data in the field, resulting in a low‐resolution estimation. Moreover, high‐resolution DNAPL characterization requires a large number of unknowns to be estimated, presenting a computational bottleneck. In this paper, a low‐cost geophysical approach, the self‐potential method, is used as additional information for hydraulic properties characterization. Joint inversion of hydraulic head and self‐potential measurements is proposed to improve hydraulic conductivity estimation, which is then used to characterize the DNAPL saturation distribution by inverting partitioning tracer measurements. The computational barrier is overcome by (a) solving the inversion by the principal component geostatistical approach, in which the covariance matrix is replaced by a low‐rank approximation, thus reducing the number of forward model runs; (b) using temporal moments of concentrations instead of individual concentration data points for faster forward simulations. To assess the ability of the proposed approach, numerical experiments are conducted in a 3‐D aquifer with 104 unknown hydraulic conductivities and DNAPL saturations. Results show that with realistic DNAPL sources and a limited number of hydraulic heads, the traditional hydraulic/partitioning tracer tomography roughly reconstructs subsurface heterogeneity but fails to resolve the DNAPL distribution. By adding self‐potential data, the error is reduced by 24% in hydraulic conductivity estimation and 68% in DNAPL saturation characterization. The proposed sequential inversion framework utilizes the complementary information from multi‐source hydrogeophysical data sets, and can provide high‐resolution characterizations for realistic DNAPL sources.

The dissolution and microbial degradation of mobile aromatic hydrocarbons from a Pintsch gas tar DNAPL source zone

Source zones containing tar, a dense non-aqueous phase liquid (DNAPL), can contaminate groundwater for centuries. A common occurrence of tar is at former Pintsch gas factories. Little is known about the composition and fate of contaminants dissolving from Pintsch gas tar DNAPL. In this study, we determined the composition and water-soluble characteristics of mobile aromatic hydrocarbons and their biodegradation metabolites in the DNAPL contaminated groundwater at a former Pintsch gas tar plant. We assessed the factors that determine the fate of observed groundwater contaminants. Measured values of density (1.03–1.06 kg/m3) and viscosity (18.6–39.4 cP) were found to be relatively low compared to common coal tars. Analysis showed that unlike common coal tars phenanthrene is the primary component rather than naphthalene. Moreover, it was found that Pintsch gas tar contains a relatively high amount of light molecular aromatic hydrocarbon compounds, such as benzene, toluene, ethylbenzene and xylenes (BTEX). Less commonly reported components, such as styrene, ethyltoluenes, di-ethylbenzene, 1,2,4,5-tetramethylbenzene, were also detected in water extracts from Pintsch gas tar. Moreover, 46 relatively hydrophilic metabolites were found within the tar samples. Metabolites present within the tar suggest biodegradation of mobile aromatic Pintsch gas tar compounds occurred near the DNAPL. Based on eleven detected suspect metabolites, a novel anaerobic biodegradation pathway is proposed for indene. Overall, our findings indicate that Pintsch gas tar has higher invasive and higher flux properties than most coal tars due to its relatively low density, low viscosity and, high content of water-soluble compounds. The partitioning of contaminants from multi-component DNAPL into the aqueous phase and re-dissolution of their slightly less hydrophobic metabolites back from the aqueous phase into the DNAPL is feasible and demonstrates the complexity of assessing degradation processes within a source zone.

Application of spectral induced polarization for characterizing surfactant-enhanced DNAPL remediation in laboratory column experiments

The widespread presence of entrapped dense non-aqueous phase liquid (DNAPL) in the subsurface poses a continuing challenge to groundwater remediation. Cost-effective and high-resolution subsurface characterization is a critical issue for further DNAPL recovery due to the complexity of DNAPL source zone architecture (SZA). Geophysical techniques provide a noninvasive, spatially continuous and cost-effective way for monitoring the DNAPL remediation process. In particular, the spectral induced polarization (SIP) method has shown great potential in environmental problems. In this study, we performed real-time SIP measurements on DNAPL contaminated soil in columns to quantitatively assess the ability of SIP method for monitoring surfactant-enhanced DNAPL remediation process. Chemical data was simultaneously collected during the remediation process to verify the results obtained by SIP method. Taking account into the variations of subsurface environment, we conducted a series of column flushing experiments under different flow rate, surfactant concentrations and fluid salinities. The results highlight that SIP method is able to effectively monitor the DNAPL remediation process, as well as to evaluate the remediation efficiency under different conditions. The variations in the flow rate, the concentration of surfactant and the salinity of pore water not only affect remediation effectiveness, but also have an impact on the SIP signatures. This study shows that SIP performs better for monitoring DNAPL remediation at a relatively low flow rate of ~ 0.4 m/d, low surfactant concentration of 5000 mg/L and high salinity of 1.0 S/m, with an error of saturation estimation (RMSES) <0.1.

Quantification of Uncertainties from Image Processing and Analysis in Laboratory-Scale DNAPL Release Studies Evaluated by Reflective Optical Imaging

Subsurface DNAPL (dense non-aqueous phase liquid) contamination from (un-) intentional spilling typically leads to severe environmental hazards. A large number of studies have demonstrated the relevance of DNAPL source zone geometry for the determination of contaminant plume propagation in groundwater. Optical imaging represents a promising non-invasive method for identifying DNAPL saturation without disturbing multiphase flow dynamics. However, workflow and image analysis methodologies have not been sufficiently developed or described for general application to related experimental efforts. For example, the choice of dye(s) used for phase colorization affects image processing and can bias final estimations of DNAPL saturations. In this study, we perform a series of DNAPL migration and entrapment studies in transparent tanks that are filled with three different types of porous media. Different dyes are used and raw images are acquired. Subsequently, these are used to evaluate a suite of image processing and analysis approaches, which are organized into a workflow. Our approach allows for us to identify key image processing and analysis steps that introduce the most error. Applicable dye configurations led to uncertainties of up to 41% depending on the selection of processing steps. Based on these findings, it was possible to delineate a flexible framework for image processing and analysis that has the potential for transfer and application in other tank experiment setups.

Coupled hydrogeophysical inversion of DNAPL source zone architecture and permeability field in a 3D heterogeneous sandbox by assimilation time-lapse cross-borehole electrical resistivity data via ensemble Kalman filtering

Characterization of dense non-aqueous phase liquid (DNAPL) distribution is important to facilitate the decision of remediation strategies. However, it is still a great challenge to characterize DNAPL source zone architecture with high resolution due to subsurface heterogeneity and relatively sparse data from traditional hydrogeological investigations. To overcome difficulties from such sparse data, electrical resistivity tomography (ERT) is introduced to locate DNAPL using time-lapse cross-borehole measurements. Due to the significant impact of geological heterogeneity on DNAPL source zone architecture, a data assimilation framework based on the coupled multiphase fluids-ERT model is developed to jointly invert DNAPL saturation and the permeability field using time-lapse ERT data. To validate the efficiency and performance of this framework, synthetic and laboratory experiments are both performed to monitor DNAPL migration and distribution in 3D heterogeneous sandbox with cross-borehole ERT. Result shows that time-lapse ERT and direct inversion can map the evolution of the DNAPL plume but loses details regarding the plume morphology due to the over-smoothing caused by geophysical inversion using an isotropic and homogeneous roughness-based regularization procedure. By contrast, the coupled inversion is successful to characterize both the permeability field and the evolution of the DNAPL plume with a higher resolution. This is because the coupled inversion is able to directly translate raw geophysical data into hydrologic meaningful information and therefore avoid artifacts caused by direct geophysical inversion.

Source strength functions from long-term monitoring data and spatially distributed mass discharge measurements

Source strength functions (SSF), defined as contaminant mass discharge or flux-averaged concentration from dense nonaqueous phase liquid (DNAPL) source zones as a function of time, provide a quantitative model of DNAPL source-zone behavior. Such information is useful for calibration of screening-level models to assist with site management decisions. We investigate the use of historic data collected during long-term monitoring (LTM) activities at a site in Rhode Island to predict the SSF based on temporal mass discharge measurements at a fixed location, as well as SSF estimation using mass discharge measurements at a fixed time from three spatially distributed control planes. Mass discharge based on LTM data decreased from ~300 g/day in 1996 to ~70 g/day in 2012 at a control plane downgradient of the suspected DNAPL source zone, and indicates an overall decline of ~80% in 16 years. These measurements were compared to current mass discharge measurements across three spatially distributed control planes. Results indicate that mass discharge increased in the downgradient direction, and was ~6 g/day, ~37 g/day, and ~400 g/day at near, intermediate, and far distances from the suspected source zone, respectively. This behavior was expected given the decreasing trend observed in the LTM data at a fixed location. These two data sets were compared using travel time as a means to plot the data sets on a common axis. The similarity between the two data sets gives greater confidence to the use of this combined data set for site-specific SSF estimation relative to either the sole use of LTM or spatially distributed data sets.