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Surfactant flooding makes a comeback: Results of a full-scale, field implementation to recover mobilized NAPL
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Surfactant flooding makes a comeback: Results of a full-scale, field implementation to recover mobilized NAPL ⁎
Pushpesh Sharmaa, Konstantinos Kostarelosa, , Søren Lenschowb, Anders Christensenb, Phillip C. de Blancc a
University of Houston, Houston, TX, USA NIRAS A/S, Alleroed, Denmark c GSI Environmental Inc., Houston, TX, USA b
A B S T R A C T
Non-aqueous phase liquid (NAPL) remediation techniques using surfactants, such as enhanced pump and treat (also known as Surfactant–Enhanced Aquifer Remediation, “SEAR”) and micellar flooding provide a faster and more efficient way to recover NAPL from the subsurface. Micellar flooding is a recovery technique that relies on the ability of surfactants to mobilize the NAPL phase by reducing the interfacial tension between the aqueous phase and the NAPL. The application of micellar flooding for NAPL recovery has been limited to laboratory studies and some pilot–scale field applications primarily due to concerns that the technology might lead to uncontrolled movement of NAPL. This paper presents results from a full-scale field application of the micellar flood process designed to mobilize and recover an LNAPL (Jet fuel) from a surficial sandy aquifer located at a tank facility in western Jutland, Denmark. Phase behavior and flow experiments were conducted with field samples to identify suitable surfactant formulations. A field–scale simulation model was developed that indicated that a line–drive pattern with hydraulic control wells would be optimal for NAPL recovery. In addition to monitoring during the field implementation, monitoring was conducted immediately after and for a period of > 1 year. The field implementation resulted in > 90% recovery (approximately 36,000 Kg of LNAPL) based on the mass balance using laser–induced fluorescence (LIF) and chemical soil analysis (total petroleum hydrocarbon or TPH and BTEX) data. Post–surfactant flood site monitoring consisted of sampling water from multi–levels and from recovery wells. Groundwater samples were analyzed for total petroleum hydrocarbon (TPH) and benzene, toluene, ethylbenzene and xylene (BTEX). The pre–treatment and post–treatment mass discharges were also monitored, which led to a relationship between mass discharge with the mass reduction in the source zone. Also, the mass discharge Γ–model commonly used for DNAPL modeling was successfully implemented for LNAPL remediation. Studies of field applications of surfactant remediation processes are not readily available; it is especially rare to present a study of micellar flooding implementation for fullscale remediation processes.
1. Introduction Non-aqueous phase liquids (NAPL) contamination of soil is a significant problem, which leads to contamination of groundwater bodies, adverse impact on ecosystems and posing risk to human health. NAPL is classified as Light (LNAPL) and Dense (DNAPL) based on their density with respect to water. Jet fuel is characterized as an LNAPL and is primarily a fuel source for aviation industry. Jet fuel contamination is very common in areas near airport fuel storage tanks due to leaks in pipelines or tanks. Surfactant–assisted remediation techniques have been discussed in detail in the literature Mulligan et al. (2001); Mao et al. (2015). Surfactant–assisted remediation can be classified based on the mechanism of recovery: Surfactant Enhanced Aquifer Remediation (SEAR) relies on increasing the solubilization of NAPL into the aqueous phase, acting as an enhancement to conventional pump–and–treat (P&T) methods, while micellar flooding relies on reducing the interfacial tension
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between the NAPL and aqueous phase in order to mobilize the NAPL. Micellar flooding has been studied in detail as a chemical enhanced oil recovery method in the petroleum engineering field at the pilot scale with limited full-scale applications for crude oil recovery.(Lake et al., 2014; Sheng, 2010; Hirasaki et al., 2011) SEAR methods have been well–researched and applied in many pilot & field scale remediation applications for NAPL recovery.(Dwarakanath et al., 1999; Childs et al., 2006; Gallego et al., 2011; Kostarelos et al., 2013; NAVFAC, 2002; Fountain et al., 1996; Khalladi et al., 2009; Paria, 2008; Ghosh et al., 2019; Babaei and Copty, 2019) While SEAR can reduce the time required to recover NAPL when compared to P&T methods, the mobilization approach (micellar flooding) could recover contaminants in a shorter time and with less surfactant injection compared to SEAR, significantly reducing the cost of remediation. The concern, however, is that the micellar flooding approach can lead to migration of contaminants into deeper formation especially if contaminants are a DNAPL, however there are examples in literature to eliminate the
Corresponding author. E-mail address: [email protected] (K. Kostarelos).
https://doi.org/10.1016/j.jconhyd.2020.103602 Received 9 July 2019; Received in revised form 27 December 2019; Accepted 13 January 2020 0169-7722/ © 2020 Elsevier B.V. All rights reserved.
Please cite this article as: Pushpesh Sharma, et al., Journal of Contaminant Hydrology, https://doi.org/10.1016/j.jconhyd.2020.103602
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LNAPL below the water table (indicated as GWL in Fig. 2b). No LNAPL mass was found above the water table, likely due to the effect of vaporization. 2. Field implementation - design Success of surfactant–based remediation processes for a field scenario requires extensive laboratory studies such as phase behavior studies and flow experiments. These laboratory studies provide key information for generating numerical simulations and preliminary modeling assessments, which is critical for scale–up to the field level. Findings of these tests and models are discussed briefly below. Phase Behavior Studies and 1-D Flow Experiments: Phase behavior studies were conducted to identify suitable surfactant formulations for Jet A fuel. The experiments are discussed in detail by Kostarelos et al. (Kostarelos et al., 2016) in a previous publication. The selected surfactant formulation was a 4 wt% (1:1) mixture of sodium dioctyl sulfosuccinate (OT-75), sodium di-hexyl sulfosuccinate (MA-80) and 4 wt % sec-butanol at 22,000 mg/L optimum salinity at the aquifer temperature (10 °C). The surfactants utilized for the formulation were provided by Cytec Industries, Inc. (now Cytec Solvay) and were formulated at concentrations above the critical micelle concentration (CMC). A ternary phase diagram was also developed for the selected surfactant formulation that is used as input data for the Simulation Studies (below). After selecting the surfactant formulation, two column experiments were conducted at the design salinity. Properties of sandpacks using sand collected from the aquifer were measured, then flooded with Jet A fuel and water to measure endpoint relative permeabilities. The surfactant flood of these sandpacks confirmed the compatibility of the selected surfactant formulation with the soil since: a) the pressure measured during the experiment remained low indicating that no viscous phases formed in-situ, and; b) the recovery of the residual LNAPL was over 90%. The surfactant flood was performed with a horizontal orientation to observe the “oil bank” formed during the experiment and it matched the calculated bank angle. Simulation Studies: The simulation model, UTCHEM, is a 3D, multi–component, multi–phase, compositional model of chemical flooding processes that has been used for contaminant transport and surfactant flooding simulations (Delshad et al., 1996, 2002). The model accounts for complex phase behavior, chemical and physical transformations, and heterogeneous porous media properties. The flow and mass-transport equations are solved for any number of user-specified chemical components (water, oil, surfactant, alcohols, polymer, chloride, calcium, other electrolytes, tracers, cross linkers, etc.). These components can form up to four fluid phases (air, water, oil, and microemulsion) and any number of solid minerals depending upon the overall composition. The phase behavior model is critical to obtaining a wide range of the commonly–observed micellar and microemulsion behavior relevant to surfactant flooding and SEAR. Surfactant–related properties such as adsorption, interfacial tension, capillary pressure, capillary number and microemulsion viscosity are all dependent on an accurate phase behavior model. The laboratory studies provided essential information that was used for modeling the field application scenarios. A multi–phase simulation model was developed in UTCHEM using laboratory measurements; the UTCHEM model phase behavior was then run and compared with (calibrated) the column experiment results prior to implementing the model for full-scale simulations. Parameters such as hydraulic conductivity, porosity, and LNAPL saturations were determined in the field by means of a tracer test, from cone penetrometer (CPT) laser–induced fluorescence (LIF) measurements, and from in–situ water pressure measurements. The simulation studies were then used to determine well spacing, screened intervals, injection/extraction rates, salt concentrations, and injection/extraction time periods for maximum LNAPL recovery. Based on the simulation studies, it was decided to employ a line drive pattern consisting of 15 injection wells and 15 extraction
Fig. 1. The location of the Jet fuel contamination on the site in western Jutland, Denmark. The remediation zone is circled in red. Notice the central area where the contamination intensity was highest. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
downward migration.(Kostarelos et al., 1998) Currently, to our knowledge, no studies of full–scale field application of micellar flooding for LNAPL remediation have been found in peer–reviewed journals; thus, this paper presents the first known full–scale field application of micellar flooding for LNAPL recovery from the subsurface. The steps taken to design the flood, such as lab studies and simulation work, are also summarized in this paper. The primary aim of the micellar flood was the recovery of LNAPL (Jet A fuel) from a surficial sandy aquifer located at a tank facility in western Jutland, Denmark. The spill was observed in 2003 from a leaking pipeline, near the northern end of the manifold building. The location of the leak and extent of the LNAPL area are shown in Fig. 1. The amount of LNAPL released was not recorded. Approximately 24 m3 of LNAPL was recovered using a process known as “skimming” of the groundwater table until the flow of LNAPL to skimmer wells was reduced to an insignificant rate. Attempts to recovery the remaining mobile LNAPL using water injection yielded no LNAPL, indicating LNAPL at residual saturation. However, in 2010, an oil film was observed in the wells located near the area. Subsequent studies were conducted to investigate the extent of LNAPL contamination. The LNAPL zone was delineated using laser induced fluorescence (LIF) measurements. In Fig. 2a, the location of the LIF measurements and the fluorescence intensity (signal %RE) measured is plotted with respect to the elevation and clearly indicates the presence of LNAPL below the groundwater level. Based on these measurements, the areal extent of the contamination was estimated to be approximately 1000 m2 (see Fig. 3). A central area of 65 m2 as depicted by dark red in the heat map (see Fig. 3), had the strongest indications of contamination. The subsurface extent of the contamination was in the smear zone from 3 to 4 m below ground level (bgl) and from top of the aquifer to a depth of 5.5 m bgl. Based on the studies and analyses, the amount of LNAPL remaining in the subsurface was estimated to be approximately 44 m3, most of which was present at residual saturation. Thus, the LNAPL was within a surficial aquifer so that two points should be made: the aquifer was used for agriculture prior to the accidental jet fuel release and was a significant motivation behind the work to recover the LNAPl, and; the water table fluctuated greatly that led to a ‘smear zone’ of trapped 2
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Fig. 2. a)The LIF measurement locations are shown (left); b) fluorescence intensity (%RE) is plotted against elevation, ground level is 22 m (right). Most of the LNAPL contamination is below the groundwater level (GWL).
Fig. 4. Well configuration and flow scheme for the first stage of the remediation. The direction of the flow was from north to south.
hydraulic conductivity (Kh) of approximately 8.6 m/d (10−2 cm/s). This value of Kh was used in a simulation of the tracer test in order to ascertain a more accurate value and determine the degree of aquifer heterogeneity. In the field, pumping was initiated and once steady draw-down achieved, a measured volume of sodium chloride solution was injected up-gradient while samples were collected down-gradient. The samples were analyzed for chloride and result used for numerical simulation. The tracer simulations suggested that the value of Kh was closer to 15 m/d, and that the aquifer appeared to be isotropic with respect to hydraulic conductivity. Therefore, a value of 15 m/d was used in the hydraulic design simulations for both horizontal and vertical (Kv) hydraulic conductivities. Other parameter values used in the simulations are listed in Table 1. Monitoring: During the remediation, monitoring of the site and flood performance was conducted during each stage to evaluate the performance of the process so that adjustments could be made if necessary. Water samples from monitoring and recovery wells were analyzed for electrical conductivity to understand the distribution of the injected brine in the aquifer. These samples were also titrated for chloride and surfactant concentration. Electrical conductivity data loggers were installed in the recovery wells to detect breakthrough and to adjust the
Fig. 3. The maximum fluorescence intensity overlain onto the site map. Notice the dark red spot in the center–left denoting the 65 m2-area with higher contamination. The black dots denote the well locations for field remediation. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
wells in two rows 5 m apart (Fig. 4). The modeling studies also indicated that hydraulic control wells (HCWs) injecting water up–gradient of the injection wells and recovering water downgradient of the extraction wells would keep the injected fluids at a shallow depth within the formation where the targeted LNAPL was located. The final simulation model consisted of a 100 × 80 horizontal grid with 29 layers of different hydraulic conductivity. The model was run on a PC with an Intel Core i7 processor and 16 GB of RAM. Details of the simulation studies are discussed by de Blanc et al. (2016) and some details are presented here for the reader. The field data, together with data from pumping and slug tests, were used to determine preliminary, conservative estimates of horizontal 3
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Table 1 Hydrogeological parameters used for the simulation studies.
Table 3 Volumes of surfactant, alcohol and brine injected in each stage.
Parameter
Value
Storage coefficient (confined aquifer) Specific yield (unconfined aquifer) Effective porosity Recharge rate (m/d) Longitudinal dispersivity (m) Horizontal transverse dispersivity (m) Vertical transverse dispersivity (m) Groundwater gradient (south)
0.00017 0.017 0.1 0 0.005 0.0005 0.00005 0.0125
Fig. 6. Location of transect for measuring mass discharge down-gradient from the site.
Table 2 Baseline mass discharge at the transect. Gradient (−)
TPH (Kg/ year)
Benzene (Kg/ year)
BTEX (Kg/ year)
JNov. 2014 JJan. 2015 JMar 2015 Jo, avg
0.8 1.1 1.1 1
0.98 1.42 1.27 1.22
0.05 0.05 0.05 0.05
0.12 0.17 0.12 0.14
Start
End
Volume surfactant (m3)
Volume SBA (m3)
Volume brine (m3)
1 2 3 4 5 6 7 8
08.12.2015 11.01.2016 04.04.2016 18.04.2016 09.05.2016 23.05.2016 09.06.2016 20.06.2016
22.12.2016 22.01.2016 12.04.2016 02.05.2016 18.05.2016 02.06.2016 16.06.2016 04.07.2016 Total:
5 7.1 6.2 5.4 6.7 6.1 5.9 5.3 47.7
3.8 3.4 4.1 4.6 4.4 3.1 4 3.1 30.5
40.8 45.8 46.4 39.1 36.2 22.9 22.8 21 275
subsurface soils, capable of probing to depths up to 30 m. The technology is useful for obtaining qualitative to semi-quantitative information about subsurface contamination by polycyclic aromatic hydrocarbons (PAHs). In the simplest terms, PAHs will fluoresce when excited by ultra-violet (UV) light. Contaminants containing PAHs are excited by a UV laser fluoresce with an intensity that is quantifiable and related to the amount of PAH. This approach is employed by using a sapphire crystal window mounted on the side of a direct push probe which are constrained to use in unconsolidated media to depths of 50 to 100 ft depending on soil strength. In this way, a light source and detector can be installed on one side of the sapphire window allowing for detection of PAHs on the other while the probe is pushed down through the subsurface and the data logged. PAH monitoring was important to measure the flood performance. There are two methods available for deployment of the LIF sensors: cone penetrometer and percussion direct–push rigs.(Germain, 2011) In this study the direct-push method was utilized. Fuels and oils contain various amount of monoaromatic hydrocarbons (MAHs), PAHs, and aliphatic hydrocarbons. Electrons in the aromatic molecules absorbs energy at a certain wavelength and emit fluorescence. This spectrum is unique to each molecule and make it possible to discern the molecule from the fluorescence spectrum. However, because NAPLs are usually mixtures that emit overlapping spectra, it can be difficult to identify individual compounds from LIF data. LIF is useful in determination of relative concentrations and type of product present in the subsurface.(Germain, 2011). Mass Discharge Model: The dissolution of NAPL into groundwater is a complicated process that is affected by subsurface properties, heterogeneity, NAPL properties, and NAPL distribution. Due to these complexities, remediation processes for NAPLs fail to completely remove all the contaminants from the ground. Therefore, relating partial mass removal to the reduction in contaminant mass flux reduction is of utmost importance to evaluate the performance of remediation effort. Contaminant mass flux (mass discharge) relationship to mass-removal processes have been discussed in detail in literature.(Fried et al., 1979) Mass removal and mass discharge relationship is significantly impacted by the NAPL distribution in subsurface and heterogeneity of the formation.(Zhu and Sykes, 2000; DiFilippo and Brusseau, 2008; DiFilippo et al., 2010; Brusseau et al., 2007; Brown et al., 2012) In heterogeneous aquifers, a general approach is to approximate source strength by a power function of the remaining mass of NAPL in the source zone,(Rao and Jawitz, 2003; Rao et al., 2001) as shown in the so–called “Γ–model” (Eq. (1))
Fig. 5. Well configuration and flow scheme for the last stage (stage 8) of remediation. The flow direction was reversed in this stage to contain the LNAPL.
Parameter
Stage
Γ
Jt M = ⎛ t⎞ Jo M ⎝ o⎠ ⎜
brine dosage. Laser–induced Fluorescence: A LIF high resolution probe using an Ultra Violet Optical Screening Tool (UVOST) was utilized to adjust and optimize various remediation stages. LIF is a real–time, in–situ field screening method for residual and NAPL contaminants within
⎟
(1)
where Jo is the initial mass discharge resulting from the initial mass Mo in place, and Jt is the mass discharge resulting from the mass Mt at time t, and Γ is an empirical factor that is dependent upon geology and properties of the NAPL contaminants.(Falta et al., 2005a) The value of Γ is strongly correlated to the heterogeneity of the field and DNAPL 4
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Table 4 Total LNAPL recovered during each treatment stage at the oil/water separator and during water treatment. Stage
O/W Separator 3
1 2 3 4 5 6 7 8 Total
3
After O/W separator (during water treatment)
Total
Recovered micro–emulsion (m )
Mobilized NAPL (m )
Mobilized NAPL (Kg)
Dissolved NAPL (Kg)
(Kg)
0 4 8.1 7.6 26 23 25 2.7 96.4
0 0.5 2.8 3 9.4 10.3 9.2 2.1 37.3
0 410 2296 2460 7708 8446 7544 1722 30,586
104 452 321 238 317 288 124 295 2139
104 862 2617 2698 8025 8734 7668 2017 32,725
Fig. 7. Mass of TPH recovered as a separate, mobile phase compared to mass of solubilized TPH recovered. Notice that mobilized NAPL contributes most to the total recovery.
Fig. 8. Cumulative mass removal and mass removal rate with respect of injection time during Stage 2 from the extraction wells. A brine pre-flush and a post-flush were conducted before and after the surfactant flush.
Fig. 9. Cumulative mass removal and mass removal rate with respect to injection time during Stage 2 from the hydraulic control wells. A brine pre-flush and a post-flush were conducted before and after the surfactant flush.
architecture (distribution of DNAPL within the subsurface). The Γ–factor often varies between 0.5 and 2.0 for DNAPL sites. For cases where Γ < 1, a significant mass reduction (Mt/Mo) does not result in a corresponding reduction in mass flux (Jt/Jo); conversely, observing a small reduction in mass flux (Jt/Jo) following a remediation effort should not be misinterpreted as an indication of failure. Likewise, for Γ > 1 cases, a large reduction in mass flux could be misconstrued as a large mass reduction. The point is that measuring the post–remediation
mass flux at a site is not meaningful unless the Γ–factor is known.(Falta et al., 2005b) If the Γ–factor is known, the degree of mass reduction can be estimated by means of the mass flux measurements Jt/Jo. Alkali Hydrolysis: Treatment of the produced fluids was essential for the re-use of the water. Separation of the produced fluids was also critical to determine the amount of LNAPL recovered. This was complicated by the presence of the surfactant in the produced fluids, which 5
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Fig. 10. Comparison of heat map before and after the remediation work. The stark difference in the intensity coveys the effectiveness of the remediation.
Fig. 5, the hydraulic control injection and extraction wells were interchanged for stage 8. This was done to ensure that NAPL would not move out of the contaminated body. In addition, earlier studies indicated that the presence of fine sediment in the southern part of the field, which could have prevented achieving sufficient pumping rates in the last stage. The injection was started with a 54 m3 pre–flush of brine solution, followed by a 185 m3 of surfactant formulation flush. The surfactant flush was chased with 305 m3 post-flush of brine to continue pushing the mobilized LNAPL to the extraction wells and to recover remaining microemulsion in the system. The volumes used were calculated to be approximately 0.5 pore volume (PV) pre–flush, 3 PV surfactant flood, and 3.5 PV post–surfactant flood (i.e., brine post-flush). Since the swept pore volume in the field varies depending upon flow rates and on the size of a particular stage, the volumes used are presented in the results section (Table 3). Pressure, flow rates, and amount of LNAPL recovered were recorded for each stage. Produced samples from the extraction wells were analyzed for chloride and surfactant concentration using titration. Electrical conductivity was measured to determine the breakthrough curves and estimate swept pore volume. Total recovery from a stage was calculated by measuring mobilized LNAPL produced (mobilized) and the amount of LNAPL separated from microemulsion using alkali hydrolysis. As a method of confirming results (i.e., for consistency and validation of the methods herein), the soil was analyzed with LIF after every stage, which also served to properly optimize the next remediation stage. After eight stages, total recovery was confirmed using additional LIF and chemical soil analysis. Soil analysis consisted of soil sample collection, preservation, and laboratory chemical analysis by a contract lab. Effectiveness of the remediation was also quantified based on the reduction of mass discharge hydrocarbons. The transect method was utilized to measure mass discharge before and after the remediation. The transect, placed down-gradient from the remediation body, was 45m wide and contained 6 wells with 35 total sampling points as depicted in Fig. 6. Samples acquired from these points were analyzed for TPH and BTEX. The groundwater gradient was estimated by hydraulic heads in the wells, and the hydraulic conductivity was estimated from slug tests and a Geo-probe Hydraulic Profiling Tool (HPT-logs). The mass discharge was estimated using the GSI Mass Flux Tool Kit. Baseline mass
created an emulsion and microemulsion that required > 1 week to separate. A treatment step was added to remove the surfactant. Alkaline hydrolysis is the reaction of esters with sodium hydroxide to create a carboxylate salt and alcohol. Alkaline hydrolysis of esters is also known as saponification.
R‐COOR + NaOH → RCOONa + ROH Ester Base Carboxylate Soap Alcohol The surfactants utilized in this field application are both sulfosuccinates; i.e., sodium salts of alkyl esters of sulfosuccinic acid. Sulfosuccinates are very sensitive to hydrolysis under both acidic and basic conditions due to the presence of the ester linkage.(Deepika and Tyagi, 2006) Under basic conditions, the (OH−) group acts as a nucleophile and attacks the ester group, which leads to formation of salt of sulfosuccinic acid and an alcohol. According to Batchu et al. the hydrolysis of di-octyl sulfosuccinate occurs under both acidic and basic conditions, but the hydrolysis is more effective in the presence of strong base.(Batchu et al., 2014) Testing in our laboratory confirmed that alkaline hydrolysis of the surfactant occurred and the time required for hydrolysis was also determined at the groundwater temperature at the site. Hence, in this field application, alkaline hydrolysis (NaOH) was utilized to degrade the surfactant in the produced microemulsion so that the jet fuel and water could be separated, after which the jet fuel was sold and the water treated for re–use. 3. Field implementation - execution Based on the dimensions of the site and the well spacing, field implementation was planned to be conducted in eight stages moving from up–gradient to down–gradient (north to south). Although the simulation studies recommended 15 injection per row and 15 extraction wells per row to create a line drive pattern, the last 5 rows (down gradient) of the site could only accommodate 13 wells. Fig. 4 shows the pattern and location of the wells for Stage 1. The progression of the field implementation would then proceed to the next row or stage after assessing the performance and instituting modifications if deemed necessary. The direction of the hydraulically–induced flow was from north to south, which was parallel to the overall groundwater flow direction. Thus, a similar pattern was followed for 7 stages, although for stage 8 the direction of flow was reversed (south to north). As shown in 6
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Fig. 11. Comparison of groundwater concentrations at transect before and after remediation of: a) TPH; b) benzene, and; c) BTEX compounds. The well locations and screened intervals, (highlighted in yellow, are shown on the first diagram. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 7
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In the field, produced water was treated by an on–site treatment plant which consisted of oil/water separators, a combined stripper–bioreactor, sand filters, and two granular activated carbon (GAC) filters. Initially, surfactant and oil were detected in the treated water, which was linked to the presence of surfactants in the produced water. To address this problem, alkaline hydrolysis was implemented as a pre-treatment stage before the on–site treatment plant. Laboratory studies tested alkaline hydrolysis of the surfactant formulation and demonstrated that the reaction time, reaction temperature, and pH of the solution were the controlling factors for the reaction. It was determined that the relatively low groundwater temperature required longer reaction times, so the produced groundwater was collected in large tanks for hydrolysis so that adequate reaction time could be maintained, which was more economical than heating the produced water. The pH was used as a control for hydrolysis and was always maintained higher than 12. On average, 526 Kg of the caustic solution (NaOH) was added to the 50,000 L capacity treatment tank. These treatment tanks were equipped with recirculation pumps to provide sufficient mixing of the solution. The mass removal of NAPL was calculated using the mass recovered in the solubilized microemulsion from the extraction wells and hydraulic control wells (and was separated in the hydrolysis tanks), and also from the NAPL mass which was directly mobilized and captured from the oil/water separator. The amount of NAPL recovered from each stage is tabulated in Table 4. The recovery from stage 5, 6, and 7 were highest, which was expected based on the fact that these stages were
Table 5 Mass discharge measured after the remediation process. Parameter
Gradient (%)
TPH (Kg/ year)
Benzene (Kg/ year)
BTEX (Kg/ year)
Jo, avg JJune 17 JSept 17 JDec 17 JFeb 18 J2017–2018, avg Reduction %
1 2 0.5 1.6 1.3 1.3 –
1.22 0.37 0.14 0.43 0.23 0.29 64–88
0.05 0.0006 0.00009 0.00023 0.00016 0.00027 98–99
0.14 0.003 0.0006 0.0015 0.00099 0.0015 97–99
discharge was calculated based on 3 sampling events done from November 2014 to March 2015. The baseline measurement for gradient, TPH, benzene and BTEX is tabulated in Table 2.
4. Results and discussion Total amount of surfactant, co-solvent (sec-butanol) and brine injected in each stage of the remediation process are listed in Table 3. Because the aquifer was much deeper than the treated NAPL layer, it is possible that some of the injected surfactant solution may have “underrun” below the NAPL layer before it contacted NAPL. Because of the difficulty in determining swept pore volume, all of the reported volumes are in cubic meters instead of pore volumes.
Fig. 12. Mass Discharge of TPH using a varying gradient (upper graph) and a steady gradient (lower graph). Both cases show significant mass flux reduction after remediation. 8
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5. Conclusion
located in the zones of highest LIF intensity. The mobilized NAPL contributed to the majority of the recovery (93% of the total NAPL recovered), highlighting the effectiveness of micellar flooding, and is depicted graphically in Fig. 7. Figs. 8 and 9 report the mass removal and mass removal rates for Stage 2 of the project, comparing the recovery from the extraction wells (Fig. 8) to the hydraulic control wells (Fig. 9). A total of 40 m3 (32,700 Kg) LNAPL was recovered during the remediation. The mass recovery rates are on the order of 25 and 45 g/h in the hydraulic control wells (Fig. 9) and showed little change as a result of the surfactant flush. The recovery rates at the extraction wells were at a similar level as the hydraulic control wells and increased to levels between 10,000 g/h and 37,000 g/h as a result of the surfactant flush. The fact that the mass of hydrocarbon arriving at the hydraulic control wells remained low when compared to the extraction wells—which increased 3 orders of magnitude—indicates good hydraulic control of the injected surfactant solution. Mass balance analyses were performed based on actual production data during remediation, and on pre– and post–remedial investigation data including LIF and chemical soil analysis. Both analyses showed that approximately 90% of the contamination was recovered from the source zone. The remaining amount of LNAPL on the site was estimated to be approximately 4 m3 (2700 Kg). The average LIF comparison of the pre-remediation and post–remediation “heat maps” based on LIF measurements demonstrates the effectiveness of the remediation process (Fig. 10). Additionally, the concentration of TPH, benzene and BTEX were measured at a downgradient transect after remediation (see Fig. 6 for location of six wells). Each of these six wells are actually clusters that have a screened interval at different depths identified on the transect in Fig. 11. The well locations and number of screened intervals are labelled as A (3 screens), B (5 screens), C (5 screens), D (5 screens), E (3 screens) and F (3 screens). In addition to these samples, we also sampled from wells locations slightly up and downgradient of the transect for comparison, but we did not use the data for estimation of the mass discharge. These data from six wells are compared to measurements made prior to remediation in Fig. 11. The contours shown in Fig. 11 were made using ordinary kriging method and measured concentrations of nearest neighbors. Flux measurements of hydrocarbons were also made in order to compute the mass flux after remediation and compare with the baseline measurements. Transect measurements document hydrocarbon concentration reductions up to 99%. The flux calculations were made using the GSI Mass Flux Toolkit (freeware: https://www.gsi-net.com/en/ software/free-software/mass-flux-toolkit.html). The reduction in mass flux is tabulated in Table 5 and show a significant reduction after remediation for the BTEX compounds of 97–99%. The TPH mass flux was also reduced significantly of over 64% based on the. conservative values in Table 5. Pre– and post–flush mass discharge measurements were utilized to correlate a Γ–factor based on the reduction in mass discharge, according to the Γ–model. Based on the TPH data and mass removal from the source zone, the Γ–factor is estimated to range from 0.41 to 0.85 depending on the indicator (TPH, benzene, or BTEX). The Γ–factor is in the range 0.51–0.69 if the groundwater gradient is considered steady at 1%. During post monitoring, the gradient varied from 0.5–2.0%, and was more unstable than during the baseline monitoring, when the gradient was stable around 1%. Therefore, the variation of the gradient has had greater influence on the mass discharge than the measured concentration levels. Thus, a steady gradient of 1% was used to estimate mass discharge, instead of using the varying gradient, in order to compare the mass discharge before and after remediation. The mass flux for both the varying and steady gradient conditions were computed and the results for TPH are compared in Fig. 12 to the baseline conditions which show reduction in mass flux of 93.2% for a varying gradient and 98.5% assuming a steady gradient.
It is important to note several points regarding this project. First, that the surfactant flood used to mobilize and recover the LNAPL was completed in a relatively short period of time: the entire field project took less than six months, including down-time used to make measurements and confirm the design. Second, the monitoring confirmed that the LNAPL movement was hydraulically controlled and captured. Post–surfactant flood analyses (aqueous sampling, LIF measurements, soil sampling) of the site indicate over 90% of LNAPL mass recovered. The reduction in mass flux from the site 1–year after treatment is over 98% with respect to BTEX compounds. With respect to total petroleum hydrocarbons, the mass flux reduction is 64% assuming a varying gradient or 88% if a steady gradient is assumed. The significance of the field work is important to consider in light of publications presenting laboratory work that cautioned against this approach for NAPL recovery. After a period of interest from the early 1990s to early 2000s, field implementation of surfactants declined. Although some publications presented the use of surfactants to increase solubility and recovery of NAPL by way of enhancing the conventional “pump–and–treat” approach, this paper presents the first known full–scale field application of micellar flooding to LNAPL recovery from the subsurface by means of mobilization. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References Babaei, M., Copty, N.K., 2019. Numerical modelling of the impact of surfactant partitioning on the surfactant-enhanced aquifer remediation. J. Contam. Hydrol. 221, 69–81. Batchu, S.R., Ramirez, C.E., Gardinali, P.R., 2014. Stability of dioctyl sulfosuccinate (DOSS) towards hydrolysis and photodegradation under simulated solar conditions. Science of Total Environment 481, 260–265. de Blanc, P.C., Lenschow, S.R., Christensen, A.G., Mygind, M.M., Lindof, A.M., Kostarelos, K., 2016. Multi-phase simulations for design of a surfactant – enhanced aquifer remediation. In: Battelle 2016 International Conference on Remediation of Chlorinated and Recalcitrant Compounds, May. California, USA. Brown, G.H., Brooks, M.C., Wood, A.L., Annable, M.D., Huang, J., 2012. Aquitard contaminant storage and flux resulting from dense nonaqueous phase liquid source zone dissolution and remediation. Water Resour. Res. 48. Brusseau, M.L., Nelson, N.T., Zhang, Z., Blue, J.E., Rohrer, J., Allen, T., 2007. Source-zone characterization of a chlorinated-solvent contaminated superfund site in Tucson, AZ. J. Contam. Hydrol. 90, 21–40. Childs, J., Acosta, E., Annable, M.D., Brooks, M.C., Enfield, C.G., Harwell, J.H., Hasegawa, M., Knox, R.C., Rao, S.P.S., Sabatini, D.A., Shiau, B., Szekeres, E., Wood, L.A., 2006. Field demonstration of surfactant-enhanced solubilization of DNAPL at Dover Air Force Base. J. Contam. Hydrol. 82, 1–22. Deepika, L., Tyagi, V.K., 2006. Sulfosuccinates as mild surfactants. Journal of Oleo Science 55 (9), 429–439. Delshad, M., Pope, G.A., Sepehrnoori, K., 1996. A compositional simulator for modeling surfactant enhanced aquifer remediation, 1 formulation. J. Contam. Hydrol. 23, 303–327. Delshad, M., Asakawa, K., Pope, G.A., Sepehrnoori, K., 2002. Simulations of chemical and microbial enhanced oil recovery methods. In: SPE/DOE Improved Oil Recovery Symposium, 13–17 April, Tulsa, Oklahoma, SPE-75237-MS. DiFilippo, E.L., Brusseau, M.L., 2008. Relationship between mass-flux reduction and source-zone mass removal: analysis of field data. J. Contam. Hydrol. 98, 22–35. DiFilippo, E.L., Carroll, K.C., Brusseau, M.L., 2010. Impact of organic-liquid distribution and flow-field heterogeneity on reductions in mass flux. J. Contam. Hydrol. 115, 14–25. Dwarakanath, V., Kostarelos, K., Pope, G.A., Shotts, D., Wade, W.H., 1999. Anionic surfactant remediation of soil columns contaminated by nonaqueous phase liquids. J. Contam. Hydrol. 38 (4), 465–488. Falta, R.W., Rao, P.S.C., Basu, N., 2005a. Assessing the impacts of partial mass depletion in DNAPL source zones I. Analytical modeling of source strength functions and plume response. J. Contam. Hydrol. 78, 259–280. Falta, R.W., Rao, S.P.C., Basu, N., 2005b. Assessing impacts of partial mass depletion in DNAPL source zones II. Coupling source strength functions to plume evolution. J. Contam. Hydrol. 79, 45–66. Fountain, J.C., Starr, R.C., Middleton, T., Beikirch, M., September 1996. A controlled field test of surfactant-enhanced aquifer remediation. Groundwater 34 (5), 910–916.
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recovery. Society of Petroleum Engineering. Mao, X., Jiang, R., Xiao, W., Yu, J., 2015. Use of surfactants for the remediation of contaminated soils: a review. J. Hazard. Mater. 285, 419–435. Mulligan, C.N., Yong, R.N., Gibbs, B.F., 2001. Surfactant-enchaced remediation of contaminated soil: a review. Eng. Geol. 60 (1–4), 371–380. NAVFAC, 2002. Naval facilities engineering and command. In: Surfactant-Enhanced Aquifer Remediation (SEAR) Design Manual NFESC Technical Report TR-2206-ENV. Naval Facilities Engineering Command, Duke Engineering and Services, Washington. Paria, S., 2008. Surfactant-enhanced remediation of organic contaminated soil and water. Adv. Colloid Interf. Sci. 138, 24–58. Rao, P.S.C., Jawitz, J.W., 2003. Comment on “Steady-state mass transfer from singlecomponent dense nonaqueous phase liquids in uniform flow fields” by T.C. Sale and D.B. McWhorter. Water Resour. Res. 39 (3) (COM 1). Rao, P.S.C., Jawitz, J.W., Enfield, C.G., Falta, R., Annabel, M.D., Wood, A.L., 2001. Technology Integration for Contaminated Site Remediation: Cleanup Goals and Performance Metrics. Groundwater Quality, Sheffield, UK, pp. 410–412. Sheng, J., 2010. Modern chemical enhanced oil recovery: theory and practice. In: Modern Chemical Enhanced Oil Recovery: Theory and Practice. Vol. 25 Gulf Professional Publishing. Zhu, J., Sykes, J.F., 2000. The influence of NAPL dissolution characteristics on field-scale contaminant transport in subsurface. J. Contam. Hydrol. 41, 133–154.
Fried, J.J., Muntzer, P., Zilliox, L., 1979. Ground-water pollution by transfer of oil hydrocarbons. Ground Water 17, 586–594. Gallego, J.L.R., Sierra, C., Permanyer, A., Peláez, A.I., Menéndez-Vega, D., Sánchez, J., 2011. Full-scale remediation of a jet fuel-contaminated soil:assessment of biodegradation, volatilization and bioavailability. Water Air Soil Pollut. 197–211. Germain, R.S., 2011. Laser-induced fluorescence primer. Applied NAPL Science Review 1. Ghosh, J., Geoffrey, R.T., Akyol, N.H., Zhang, Y., 2019. A pore-scale investigation of heavy crude oil trapping and removal during surfactant-enhanced remediation. J. Contam. Hydrol. 223, 103471. Hirasaki, G., Miller, C.A., Puerto, M., 2011. Recent advances in surfactant EOR. SPE J. 16 (4), 889–907. Khalladi, R., Benhabiles, O., Bentahar, F., Moulai-Mostefa, N., 2009. Surfactant remediation of diesel fuel polluted soil. J. Hazard. Mater. 164, 1179–1184. Kostarelos, K., Pope, G.A., Rouse, B.A., Shook, G.M., 1998. A new concept: the use of neutrally-buoyant microemulsions for DNAPL remediation. J. Contam. Hydrol. 34, 383–397. Kostarelos, K., Yoon, S., Lee, Y.K., 2013. Coal tar recovery using enhanced pump & treat. J. Chem. Technol. Biotechnol. 88 (12), 2252–2263. Kostarelos, K., Lenschow, S.R., Stylianou, M.A., de Blanc, P.C., Mygind, M.M., Christensen, A.G., 2016. Jet a fuel recovery using micellar flooding: design and implementation. Sci. Total Environ. 563–564, 890–898. Lake, W.L., Johns, R., Rossen, B., Pope, G.A., 2014. Fundamentals of enhanced oil
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Journal of Contaminant Hydrology journal homepage: www.elsevier.com/locate/jconhyd
Surfactant flooding makes a comeback: Results of a full-scale, field implementation to recover mobilized NAPL ⁎
Pushpesh Sharmaa, Konstantinos Kostarelosa, , Søren Lenschowb, Anders Christensenb, Phillip C. de Blancc a
University of Houston, Houston, TX, USA NIRAS A/S, Alleroed, Denmark c GSI Environmental Inc., Houston, TX, USA b
A B S T R A C T
Non-aqueous phase liquid (NAPL) remediation techniques using surfactants, such as enhanced pump and treat (also known as Surfactant–Enhanced Aquifer Remediation, “SEAR”) and micellar flooding provide a faster and more efficient way to recover NAPL from the subsurface. Micellar flooding is a recovery technique that relies on the ability of surfactants to mobilize the NAPL phase by reducing the interfacial tension between the aqueous phase and the NAPL. The application of micellar flooding for NAPL recovery has been limited to laboratory studies and some pilot–scale field applications primarily due to concerns that the technology might lead to uncontrolled movement of NAPL. This paper presents results from a full-scale field application of the micellar flood process designed to mobilize and recover an LNAPL (Jet fuel) from a surficial sandy aquifer located at a tank facility in western Jutland, Denmark. Phase behavior and flow experiments were conducted with field samples to identify suitable surfactant formulations. A field–scale simulation model was developed that indicated that a line–drive pattern with hydraulic control wells would be optimal for NAPL recovery. In addition to monitoring during the field implementation, monitoring was conducted immediately after and for a period of > 1 year. The field implementation resulted in > 90% recovery (approximately 36,000 Kg of LNAPL) based on the mass balance using laser–induced fluorescence (LIF) and chemical soil analysis (total petroleum hydrocarbon or TPH and BTEX) data. Post–surfactant flood site monitoring consisted of sampling water from multi–levels and from recovery wells. Groundwater samples were analyzed for total petroleum hydrocarbon (TPH) and benzene, toluene, ethylbenzene and xylene (BTEX). The pre–treatment and post–treatment mass discharges were also monitored, which led to a relationship between mass discharge with the mass reduction in the source zone. Also, the mass discharge Γ–model commonly used for DNAPL modeling was successfully implemented for LNAPL remediation. Studies of field applications of surfactant remediation processes are not readily available; it is especially rare to present a study of micellar flooding implementation for fullscale remediation processes.
1. Introduction Non-aqueous phase liquids (NAPL) contamination of soil is a significant problem, which leads to contamination of groundwater bodies, adverse impact on ecosystems and posing risk to human health. NAPL is classified as Light (LNAPL) and Dense (DNAPL) based on their density with respect to water. Jet fuel is characterized as an LNAPL and is primarily a fuel source for aviation industry. Jet fuel contamination is very common in areas near airport fuel storage tanks due to leaks in pipelines or tanks. Surfactant–assisted remediation techniques have been discussed in detail in the literature Mulligan et al. (2001); Mao et al. (2015). Surfactant–assisted remediation can be classified based on the mechanism of recovery: Surfactant Enhanced Aquifer Remediation (SEAR) relies on increasing the solubilization of NAPL into the aqueous phase, acting as an enhancement to conventional pump–and–treat (P&T) methods, while micellar flooding relies on reducing the interfacial tension
⁎
between the NAPL and aqueous phase in order to mobilize the NAPL. Micellar flooding has been studied in detail as a chemical enhanced oil recovery method in the petroleum engineering field at the pilot scale with limited full-scale applications for crude oil recovery.(Lake et al., 2014; Sheng, 2010; Hirasaki et al., 2011) SEAR methods have been well–researched and applied in many pilot & field scale remediation applications for NAPL recovery.(Dwarakanath et al., 1999; Childs et al., 2006; Gallego et al., 2011; Kostarelos et al., 2013; NAVFAC, 2002; Fountain et al., 1996; Khalladi et al., 2009; Paria, 2008; Ghosh et al., 2019; Babaei and Copty, 2019) While SEAR can reduce the time required to recover NAPL when compared to P&T methods, the mobilization approach (micellar flooding) could recover contaminants in a shorter time and with less surfactant injection compared to SEAR, significantly reducing the cost of remediation. The concern, however, is that the micellar flooding approach can lead to migration of contaminants into deeper formation especially if contaminants are a DNAPL, however there are examples in literature to eliminate the
Corresponding author. E-mail address: [email protected] (K. Kostarelos).
https://doi.org/10.1016/j.jconhyd.2020.103602 Received 9 July 2019; Received in revised form 27 December 2019; Accepted 13 January 2020 0169-7722/ © 2020 Elsevier B.V. All rights reserved.
Please cite this article as: Pushpesh Sharma, et al., Journal of Contaminant Hydrology, https://doi.org/10.1016/j.jconhyd.2020.103602
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LNAPL below the water table (indicated as GWL in Fig. 2b). No LNAPL mass was found above the water table, likely due to the effect of vaporization. 2. Field implementation - design Success of surfactant–based remediation processes for a field scenario requires extensive laboratory studies such as phase behavior studies and flow experiments. These laboratory studies provide key information for generating numerical simulations and preliminary modeling assessments, which is critical for scale–up to the field level. Findings of these tests and models are discussed briefly below. Phase Behavior Studies and 1-D Flow Experiments: Phase behavior studies were conducted to identify suitable surfactant formulations for Jet A fuel. The experiments are discussed in detail by Kostarelos et al. (Kostarelos et al., 2016) in a previous publication. The selected surfactant formulation was a 4 wt% (1:1) mixture of sodium dioctyl sulfosuccinate (OT-75), sodium di-hexyl sulfosuccinate (MA-80) and 4 wt % sec-butanol at 22,000 mg/L optimum salinity at the aquifer temperature (10 °C). The surfactants utilized for the formulation were provided by Cytec Industries, Inc. (now Cytec Solvay) and were formulated at concentrations above the critical micelle concentration (CMC). A ternary phase diagram was also developed for the selected surfactant formulation that is used as input data for the Simulation Studies (below). After selecting the surfactant formulation, two column experiments were conducted at the design salinity. Properties of sandpacks using sand collected from the aquifer were measured, then flooded with Jet A fuel and water to measure endpoint relative permeabilities. The surfactant flood of these sandpacks confirmed the compatibility of the selected surfactant formulation with the soil since: a) the pressure measured during the experiment remained low indicating that no viscous phases formed in-situ, and; b) the recovery of the residual LNAPL was over 90%. The surfactant flood was performed with a horizontal orientation to observe the “oil bank” formed during the experiment and it matched the calculated bank angle. Simulation Studies: The simulation model, UTCHEM, is a 3D, multi–component, multi–phase, compositional model of chemical flooding processes that has been used for contaminant transport and surfactant flooding simulations (Delshad et al., 1996, 2002). The model accounts for complex phase behavior, chemical and physical transformations, and heterogeneous porous media properties. The flow and mass-transport equations are solved for any number of user-specified chemical components (water, oil, surfactant, alcohols, polymer, chloride, calcium, other electrolytes, tracers, cross linkers, etc.). These components can form up to four fluid phases (air, water, oil, and microemulsion) and any number of solid minerals depending upon the overall composition. The phase behavior model is critical to obtaining a wide range of the commonly–observed micellar and microemulsion behavior relevant to surfactant flooding and SEAR. Surfactant–related properties such as adsorption, interfacial tension, capillary pressure, capillary number and microemulsion viscosity are all dependent on an accurate phase behavior model. The laboratory studies provided essential information that was used for modeling the field application scenarios. A multi–phase simulation model was developed in UTCHEM using laboratory measurements; the UTCHEM model phase behavior was then run and compared with (calibrated) the column experiment results prior to implementing the model for full-scale simulations. Parameters such as hydraulic conductivity, porosity, and LNAPL saturations were determined in the field by means of a tracer test, from cone penetrometer (CPT) laser–induced fluorescence (LIF) measurements, and from in–situ water pressure measurements. The simulation studies were then used to determine well spacing, screened intervals, injection/extraction rates, salt concentrations, and injection/extraction time periods for maximum LNAPL recovery. Based on the simulation studies, it was decided to employ a line drive pattern consisting of 15 injection wells and 15 extraction
Fig. 1. The location of the Jet fuel contamination on the site in western Jutland, Denmark. The remediation zone is circled in red. Notice the central area where the contamination intensity was highest. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
downward migration.(Kostarelos et al., 1998) Currently, to our knowledge, no studies of full–scale field application of micellar flooding for LNAPL remediation have been found in peer–reviewed journals; thus, this paper presents the first known full–scale field application of micellar flooding for LNAPL recovery from the subsurface. The steps taken to design the flood, such as lab studies and simulation work, are also summarized in this paper. The primary aim of the micellar flood was the recovery of LNAPL (Jet A fuel) from a surficial sandy aquifer located at a tank facility in western Jutland, Denmark. The spill was observed in 2003 from a leaking pipeline, near the northern end of the manifold building. The location of the leak and extent of the LNAPL area are shown in Fig. 1. The amount of LNAPL released was not recorded. Approximately 24 m3 of LNAPL was recovered using a process known as “skimming” of the groundwater table until the flow of LNAPL to skimmer wells was reduced to an insignificant rate. Attempts to recovery the remaining mobile LNAPL using water injection yielded no LNAPL, indicating LNAPL at residual saturation. However, in 2010, an oil film was observed in the wells located near the area. Subsequent studies were conducted to investigate the extent of LNAPL contamination. The LNAPL zone was delineated using laser induced fluorescence (LIF) measurements. In Fig. 2a, the location of the LIF measurements and the fluorescence intensity (signal %RE) measured is plotted with respect to the elevation and clearly indicates the presence of LNAPL below the groundwater level. Based on these measurements, the areal extent of the contamination was estimated to be approximately 1000 m2 (see Fig. 3). A central area of 65 m2 as depicted by dark red in the heat map (see Fig. 3), had the strongest indications of contamination. The subsurface extent of the contamination was in the smear zone from 3 to 4 m below ground level (bgl) and from top of the aquifer to a depth of 5.5 m bgl. Based on the studies and analyses, the amount of LNAPL remaining in the subsurface was estimated to be approximately 44 m3, most of which was present at residual saturation. Thus, the LNAPL was within a surficial aquifer so that two points should be made: the aquifer was used for agriculture prior to the accidental jet fuel release and was a significant motivation behind the work to recover the LNAPl, and; the water table fluctuated greatly that led to a ‘smear zone’ of trapped 2
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Fig. 2. a)The LIF measurement locations are shown (left); b) fluorescence intensity (%RE) is plotted against elevation, ground level is 22 m (right). Most of the LNAPL contamination is below the groundwater level (GWL).
Fig. 4. Well configuration and flow scheme for the first stage of the remediation. The direction of the flow was from north to south.
hydraulic conductivity (Kh) of approximately 8.6 m/d (10−2 cm/s). This value of Kh was used in a simulation of the tracer test in order to ascertain a more accurate value and determine the degree of aquifer heterogeneity. In the field, pumping was initiated and once steady draw-down achieved, a measured volume of sodium chloride solution was injected up-gradient while samples were collected down-gradient. The samples were analyzed for chloride and result used for numerical simulation. The tracer simulations suggested that the value of Kh was closer to 15 m/d, and that the aquifer appeared to be isotropic with respect to hydraulic conductivity. Therefore, a value of 15 m/d was used in the hydraulic design simulations for both horizontal and vertical (Kv) hydraulic conductivities. Other parameter values used in the simulations are listed in Table 1. Monitoring: During the remediation, monitoring of the site and flood performance was conducted during each stage to evaluate the performance of the process so that adjustments could be made if necessary. Water samples from monitoring and recovery wells were analyzed for electrical conductivity to understand the distribution of the injected brine in the aquifer. These samples were also titrated for chloride and surfactant concentration. Electrical conductivity data loggers were installed in the recovery wells to detect breakthrough and to adjust the
Fig. 3. The maximum fluorescence intensity overlain onto the site map. Notice the dark red spot in the center–left denoting the 65 m2-area with higher contamination. The black dots denote the well locations for field remediation. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
wells in two rows 5 m apart (Fig. 4). The modeling studies also indicated that hydraulic control wells (HCWs) injecting water up–gradient of the injection wells and recovering water downgradient of the extraction wells would keep the injected fluids at a shallow depth within the formation where the targeted LNAPL was located. The final simulation model consisted of a 100 × 80 horizontal grid with 29 layers of different hydraulic conductivity. The model was run on a PC with an Intel Core i7 processor and 16 GB of RAM. Details of the simulation studies are discussed by de Blanc et al. (2016) and some details are presented here for the reader. The field data, together with data from pumping and slug tests, were used to determine preliminary, conservative estimates of horizontal 3
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Table 1 Hydrogeological parameters used for the simulation studies.
Table 3 Volumes of surfactant, alcohol and brine injected in each stage.
Parameter
Value
Storage coefficient (confined aquifer) Specific yield (unconfined aquifer) Effective porosity Recharge rate (m/d) Longitudinal dispersivity (m) Horizontal transverse dispersivity (m) Vertical transverse dispersivity (m) Groundwater gradient (south)
0.00017 0.017 0.1 0 0.005 0.0005 0.00005 0.0125
Fig. 6. Location of transect for measuring mass discharge down-gradient from the site.
Table 2 Baseline mass discharge at the transect. Gradient (−)
TPH (Kg/ year)
Benzene (Kg/ year)
BTEX (Kg/ year)
JNov. 2014 JJan. 2015 JMar 2015 Jo, avg
0.8 1.1 1.1 1
0.98 1.42 1.27 1.22
0.05 0.05 0.05 0.05
0.12 0.17 0.12 0.14
Start
End
Volume surfactant (m3)
Volume SBA (m3)
Volume brine (m3)
1 2 3 4 5 6 7 8
08.12.2015 11.01.2016 04.04.2016 18.04.2016 09.05.2016 23.05.2016 09.06.2016 20.06.2016
22.12.2016 22.01.2016 12.04.2016 02.05.2016 18.05.2016 02.06.2016 16.06.2016 04.07.2016 Total:
5 7.1 6.2 5.4 6.7 6.1 5.9 5.3 47.7
3.8 3.4 4.1 4.6 4.4 3.1 4 3.1 30.5
40.8 45.8 46.4 39.1 36.2 22.9 22.8 21 275
subsurface soils, capable of probing to depths up to 30 m. The technology is useful for obtaining qualitative to semi-quantitative information about subsurface contamination by polycyclic aromatic hydrocarbons (PAHs). In the simplest terms, PAHs will fluoresce when excited by ultra-violet (UV) light. Contaminants containing PAHs are excited by a UV laser fluoresce with an intensity that is quantifiable and related to the amount of PAH. This approach is employed by using a sapphire crystal window mounted on the side of a direct push probe which are constrained to use in unconsolidated media to depths of 50 to 100 ft depending on soil strength. In this way, a light source and detector can be installed on one side of the sapphire window allowing for detection of PAHs on the other while the probe is pushed down through the subsurface and the data logged. PAH monitoring was important to measure the flood performance. There are two methods available for deployment of the LIF sensors: cone penetrometer and percussion direct–push rigs.(Germain, 2011) In this study the direct-push method was utilized. Fuels and oils contain various amount of monoaromatic hydrocarbons (MAHs), PAHs, and aliphatic hydrocarbons. Electrons in the aromatic molecules absorbs energy at a certain wavelength and emit fluorescence. This spectrum is unique to each molecule and make it possible to discern the molecule from the fluorescence spectrum. However, because NAPLs are usually mixtures that emit overlapping spectra, it can be difficult to identify individual compounds from LIF data. LIF is useful in determination of relative concentrations and type of product present in the subsurface.(Germain, 2011). Mass Discharge Model: The dissolution of NAPL into groundwater is a complicated process that is affected by subsurface properties, heterogeneity, NAPL properties, and NAPL distribution. Due to these complexities, remediation processes for NAPLs fail to completely remove all the contaminants from the ground. Therefore, relating partial mass removal to the reduction in contaminant mass flux reduction is of utmost importance to evaluate the performance of remediation effort. Contaminant mass flux (mass discharge) relationship to mass-removal processes have been discussed in detail in literature.(Fried et al., 1979) Mass removal and mass discharge relationship is significantly impacted by the NAPL distribution in subsurface and heterogeneity of the formation.(Zhu and Sykes, 2000; DiFilippo and Brusseau, 2008; DiFilippo et al., 2010; Brusseau et al., 2007; Brown et al., 2012) In heterogeneous aquifers, a general approach is to approximate source strength by a power function of the remaining mass of NAPL in the source zone,(Rao and Jawitz, 2003; Rao et al., 2001) as shown in the so–called “Γ–model” (Eq. (1))
Fig. 5. Well configuration and flow scheme for the last stage (stage 8) of remediation. The flow direction was reversed in this stage to contain the LNAPL.
Parameter
Stage
Γ
Jt M = ⎛ t⎞ Jo M ⎝ o⎠ ⎜
brine dosage. Laser–induced Fluorescence: A LIF high resolution probe using an Ultra Violet Optical Screening Tool (UVOST) was utilized to adjust and optimize various remediation stages. LIF is a real–time, in–situ field screening method for residual and NAPL contaminants within
⎟
(1)
where Jo is the initial mass discharge resulting from the initial mass Mo in place, and Jt is the mass discharge resulting from the mass Mt at time t, and Γ is an empirical factor that is dependent upon geology and properties of the NAPL contaminants.(Falta et al., 2005a) The value of Γ is strongly correlated to the heterogeneity of the field and DNAPL 4
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Table 4 Total LNAPL recovered during each treatment stage at the oil/water separator and during water treatment. Stage
O/W Separator 3
1 2 3 4 5 6 7 8 Total
3
After O/W separator (during water treatment)
Total
Recovered micro–emulsion (m )
Mobilized NAPL (m )
Mobilized NAPL (Kg)
Dissolved NAPL (Kg)
(Kg)
0 4 8.1 7.6 26 23 25 2.7 96.4
0 0.5 2.8 3 9.4 10.3 9.2 2.1 37.3
0 410 2296 2460 7708 8446 7544 1722 30,586
104 452 321 238 317 288 124 295 2139
104 862 2617 2698 8025 8734 7668 2017 32,725
Fig. 7. Mass of TPH recovered as a separate, mobile phase compared to mass of solubilized TPH recovered. Notice that mobilized NAPL contributes most to the total recovery.
Fig. 8. Cumulative mass removal and mass removal rate with respect of injection time during Stage 2 from the extraction wells. A brine pre-flush and a post-flush were conducted before and after the surfactant flush.
Fig. 9. Cumulative mass removal and mass removal rate with respect to injection time during Stage 2 from the hydraulic control wells. A brine pre-flush and a post-flush were conducted before and after the surfactant flush.
architecture (distribution of DNAPL within the subsurface). The Γ–factor often varies between 0.5 and 2.0 for DNAPL sites. For cases where Γ < 1, a significant mass reduction (Mt/Mo) does not result in a corresponding reduction in mass flux (Jt/Jo); conversely, observing a small reduction in mass flux (Jt/Jo) following a remediation effort should not be misinterpreted as an indication of failure. Likewise, for Γ > 1 cases, a large reduction in mass flux could be misconstrued as a large mass reduction. The point is that measuring the post–remediation
mass flux at a site is not meaningful unless the Γ–factor is known.(Falta et al., 2005b) If the Γ–factor is known, the degree of mass reduction can be estimated by means of the mass flux measurements Jt/Jo. Alkali Hydrolysis: Treatment of the produced fluids was essential for the re-use of the water. Separation of the produced fluids was also critical to determine the amount of LNAPL recovered. This was complicated by the presence of the surfactant in the produced fluids, which 5
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Fig. 10. Comparison of heat map before and after the remediation work. The stark difference in the intensity coveys the effectiveness of the remediation.
Fig. 5, the hydraulic control injection and extraction wells were interchanged for stage 8. This was done to ensure that NAPL would not move out of the contaminated body. In addition, earlier studies indicated that the presence of fine sediment in the southern part of the field, which could have prevented achieving sufficient pumping rates in the last stage. The injection was started with a 54 m3 pre–flush of brine solution, followed by a 185 m3 of surfactant formulation flush. The surfactant flush was chased with 305 m3 post-flush of brine to continue pushing the mobilized LNAPL to the extraction wells and to recover remaining microemulsion in the system. The volumes used were calculated to be approximately 0.5 pore volume (PV) pre–flush, 3 PV surfactant flood, and 3.5 PV post–surfactant flood (i.e., brine post-flush). Since the swept pore volume in the field varies depending upon flow rates and on the size of a particular stage, the volumes used are presented in the results section (Table 3). Pressure, flow rates, and amount of LNAPL recovered were recorded for each stage. Produced samples from the extraction wells were analyzed for chloride and surfactant concentration using titration. Electrical conductivity was measured to determine the breakthrough curves and estimate swept pore volume. Total recovery from a stage was calculated by measuring mobilized LNAPL produced (mobilized) and the amount of LNAPL separated from microemulsion using alkali hydrolysis. As a method of confirming results (i.e., for consistency and validation of the methods herein), the soil was analyzed with LIF after every stage, which also served to properly optimize the next remediation stage. After eight stages, total recovery was confirmed using additional LIF and chemical soil analysis. Soil analysis consisted of soil sample collection, preservation, and laboratory chemical analysis by a contract lab. Effectiveness of the remediation was also quantified based on the reduction of mass discharge hydrocarbons. The transect method was utilized to measure mass discharge before and after the remediation. The transect, placed down-gradient from the remediation body, was 45m wide and contained 6 wells with 35 total sampling points as depicted in Fig. 6. Samples acquired from these points were analyzed for TPH and BTEX. The groundwater gradient was estimated by hydraulic heads in the wells, and the hydraulic conductivity was estimated from slug tests and a Geo-probe Hydraulic Profiling Tool (HPT-logs). The mass discharge was estimated using the GSI Mass Flux Tool Kit. Baseline mass
created an emulsion and microemulsion that required > 1 week to separate. A treatment step was added to remove the surfactant. Alkaline hydrolysis is the reaction of esters with sodium hydroxide to create a carboxylate salt and alcohol. Alkaline hydrolysis of esters is also known as saponification.
R‐COOR + NaOH → RCOONa + ROH Ester Base Carboxylate Soap Alcohol The surfactants utilized in this field application are both sulfosuccinates; i.e., sodium salts of alkyl esters of sulfosuccinic acid. Sulfosuccinates are very sensitive to hydrolysis under both acidic and basic conditions due to the presence of the ester linkage.(Deepika and Tyagi, 2006) Under basic conditions, the (OH−) group acts as a nucleophile and attacks the ester group, which leads to formation of salt of sulfosuccinic acid and an alcohol. According to Batchu et al. the hydrolysis of di-octyl sulfosuccinate occurs under both acidic and basic conditions, but the hydrolysis is more effective in the presence of strong base.(Batchu et al., 2014) Testing in our laboratory confirmed that alkaline hydrolysis of the surfactant occurred and the time required for hydrolysis was also determined at the groundwater temperature at the site. Hence, in this field application, alkaline hydrolysis (NaOH) was utilized to degrade the surfactant in the produced microemulsion so that the jet fuel and water could be separated, after which the jet fuel was sold and the water treated for re–use. 3. Field implementation - execution Based on the dimensions of the site and the well spacing, field implementation was planned to be conducted in eight stages moving from up–gradient to down–gradient (north to south). Although the simulation studies recommended 15 injection per row and 15 extraction wells per row to create a line drive pattern, the last 5 rows (down gradient) of the site could only accommodate 13 wells. Fig. 4 shows the pattern and location of the wells for Stage 1. The progression of the field implementation would then proceed to the next row or stage after assessing the performance and instituting modifications if deemed necessary. The direction of the hydraulically–induced flow was from north to south, which was parallel to the overall groundwater flow direction. Thus, a similar pattern was followed for 7 stages, although for stage 8 the direction of flow was reversed (south to north). As shown in 6
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Fig. 11. Comparison of groundwater concentrations at transect before and after remediation of: a) TPH; b) benzene, and; c) BTEX compounds. The well locations and screened intervals, (highlighted in yellow, are shown on the first diagram. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 7
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In the field, produced water was treated by an on–site treatment plant which consisted of oil/water separators, a combined stripper–bioreactor, sand filters, and two granular activated carbon (GAC) filters. Initially, surfactant and oil were detected in the treated water, which was linked to the presence of surfactants in the produced water. To address this problem, alkaline hydrolysis was implemented as a pre-treatment stage before the on–site treatment plant. Laboratory studies tested alkaline hydrolysis of the surfactant formulation and demonstrated that the reaction time, reaction temperature, and pH of the solution were the controlling factors for the reaction. It was determined that the relatively low groundwater temperature required longer reaction times, so the produced groundwater was collected in large tanks for hydrolysis so that adequate reaction time could be maintained, which was more economical than heating the produced water. The pH was used as a control for hydrolysis and was always maintained higher than 12. On average, 526 Kg of the caustic solution (NaOH) was added to the 50,000 L capacity treatment tank. These treatment tanks were equipped with recirculation pumps to provide sufficient mixing of the solution. The mass removal of NAPL was calculated using the mass recovered in the solubilized microemulsion from the extraction wells and hydraulic control wells (and was separated in the hydrolysis tanks), and also from the NAPL mass which was directly mobilized and captured from the oil/water separator. The amount of NAPL recovered from each stage is tabulated in Table 4. The recovery from stage 5, 6, and 7 were highest, which was expected based on the fact that these stages were
Table 5 Mass discharge measured after the remediation process. Parameter
Gradient (%)
TPH (Kg/ year)
Benzene (Kg/ year)
BTEX (Kg/ year)
Jo, avg JJune 17 JSept 17 JDec 17 JFeb 18 J2017–2018, avg Reduction %
1 2 0.5 1.6 1.3 1.3 –
1.22 0.37 0.14 0.43 0.23 0.29 64–88
0.05 0.0006 0.00009 0.00023 0.00016 0.00027 98–99
0.14 0.003 0.0006 0.0015 0.00099 0.0015 97–99
discharge was calculated based on 3 sampling events done from November 2014 to March 2015. The baseline measurement for gradient, TPH, benzene and BTEX is tabulated in Table 2.
4. Results and discussion Total amount of surfactant, co-solvent (sec-butanol) and brine injected in each stage of the remediation process are listed in Table 3. Because the aquifer was much deeper than the treated NAPL layer, it is possible that some of the injected surfactant solution may have “underrun” below the NAPL layer before it contacted NAPL. Because of the difficulty in determining swept pore volume, all of the reported volumes are in cubic meters instead of pore volumes.
Fig. 12. Mass Discharge of TPH using a varying gradient (upper graph) and a steady gradient (lower graph). Both cases show significant mass flux reduction after remediation. 8
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5. Conclusion
located in the zones of highest LIF intensity. The mobilized NAPL contributed to the majority of the recovery (93% of the total NAPL recovered), highlighting the effectiveness of micellar flooding, and is depicted graphically in Fig. 7. Figs. 8 and 9 report the mass removal and mass removal rates for Stage 2 of the project, comparing the recovery from the extraction wells (Fig. 8) to the hydraulic control wells (Fig. 9). A total of 40 m3 (32,700 Kg) LNAPL was recovered during the remediation. The mass recovery rates are on the order of 25 and 45 g/h in the hydraulic control wells (Fig. 9) and showed little change as a result of the surfactant flush. The recovery rates at the extraction wells were at a similar level as the hydraulic control wells and increased to levels between 10,000 g/h and 37,000 g/h as a result of the surfactant flush. The fact that the mass of hydrocarbon arriving at the hydraulic control wells remained low when compared to the extraction wells—which increased 3 orders of magnitude—indicates good hydraulic control of the injected surfactant solution. Mass balance analyses were performed based on actual production data during remediation, and on pre– and post–remedial investigation data including LIF and chemical soil analysis. Both analyses showed that approximately 90% of the contamination was recovered from the source zone. The remaining amount of LNAPL on the site was estimated to be approximately 4 m3 (2700 Kg). The average LIF comparison of the pre-remediation and post–remediation “heat maps” based on LIF measurements demonstrates the effectiveness of the remediation process (Fig. 10). Additionally, the concentration of TPH, benzene and BTEX were measured at a downgradient transect after remediation (see Fig. 6 for location of six wells). Each of these six wells are actually clusters that have a screened interval at different depths identified on the transect in Fig. 11. The well locations and number of screened intervals are labelled as A (3 screens), B (5 screens), C (5 screens), D (5 screens), E (3 screens) and F (3 screens). In addition to these samples, we also sampled from wells locations slightly up and downgradient of the transect for comparison, but we did not use the data for estimation of the mass discharge. These data from six wells are compared to measurements made prior to remediation in Fig. 11. The contours shown in Fig. 11 were made using ordinary kriging method and measured concentrations of nearest neighbors. Flux measurements of hydrocarbons were also made in order to compute the mass flux after remediation and compare with the baseline measurements. Transect measurements document hydrocarbon concentration reductions up to 99%. The flux calculations were made using the GSI Mass Flux Toolkit (freeware: https://www.gsi-net.com/en/ software/free-software/mass-flux-toolkit.html). The reduction in mass flux is tabulated in Table 5 and show a significant reduction after remediation for the BTEX compounds of 97–99%. The TPH mass flux was also reduced significantly of over 64% based on the. conservative values in Table 5. Pre– and post–flush mass discharge measurements were utilized to correlate a Γ–factor based on the reduction in mass discharge, according to the Γ–model. Based on the TPH data and mass removal from the source zone, the Γ–factor is estimated to range from 0.41 to 0.85 depending on the indicator (TPH, benzene, or BTEX). The Γ–factor is in the range 0.51–0.69 if the groundwater gradient is considered steady at 1%. During post monitoring, the gradient varied from 0.5–2.0%, and was more unstable than during the baseline monitoring, when the gradient was stable around 1%. Therefore, the variation of the gradient has had greater influence on the mass discharge than the measured concentration levels. Thus, a steady gradient of 1% was used to estimate mass discharge, instead of using the varying gradient, in order to compare the mass discharge before and after remediation. The mass flux for both the varying and steady gradient conditions were computed and the results for TPH are compared in Fig. 12 to the baseline conditions which show reduction in mass flux of 93.2% for a varying gradient and 98.5% assuming a steady gradient.
It is important to note several points regarding this project. First, that the surfactant flood used to mobilize and recover the LNAPL was completed in a relatively short period of time: the entire field project took less than six months, including down-time used to make measurements and confirm the design. Second, the monitoring confirmed that the LNAPL movement was hydraulically controlled and captured. Post–surfactant flood analyses (aqueous sampling, LIF measurements, soil sampling) of the site indicate over 90% of LNAPL mass recovered. The reduction in mass flux from the site 1–year after treatment is over 98% with respect to BTEX compounds. With respect to total petroleum hydrocarbons, the mass flux reduction is 64% assuming a varying gradient or 88% if a steady gradient is assumed. The significance of the field work is important to consider in light of publications presenting laboratory work that cautioned against this approach for NAPL recovery. After a period of interest from the early 1990s to early 2000s, field implementation of surfactants declined. Although some publications presented the use of surfactants to increase solubility and recovery of NAPL by way of enhancing the conventional “pump–and–treat” approach, this paper presents the first known full–scale field application of micellar flooding to LNAPL recovery from the subsurface by means of mobilization. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References Babaei, M., Copty, N.K., 2019. Numerical modelling of the impact of surfactant partitioning on the surfactant-enhanced aquifer remediation. J. Contam. Hydrol. 221, 69–81. Batchu, S.R., Ramirez, C.E., Gardinali, P.R., 2014. Stability of dioctyl sulfosuccinate (DOSS) towards hydrolysis and photodegradation under simulated solar conditions. Science of Total Environment 481, 260–265. de Blanc, P.C., Lenschow, S.R., Christensen, A.G., Mygind, M.M., Lindof, A.M., Kostarelos, K., 2016. Multi-phase simulations for design of a surfactant – enhanced aquifer remediation. In: Battelle 2016 International Conference on Remediation of Chlorinated and Recalcitrant Compounds, May. California, USA. Brown, G.H., Brooks, M.C., Wood, A.L., Annable, M.D., Huang, J., 2012. Aquitard contaminant storage and flux resulting from dense nonaqueous phase liquid source zone dissolution and remediation. Water Resour. Res. 48. Brusseau, M.L., Nelson, N.T., Zhang, Z., Blue, J.E., Rohrer, J., Allen, T., 2007. Source-zone characterization of a chlorinated-solvent contaminated superfund site in Tucson, AZ. J. Contam. Hydrol. 90, 21–40. Childs, J., Acosta, E., Annable, M.D., Brooks, M.C., Enfield, C.G., Harwell, J.H., Hasegawa, M., Knox, R.C., Rao, S.P.S., Sabatini, D.A., Shiau, B., Szekeres, E., Wood, L.A., 2006. Field demonstration of surfactant-enhanced solubilization of DNAPL at Dover Air Force Base. J. Contam. Hydrol. 82, 1–22. Deepika, L., Tyagi, V.K., 2006. Sulfosuccinates as mild surfactants. Journal of Oleo Science 55 (9), 429–439. Delshad, M., Pope, G.A., Sepehrnoori, K., 1996. A compositional simulator for modeling surfactant enhanced aquifer remediation, 1 formulation. J. Contam. Hydrol. 23, 303–327. Delshad, M., Asakawa, K., Pope, G.A., Sepehrnoori, K., 2002. Simulations of chemical and microbial enhanced oil recovery methods. In: SPE/DOE Improved Oil Recovery Symposium, 13–17 April, Tulsa, Oklahoma, SPE-75237-MS. DiFilippo, E.L., Brusseau, M.L., 2008. Relationship between mass-flux reduction and source-zone mass removal: analysis of field data. J. Contam. Hydrol. 98, 22–35. DiFilippo, E.L., Carroll, K.C., Brusseau, M.L., 2010. Impact of organic-liquid distribution and flow-field heterogeneity on reductions in mass flux. J. Contam. Hydrol. 115, 14–25. Dwarakanath, V., Kostarelos, K., Pope, G.A., Shotts, D., Wade, W.H., 1999. Anionic surfactant remediation of soil columns contaminated by nonaqueous phase liquids. J. Contam. Hydrol. 38 (4), 465–488. Falta, R.W., Rao, P.S.C., Basu, N., 2005a. Assessing the impacts of partial mass depletion in DNAPL source zones I. Analytical modeling of source strength functions and plume response. J. Contam. Hydrol. 78, 259–280. Falta, R.W., Rao, S.P.C., Basu, N., 2005b. Assessing impacts of partial mass depletion in DNAPL source zones II. Coupling source strength functions to plume evolution. J. Contam. Hydrol. 79, 45–66. Fountain, J.C., Starr, R.C., Middleton, T., Beikirch, M., September 1996. A controlled field test of surfactant-enhanced aquifer remediation. Groundwater 34 (5), 910–916.
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