Optical Measurement of Saturates, Aromatics, Resins, And

Article pubs.acs.org/EF

Optical Measurement of Saturates, Aromatics, Resins, And Asphaltenes in Crude Oil Vincent J. Sieben, Alexander J. Stickel, Collins Obiosa-Maife, Jacalyn Rowbotham, Afzal Memon, Nejib Hamed, John Ratulowski, and Farshid Mostowfi* Schlumberger - Doll Research, One Hampshire Street, One Hampshire Street, Cambridge, Massachusetts 02139, United States S Supporting Information *

ABSTRACT: We describe a novel apparatus and method for rapidly separating and measuring four subfractions of crude oil: saturates, aromatics, resins, and asphaltenes (SARA). This work is an extension of our previous work on the microfluidic measurement of asphaltene content, where a microfluidic technique was used to rapidly separate asphaltenes from crude oil for indirect optical measurement. Here, we extend the measurement by adding column chromatography to fractionate the deasphalted oil into saturate, aromatic, and resin fractions. Saturates are measured by refractive index, whereas the aromatics, resins, and asphaltenes are measured by ultraviolet−visible (UV−vis) absorbance. We evaluate 15 samples from various geographical origins to determine appropriate optical-to-gravimetric response factors. The response factors are then used to enable a seamlessly automated SARA measurement technique. When the 15 samples are run through the automated procedure, the optical-to-gravimetric root-mean-square error (RMSE) values are ±3.8 wt % for saturates, ±2.7 wt % for aromatics, ±2.3 wt % for resins, and ±1.2 wt % for asphaltenesabsolute errors. The final microfluidic SARA technique exhibited excellent reproducibility; the measurements were within ±0.8 wt % for saturates, aromatics, and resins and within ±0.2 wt % for asphaltenes. Further, the technique reduced SARA experimental times from 2 days to 4 h for topped samples while greatly reducing the need for manual labor.

■

INTRODUCTION Petroleum composition data has an important role in guiding both upstream and downstream operationsto understand fluid behavior inside the reservoir, to provide flow assurance during transportation, to understand potential outcomes when mixing or blending or diluting, to direct refinement processes, and to verify sample integrity and chain of custody.1,2 Separating the oil into its constituents is a fundamental step when characterizing the composition of a crude oil. Once separated, the fractions can then be quantified and analyzed. One of the most widely used methods to characterize the composition of a petroleum sample is SARA fractionation, which is based on molecular polarizability and solubility and separates the oil into four parts: saturates, aromatics, resins, and asphaltenes (SARA).3 The fractions are then gravimetrically weighed and reported as a weight percentage of the initial whole oil. The saturate fraction is composed of aliphatic hydrocarbon molecules that are nonpolar, which include normal alkanes, branched alkanes, and cycloalkanes. The aromatic fraction contains one or more aromatic ring hydrocarbons that may also include alkyl side chains. In some cases, the saturate fraction may contain a trace amount of aromatic ring structures with long aliphatic side chains. The saturate fraction contains few heteroatoms (N, S, O), whereas the aromatics may contain appreciable amounts of these heteroatoms (see supplementary). The last two SARA fractions, the resins and asphaltenes, are typically aromatic polycyclic molecules that may include alkyl side chains, heteroatoms, and/or trace metals (e.g., Ni, V, Fe).4 These fractions may also include other polar molecules like aliphatic acids, especially polar N- and O-heterocyclic © XXXX American Chemical Society

molecules. The resins and asphaltenes are the heaviest, most high-boiling, and most polar fractions of crude oil. The difference between the resin and the asphaltene fractions is in their solubility profile. Resins are defined as being soluble in nalkanes, such as n-pentane or n-heptane. Conversely, asphaltenes are defined as being insoluble in light n-alkanes and soluble in solvents, such as toluene or dichloromethane.5 There are many practical implementations of SARA separation and characterization, and they are generally referred to as standard methods or modified standard methods in the literature. Seemingly small modifications to a SARA procedure, either by design or by human error, can produce notably different fractionation results, thus shifting the cut points between the S-A-R-A molecular categories. Inconsistencies arise in both the separation of asphaltenes from maltenes and the fractionation of latter into saturates, aromatics, and resins.6 Historically, this has led to inconsistent data reported to end users, who are not usually aware of the implemented protocol or analytical details used in acquiring the fractional percentages.7,8 This is particularly true when data is generated at commercial laboratories that use modified standard procedures and proprietary methods. Furthermore, the SARA procedure often requires several days of qualified technician time, occupies a considerable physical footprint, and consumes large volumes of solvent (including proper disposal), making the technique relatively expensive to perform. Received: December 9, 2016 Revised: March 3, 2017

A

DOI: 10.1021/acs.energyfuels.6b03274 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels Table 1. Crude Oils Used in This Study SARA composition: reported on topped oil basis (wt %)a crude oil sample no.

API gravity (deg)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

12.9 17.3 20.1 20.8 28.2 28.5 32.3 33.5 33.9 34.4 35.0 39.0 40.2 41.1 44.9

b

c

origin

remaining after toppingd

saturates

aromatics

resins

n-C7 asphaltenes

recovery

SAM NAM SAM SAM EAF SAM EAF SAM NAM EAF SAM MEA SAM SAM EAF

87.7 89.7 80.0 77.3 71.5 66.6 67.5 65.2 70.8 56.0 66.3 51.7 43.2 36.5 33.7

19.3 37.4 29.8 35.2 58.3 42.9 51.5 50.7 52.7 50.4 46.4 55.3 73.2 63.9 64.2

37.2 27.6 38.4 29.0 21.6 26.9 24.1 27.2 23.3 24.9 29.8 33.9 19.4 22.9 17.2

28.5 32.3 25.0 22.9 19.4 19.6 21.4 15.2 21.9 22.1 18.9 12.4 6.5 9.6 15.1

15.3 2.2 13.1 12.0 2.6 8.9 2.6 7.4 1.0 0.8 4.4 0.9 0.1 0.5 0.8

100.3 99.5 106.3e 99.1 101.9 98.3 99.6 100.5 98.9 98.2 99.5 102.5 99.2 96.9 97.3

Composition acquired on topped oil at 1 atm and 30 °C. bDensity measured on whole oil at 1 atm and 20 °C. cNAM = North America, SAM = South America and Mexico, EAF = Europe and Africa, MEA = Middle East. dTopping performed to an initial boiling point of 250−300 °C (see GC data in Supporting Information). eCrude oil 3 exceeded the quality control acceptance criteria of ±3 wt % on recovery.

a

been proposed for quantifying all SARA fractions.21,22 Likewise, spectroscopic methods have been proposed for quantifying SARA components based on infrared and principal-component analysis23,24 or nuclear magnetic resonance (NMR).25,26 Automated multicolumn SARA systems have been reported using protocols that often deviate from established standard methods or have limited sample sets that correlate new sensing approaches to the conventional gravimetric results.27−29 For example, the ASTM D2007 and ASTM D4124 standard methods are based on disposable stationary phases that are used once per analysis. ASTM D2007 specifies the use of attapulgus clay and silica, while ASTM D4124 specifies the use of alumina. The differences among the adsorbents in ASTM standard methods themselves are a source of variation in SAR separations, and this is further exacerbated by variations that exist within physical properties of the adsorbents (pore size, particle size, and surface pH) that are often not included in the literature. Many of the aforementioned novel processes rely on reusable functionalized stationary phases. Ideally, new methods should match historical fractionation data and introduce minor deviations from the industry-accepted standard methods. Here, we aim to mimic the standard ASTM D6560 (asphaltenes) and D4124/D2007 (saturates, aromatics, resins) methods as much as possible and correlate optical data to gravimetric data for a diverse sample set. We describe a method based on a novel apparatus for rapidly separating and measuring four subfractions of crude oil: saturates, aromatics, resins, and asphaltenes. This report is an extension of our previous workbased on the microfluidic measurement of asphaltene content.30−34 Microfluidics is used to separate asphaltenes from the crude oil in a rapid manner and indirectly measure the asphaltenes as the difference between optical absorbance of toluene solutions of an oil and that of the heptane precipitated maltenes after microfluidic filtration of asphaltenesASTM D7996-15.35 In this work, miniaturized column chromatography is added to the analysis and used to fractionate the saturates, aromatics, and resins from the maltenes. Saturates are measured by refractive index, whereas the aromatics and resins are measured by UV−vis absorbance spectra. We show that the response factors and the

There are two main approaches to perform a SARA test: (1) utilize conventional wet chemistry, laboratory glassware, and large-column liquid chromatography followed by gravimetric measurements or (2) employ small-scale automated separation techniques followed by nongravimetric measurement of the fractions. Conventional approaches tend to take 2−4 days to complete, whereas new methods aim to perform SARA analysis in hours. Jewell et al.9 and Corbett10 pioneered the conventional approach nearly half a century ago, which led to the creation of standard methods such as ASTM D200711 and ASTM D4124.12 Initially, the asphaltenes are removed from the crude oil sample and the fractional content is measured. This is done using a procedure similar to those mentioned in standard methods, such as IP-143 or ASTM D6560.13 The remaining fractions are saturates, aromatics, and resins (SAR), collectively referred to as petrolenes, maltenes, or deasphalted oil. In conventional wet chemical separations, the SAR liquid chromatography is based on polar stationary phases comprised of clay, alumina, silica, and/or combinations. The maltenes are loaded onto the stationary phase, and separation of the various fractions is accomplished by sequentially increasing the eluent’s polarity and capturing the eluatea process termed sequential elution liquid chromatography (SE-LC). The collected fractions are then concentrated by evaporation of the elution solvent to recover the solute. As a quality check, the weights of the three fractions are summed and compared to the weight of the injected maltenes to determine the percent recovery. This conventional gravimetric method is time consuming and difficult to automate, consumes large volumes of solvents and sample, and can be intractably variable from one laboratory to the next without full disclosure of the technique. The second approach to perform a SARA test aims to remove operator bias, improve interlaboratory consistency, and provide SARA results more rapidly. These strategies rely on new detection methods to replace the cumbersome gravimetric measurement and build upon increased automation to improve standardization. Variations of high-performance liquid chromatography (HPLC) have been explored for optimizing the SAR separations,14−20 while thin-layer chromatography (TLC) equipped with a flame ionization detector (Iatroscan) has B


Article

Energy & Fuels

Figure 1. System configuration. Optical path length is 3 mm for asphaltenes and 5 mm for aromatics and resins. analysis. This prevents loss of sample as the procedure is performed. Here, we used elevated temperature and flowing nitrogen to remove the volatile components; however, other methods, such as spinning band distillation, may be more appropriate if available. One of the goals of this work is to produce a portable SARA prototype with an accompanying topping solution. The “jet evaporation” approach is more cost effective and has a smaller-simpler implementation, making the technique suitable for deployment in remote laboratories and locations. The native or neat crude oil samples were loaded into several vials (15 mL, 21 mm diameter) with the aliquot masses ranging from 2 to 3 g. The initial weights were measured and recorded. The samples were then placed on an evaporation hot plate purchased from Fisher (Reacti-Therm TS-18822 and Reacti-Vap TS-18825). The sample aliquots were heated to 80 °C and subjected to flowing nitrogen gas at 200 ± 50 standard cubic centimeters per minute (SCCM) (ultrahigh purity, 99.999%) for 22 h, and after cooling the weight was recorded. The samples were placed on the hot plate evaporator for an additional 2 h, and after cooling the weight was recorded. The rate of weight loss for all 15 samples was less than 0.3 wt % per hour after a 24 h period. The final weight percentage remaining after topping is shown in Table 1 for each sample. For three wide-ranging crude oils, we show the loss of weight versus sample conditioning time and show the final gas chromatographs in the Supporting Information. These three samples were the heavy crude oil 4, the medium/black crude oil 6, and the light crude oil 13. The data shows that the samples were effectively topped to an initial boiling point between 250 and 300 °C. Microfluidic SARA Measurements. The high-level schematic of the MF-SARA device for the fractionation and optical SARA measurement is shown in Figure 1. A detailed description of the asphaltene portion of the apparatus has been recently published.34 The

method of measuring SARA fractions described in this manuscript may be applicable to a wide range of crude oil types. The technique also demonstrates excellent reproducibility and shortened experimental times.

■

METHODS AND MATERIALS

The novel microfluidic SARA (MF-SARA) method was calibrated to gravimetric SARA data using a set of 15 crude oil samples from various geographical regions; samples ranged from heavy oils to black oils and condensates. The 15 crude oil samples are listed in Table 1, with their respective density, geographical origin, percentage by weight remaining after topping (RAT), and topped SARA fraction weight percentages. The sample set covered a wide range of SARA fractions: 19.3−73.2 wt % saturates, 17.2−38.4 wt % aromatics, 6.5−32.3 wt % resins, and 0.1−15.3 wt % asphaltenes. The SARA fractional weight percentages for each crude oil were measured using a modified ASTM D6560 (IP 143)13 and a modified ASTM D412412 procedure, with modifications and details described below. HPLC-grade solventsn-heptane (CAS 142-82-5), toluene (CAS 108-88-3), chloroform with 0.75% ethanol preservative (CAS 67-66-3), 2-propanol or isopropyl alcohol (CAS 67-63-0), and dichloromethane (DCM) (CAS 75-09-2)were used for the entire process and all purchased from Fisher Scientific (New Jersey, USA). Silica gel was purchased from Sigma-Aldrich (214477, particle size 100−200 mesh or 74−149 μm, pore size 30 Å) and dried at 130 °C for an hour prior to use. Topping. The crude oil samples were first stabilized by removing volatile components, a process otherwise known as topping the crude oil. ASTM D2007 specifies that the standard method is intended for a crude oil with an initial boiling point of at least 260 °C for SARA C


Article

Energy & Fuels

Figure 2. Optical output data generated by the MF-SARA unit for crude oil sample 8. Portion of the SAR optical measurements with peaks are shown to aid visualization, but the aromatic and resin runs are longer and return to baseline (see text). System monitoring of fluid pressure, pump activity, valve state, temperature, ambient humidity, etc., demonstrates consistent operation; data not shown. microfluidic SARA prototype automates the described optical sensing strategy to measure asphaltene weight percentage. Second, the stored maltenes from the microfluidic system are then processed by the SAR portion of the apparatus (the right part of Figure 1), where liquid chromatography is performed. The maltenes generated by the asphaltene process are stored in the maltenes valve and are introduced to the stationary phase after the column has been primed with 40 mL of n-heptane. Here, we use silica gel that is activated at 130 °C for 1 h. Fractionation of saturates begins by flowing 12.5 mL of n-heptane through the column at a rate of 2.5 mL/ min. The nonpolar molecules have little to no interaction with the silica and elute first. During this first elution, aromatic and resin fractions are retained in the column by the stationary phase. Both UV−vis data (365, 455, 590, and 780 nm) and refractive index data (950 nm at room temperature) are recorded during the saturate elution. The saturate fraction is colorless, and it can only be accurately measured by refractive index. The UV−vis absorbance data collected during the saturate elution is used primarily for quality control to ensure that aromatics and resins are being sufficiently retained by the stationary phase and are not breaking through into the saturate fraction. The eluate from the column may be collected in the saturate fraction bottle for subsequent weight measurement. Third, upon completion of the saturate run, the mobile phase is switched and the adsorbed aromatic fraction is eluted from the stationary phase in the column. The eluent used to remove aromatics must be tuned for different types of stationary phase. It was determined that a premixed solution of 90% n-heptane and 10% toluene (v:v) was suitable for the selected silica gel and was able to match the fractionation results of the alumina stationary phase, as per ASTM D4124 (see Supporting Information). For the aromatics, 50 mL of 90:10 heptane:toluene (v:v) was delivered to the column at a rate of 2.5 mL/min. During elution of aromatics, UV−vis optical absorbance data is recorded at 365 and 780 nm and the eluate is collected in the aromatic fraction bottle. Fourth and finally, the resin fraction is extracted from the column by eluting with a solvent series, increasing in polarity over time. Two solvents were required to provide a controlled release of resins, such that the recorded signal did not saturate the optical absorbance detector and data quality could be preserved. The first solvent was a

topped crude oil is injected into the MF-SARA apparatus through a 10 μm frit, shown on the left side of Figure 1. The sample is stored in the crude oil valve’s sample loop, which has a volume of 454 μL. The user loads a new polytetrafluorethylene (PTFE) filter membrane with a 0.2 μm pore size onto the microfluidic chip. A small column (8 mm i.d. × 85 mm long) is loaded with silica gel and connected to the apparatus. Finally, the user enters sample information and starts the automated process. The relevant process details are described below. During the automated process there are multiple cleaning, flushing, and referencing steps that are performed to ensure correct device operation. For simplicity, these steps are not described. First, the asphaltene content is measured indirectly on the asphaltene microfluidic chip, described in previous references.31,32 A portion of the sample is displaced from the sample loop with pump 1 at 10 μL/min and combined in the mixer reactor with toluene pumped at 800 μL/min by pump 2 for 5 min. After passing through the 0.2 μm PTFE filter, the toluene solution flows through the asphaltene f low cell into wastepassing through the maltenes valve. After appropriate flushing, a second portion of undiluted crude oil is pumped from the sample loop at 10 μL/min and combined with n-heptane flowing at 400 μL/min in the mixer reactor for 5 min. During this time aggregated asphaltenes are removed from the heptane solution by the 0.2 μm PTFE filter. The filtered maltenes solution then flows through the asphaltenes f low cell into wastepassing through the maltenes valve. Initially, the maltenes solution is directed to waste by flowing through the maltenes sample loop. After 250 s, the maltenes valve rotates to capture and store 454 μL of representative maltenes for SAR liquid chromatography. The remaining maltenes are sent directly to waste, and the system completes automated cleaning of the microfluidic chip.31 By subtracting the UV−vis spectrum of maltenes solution from that of the diluted crude oil, the spectrum of asphaltenes can be deducedrecorded as the asphaltene optical measurement. Asphaltene absorbance is extracted from the spectrum by taking the absorbance at 590 nm minus the absorbance at 780 nm as per ASTM D7996-15.35 Kharrat et al. showed that the absorbance of asphaltenes correlates well with their weight percentage, measured using the wet chemistry method.30 Historically, a similar approach was used by Bouquet and Hamon in 198536 and Fukui et al. in 1989.37 The D


Article

Energy & Fuels premixed, slightly polar solution of 2% isopropyl alcohol and 98% chloroform (v:v). The second solvent was a premixed solution of 50% isopropyl alcohol and 50% chloroform (v:v). The resin elution used 7.5 mL of the 98:2 cholorform:IPA (v:v) mixture and 30 mL of the 50:50 cholorform:IPA (v:v) mixtureboth delivered at a rate of 2.5 mL/min. The optical absorbance data at 455 and 780 nm was collected for the duration of both elutions, and both eluates were stored in the resin fraction bottle. The total solvent usage per MFSARA run is 431 mL; 261 mL of n-heptane, 113 mL of toluene, 37 mL of chloroform, and 20 mL of IPA. A typical run from the MF-SARA apparatus and protocol produces optical data as shown in Figure 2. The described process was used to evaluate the 15 samples in Table 1. Conventional SARA Measurements. The asphaltene measurement is performed after topping the crude oil. Asphaltene content was determined using a modified ASTM D6560 (IP 143) standard method. First, 2−3 g of topped oil sample was added to 40 mL of HPLC-grade n-heptane per gram of crude oil. The mixture was brought to a boil and subjected to reflux for 2 h. The mixture was then sealed and placed in a dark location to cool for 90 min. The precipitated asphaltenes were isolated with a 0.2 μm pore size PTFE filter. The filter paper and asphaltenes were folded, clamped, and subjected to rinses with n-heptane. The washes are performed to remove the nonasphaltenic materialsmaltenesthat may have been entrapped with the asphaltenes on the filter. The washes were performed by refluxing n-heptane for 2 h. Finally, the rinsed and retained asphaltenes were dissolved by refluxing DCM over the filter. The DCM/asphaltene mixture was collected, concentrated, and stored under nitrogen for subsequent weight measurement. The collected asphaltene weight divided by the starting crude oil weight was used to calculate the asphaltenes weight percentage. Also, the final filter weight was compared to the initial filter weight to ensure we accounted for retained inorganic solids that were cofiltered with the asphaltenes. The inorganic weight was negligible for all 15 samples, averaging 1 mg per 2−3 g of oil, with a standard deviation of ±2 mgwithin the measurement reproducibility error. The saturate, aromatic, and resin measurements were performed on the maltenes acquired from ASTM D7996 procedure and not on the maltenes produced from the preceding ASTM D6560 procedure. This was done to stay consistent with the automated and seamless MFSARA procedure, which separates maltenes obtained from ASTM D7996 into the SAR fractions. In other words, only the asphaltene measurement portion of the MF-SARA process was executed. However, instead of delivering the maltenes to the small column, the maltenes were stored in a collection vial. The ASTM D7996 method yields a small amount of maltenes per run, 10−25 mg. Therefore, multiple asphaltene runs (10−20) were performed on the same topped crude oil to generate sufficient maltenes for large-column chromatography analysis to ensure measurable SAR fraction weights. The collected maltenes were then concentrated using the evaporation hot plate. The maltenes were heated to 50 °C and subjected to flowing nitrogen gas at 200 SCCM for 5−10 h until the weight loss was less than 1% per hour. It should be noted that the final ASTM D7996 maltenes are created from a precise 1:40 ratio titration with n-heptane, and no additional refluxing or washing is performed. The ASTM D6560 filtered maltenes are combined with the permeate from the 2 h of refluxing heptane used for the washing step, where the temperature of the heptane rinse ranges from 60 to 70 °C. This additional washing changes the cut between resins and asphaltenes, making the ASTM D6560 maltenes contain more heavy components than the ASTM D7996 maltenes. The maltenes were then separated on a large water-jacketed column (11 mm i.d. × 600 mm long) filled with activated silica gel. The large column was held at 30 °C for the duration of the separation, as was the small column. The large column was first primed with 260 mL of nheptane at a rate of 2.5 mL/min. Then 100 mg of maltenes was manually loaded into the headspace of the column. The separation was performed with an automated process identical to the small-column process, but larger volumes of solvents were used. The volume of the large column was 13 times larger than that of the small column. This

multiplier was used to set the elution volumes for saturates and aromatics. Saturates were acquired by flowing 168 mL of n-heptane through the column at a rate of 2.5 mL/min. Aromatics were acquired by flowing 650 mL of 90:10 heptane:toluene (v:v) at a rate of 2.5 mL/ min. Resins were acquired by flowing 250 mL of 98:2 chloroform:IPA (v:v) and 130 mL of 50:50 chloroform:IPA (v:v) at a rate of 2.5 mL/ min. While the fractions were eluting, the optical data was also being recorded by the spectrometer and refractive index detectors in the MFSARA apparatus. This enables determination of the optical-togravimetric response factors. The collected fraction−solvent mixtures were stored in separate glass bottles and then concentrated by rotary evaporation. The concentrated mixture was transferred to small glass vials and dried to remove the elution solvent using evaporation on the hot plate. The fractions were heated to 50 °C and subjected to flowing nitrogen gas at 200 SCCM for 24−36 h until the weight loss was less than 1% per hour. The total solvent usage of the conventional SARA was between 2.5 and 3 L. We determined that the automated system operated reliably when sample viscosity was less than 300 cP. For some of the samples, topping increased the viscosity and it was required to dilute them in toluene (1:1 m/m) prior to injection. This did not appreciably impact results. The asphaltene/resins cut point remained the same as the sample is titrated with 40-fold n-heptane. For large-column SAR, the added toluene was removed prior to separation during the maltenes concentration step. For the automated small column SAR, the toluene eluted with the saturates fraction. It appeared as a separate and distinct peak and was not integrated when determining the saturates area. Separation of the Saturates and Aromatics. The saturates and aromatics generated from the preceding procedure were analyzed to qualitatively assess the cut point. The collected saturates and aromatics for five samples were evaluated using GC-MS (data summarized in the Supporting Information). For all five samples, data showed that saturates and aromatics are separated well. A minor amount of monoaromatic compounds was collected in the saturate fractions: 0.09 ± 0.08% monoaromatic steranes (m/z 253), 0.07 ± 0.08% alkyltoluenes (m/z 106), and 0.05 ± 0.03% alkylbenzenes (m/z 92). The aromatic fractions contained 0.04 ± 0.05% monoaromatic steranes, 0.41 ± 0.33% alkyltoluenes, and 0.13 ± 0.13% alkylbenzenes. Figure 2 shows that most of the saturates were completely eluted within 180 s or 7.5 mL or 1.8 column volumes. Therefore, it may be possible to shorten or even halve the duration of the saturate run (saturate elution volume) to further reduce the collection of aromatics in the saturates. However, the concentration of aromatics in the saturate fraction is insignificant, and the extended saturate elution volume ensures the complete extraction of the saturates from the column for a broad range of crude oils. The breakthrough of aromatics into the saturate fraction is somewhat expected. Wallace et al.38 as well as other authors39 showed that both silica and alumina do not fully resolve the saturate and aromatic fractions. For this application (SARA), Wallace et al. concluded that the silica column alone is sufficient for preliminary characterization of a sample and that further examination of the saturates (e.g., GC-MS for analyzing C14−C30) can provide additional details if required. The GC-MS data also verified that the topping procedure entirely removed components below tetradecane with a boiling point of 254 °C and also removed a portion of pristane with a boiling point of 296 °C. Perhaps the procedure is overly aggressive on the removal of volatiles and can be adjusted with reduced topping time. The data in the Supporting Information shows that the crude oil volatile removal rate reaches a plateau after 12 h, where the crude oil material loss is less than 0.5 wt % per hour. Elemental analysis (C−H−N−O−S) of all four SARA fractions for crude oils 1, 2, 8, 9, and 12 was also performed, with details provided in the Supporting Information.

■

RESULTS AND DISCUSSION The following sections describe the acquired response factors for the SARA fractions, the miniaturization of the SAR column, E


Article

Energy & Fuels

Figure 3. SARA response factor correlations for saturates, aromatics, resins, and asphaltenes. SAR response factors represent fractional weights collected from large-column chromatography versus optical areas for 15 samples. Asphaltene response factor represents the modified ASTM D6560 asphaltene weight percentage described in the methods versus the ASTM D7996 asphaltene absorbance for the samples tested in this study as well as a larger set of 52 samples. Response factor equations are determined by a least-squares linear fit to the data. For saturates, aromatics, and resins, the Y-error bars are ±2 mg, based on measurement error. Error bars for asphaltenes are discussed in previous work.31 Refractive index is measured at 950 nm and 25 °C. Dashed lines represent the RMSE bounds.

and the final comparison between the fully automated optical MF-SARA fractionation and the gravimetric data. Response Factors. Figure 3 shows the SARA optical-tomass response factor correlations for saturates, aromatics, resins, and asphaltenes along with the corresponding residuals. The asphaltene response factor has been studied in previous work,31,32 where the asphaltene content by weight percentage was correlated to UV−vis optical absorbance at 40:1 dilution. The first published microfluidic asphaltene setup reported a response factor of 1.62 wt %/(au·cm−1) using a sample set of 52 crude oils (sample set A). Optical absorbance was recorded at 600 nm less the baseline absorbance at 800 nm, hereafter reported using the notation 600−800 nm.32 Since then we developed a second microfluidic asphaltene system that increased the level of automation, details described by Sieben et al.34 The second device was calibrated using a different set of 52 crude oils (sample set B) with a response factor of 1.55 wt %/(au·cm−1). The 0.07 wt %/(au·cm−1) discrepancy is due to incremental improvements to the protocol and increased automation. For example, the first prototype used a combination of 40:1 and 80:1 for the oil dilution step, whereas data for the second prototype correlation only used 80:1 for the oil dilution step. In total, we analyzed over 100 crude oil samples from various geographical regions using our optical

method and determined that the above correlation appears to be valid for typical crude oils. The MF-SARA apparatus presented in this work implemented the second system’s process and automated protocol. However, the microfluidic SARA device used slightly different wavelengths of measurement to be compatible with ASTM D7996. The asphaltene absorbance at 600 nm was changed to 590 nm, and the reference absorbance at 800 nm was changed to 780 nm. The second asphaltene prototype mentioned above recorded the entire spectra for the diluted oil runs and maltenes run, so we were able to reprocess the data at the newly selected wavelengths. The revised data is shown in Figure 3 with red hollow squares, and the resulting response factor is 4.95 wt % per absorbance unit (sample set B) using a 3.0 mm optical path length flow cell and measuring absorbance at 590 and 780 nm. The black solid circles represent the data for the 15 samples tested in this study, which very closely resemble ASTM D7996. The minor difference is due to the smaller sample set of this study. Therefore, we use a response factor of 1.49 wt %/(au· cm−1) normalized to optical path length based on the standard. We can derive the average effective mass attenuation coefficient for asphaltenes with the response factor correlation. According to the Beer−Lambert law for optical absorbance, the response factor is inversely proportional to the product of the optical path length and the mass attenuation coefficient (see F


Article

Energy & Fuels

represent the contribution from aromaticity, meaning that nonaromatic molecules in the aromatic and resins fraction would go undetected at these wavelengths. As such, the MFSARA method is less sensitive to molecules with optical properties that are close to those of the chosen elution solvent for the various subfractions. The important consequence of utilizing intercepts is that it places a lower bound on the percentages reported from the apparatus. Given the intercepts listed in the linear correlations, the lowest weight percentages the system can report (based on a 100 mg injection) are 7 wt % for saturates, 16 wt % for aromatics, and 7 wt % for resins. The degree of scatter about each linear correlation was evaluated using the root-mean-square error (RMSE), calculated as

Appendix). Therefore, the asphaltenes effective mass attenuation coefficients are 2.81 L·g−1·cm−1 (600−800 nm) for the first calibration and 2.94 (600−800 nm) or 3.07 L·g−1·cm−1 (590−780 nm) for the second calibration, assuming an oil density of 0.9 g·cm−3. The range of variation in crude oil densities only slightly modifies the average response factor, with asphaltene molecular distribution as the primary source of deviation from the generalized response factor. The saturate, aromatic, and resin response factors of Figure 3 show the measured optical areas plotted versus collected masses for the subfractions. The data in Figure 3 was generated using a large-column configuration as described in the Methods and Materials section, typically injecting 100 mg of maltenes. On occasion, a slightly lower mass of maltenes (60−80 mg) was injected for heavier oils to avoid excess absorbance values during the resin optical area measurement. The saturates had a refractive index response factor of 4.83 × 10−4 g·(ΔmRIU·s)−1, which is close to our hypothetical value of 5.41 × 10−4 g· (ΔmRIU·s)−1. The aromatic response factor of 1.69 × 10−5 g· (Δabs·s)−1 is near that of our arbitrary hypothetical value of 0.99 × 10−5 g·(Δabs·s)−1. The resin response factor of 3.28 × 10−5 g·(Δabs·s)−1 is close to our arbitrary hypothetical value of 3.21 × 10−5 g·(Δabs·s)−1. The hypothetical response factors, derived in the Appendix of this paper, are used primarily to verify that the measured or reported response factors are reasonably close to similar molecules for the saturate, aromatic, and resin fractions. Similar to the asphaltenes, we can derive average physical properties from the SAR correlations. For the saturates, an effective refractive index of 1.4589 (25 °C, 950 nm) and a density of 0.813 g·cm−3 would produce the measured refractive index response factor, as observed in Figure 3. The aromatics effective mass attenuation coefficient is 4.925 L·g −1 ·cm −1 (365−780 nm). The resins effective mass attenuation coefficient is 2.539 L·g−1·cm−1 (455−780 nm). The saturate, aromatic, and resin correlations in Figure 3 required intercepts to provide an optimal linear fit to the data, unlike the asphaltene linear correlation with a zero intercept. The saturate, aromatic, and resin y-axis intercepts are 7, 16, and 7 mg, respectively. Ideally, the optical detectors would sense all molecules in the various subfractions, and zero concentration would correspond to a zero optical absorbance value. When we performed blank runs with no sample injected, we observed near-zero area and near-zero weight with a compounded experimental error of 2 ± 2 mg. The authors hypothesize that the origin of the intercepts for saturates, aromatics, and resins is partially due to the presence of molecules that pass optically undetected and are not included in the measurable area. In such cases, these molecules add no optical signal area (x axis) even though they add mass to the collected fraction (y axis). Saturates close to the refractive index of n-heptane, the reference fluid, are effectively “invisible” and not detected by the refractive index unit. Similarly, aromatics with minimal absorbance at 365 nm and resins with minimal absorbance at 455 nm are precluded from the aromatic and resin optical measurements, respectively. To optically measure most aromatic molecules would require a lower wavelength range, near 250−280 nm, and that would require an elution solvent other than toluene to be used. It was empirically determined that absorbance measured at 365 nm for aromatics and 455 nm for resins ensured that the absorbance values recorded were within the detection limits of the spectrometers while maximizing sensitivity and covering the possible range of crude oils. Further, UV−vis absorbance measurements

RMSE =

1 df

n

∑ (yi ̂ − yi )2 i=1

(1)

where ŷi are the optically determined weight percentages/ masses (predictions), yi are the gravimetrically measured weight percentages/masses, n is the sample size, and df is the degrees of freedom (equal to n − 1 when the intercept is fixed at zero and equal to n − 2 when the intercept is determined in the fit). The first asphaltene correlation had a RMSE of ±0.825 wt % at 600−800 nm (data from previous work32); the second correlation had a RMSE of ±0.993 wt % at 600−800 nm and ±0.892 wt % at 590−780 nm (Figure 3 data). For the asphaltenes, both the response factor and the degree of scatter about the linear fit presented in Figure 3 is in reasonable agreement with previously reported values.31 Further details on asphaltene measurement repeatability can be found in ASTM D7996. The saturates, aromatics, and resins had RMSE values of ±6.06, ±2.45, and ±1.95 mg, respectively. Part of the RMSE arises from the observable variation in repeat blank measurements, which showed ±2 mg errorlargely from the manually executed protocol steps and the measurement limits of mass balances. The remaining scatter is likely due to minor variation in the effective molecular attenuation coefficients/optical properties between different crude oil compositions. In terms of weight percentages, the errors correspond to approximately ±6.06 wt % for saturates, ±2.45 wt % for aromatics, and ±1.95 wt % for resins, as the data were acquired using 100 mg of injected maltenes. With the response factors acquired, it is possible to seamlessly integrate the entire SARA measurement. However, given the small mass produced using the microfluidic asphaltene measurement, a smaller column is required for the SAR portion. Column Miniaturization. The microfluidic asphaltene portion of the MF-SARA apparatus produces a maximum of 50 mg of maltenes. During the deasphalting process, collection of the maltenes is optimally achieved in the steady-state region. The viable amount of maltenes collected reduces to 25 mg if maltenes are selected from the center of the steady-state region. The first and last 25% of the run are ignored to avoid analyzing nonrepresentative maltenes that arise from Taylor dispersion. The steady-state region is depicted by red dashed lines from 60 to 240 s in Figure 2. The maltenes from this region were collected for large-column experiments and required multiple repeat runs to achieve a sufficient amount. To ensure consistent maltenes injections for the small column runs, it was decided to conservatively target the ∼10 mg of the maltenes run from the back portion of the center cut plug (182−249 s). The G


Article

Energy & Fuels additional 9 s allows for dead volume. Therefore, to complete a fully automated MF-SARA analysis, it is necessary to shrink the column by an order of magnitude from 100 mg down to 10 mg. A column that is 10 times smaller will also enable a more rapid SAR fractionation but will not produce a sufficient amount of weight for each fraction to be reliably measured. If 10 mg of maltenes was injected, then a 2 mg error in measurement would lead to a ±20 wt % error, making the small-column data a challenge to calibrate to the gravimetric data. Therefore, to circumvent weight measurements on the small-column fractions, optical areas from the small-column setup must be calibrated to the optical areas from the largecolumn setup. Optical area should scale linearly with injected weight, provided the column is not overloaded. By plotting optical area normalized to the injected weight, it is possible to link the small-column area to the large-column area. Under ideal conditions, the slope should be unity, as the small and large columns should separate the fractions identically, yielding areas proportional to the injected weight. However, in practice, fluid dynamics, particle-to-column diameter ratio (using the same silica gel as stationary phase), sensor detection methodologies and limits, etc., are important factors that may lead to slight deviations between the small-column and the largecolumn setups. Figure 4 shows the large-column areas versus the smallcolumn areas, both normalized to their respective injected weights, for the saturates, aromatics, and resins of the 15 samples. Large-column SAR separations were completed on 100 mg of manually loaded maltenes generated by multiple microfluidic runs. Both area and weight are known in the largecolumn runs (i.e., the response factor data from Figure 3). The maltenes from the same crude oil were separated on a small column via the completely automated MF-SARA protocol. However, in the case of the small column, we are loading a fixed volume of heptane maltenes solution onto the columnstored from the preceding microfluidic asphaltene run. Small column chromatography is performed on 454 μL of heptane maltenes solution. Therefore, to estimate the maltenes weight loaded onto the small column we require the maltenes density. We assumed the maltenes density was near that of the measured neat oil density and estimated the maltenes weight for smallcolumn runs using the total fixed volume, heptane density, and dilution ratio (1:40, v:v). Using this approach the saturates area-to-area correlation is 1.003, which is near the expected parity. Similarly, the aromatics and resins are close to unity, with area-to-area correlations of 0.947. This suggests successful mapping from the small column to the large column and enables the small-column areas to be used in conjunction with the above response factors for determining saturate, aromatic, and resin weights. Comparison of MF-SARA to Gravimetric Measurement. The optical measurements produced by the MF-SARA device need to be converted to weight percentages for each of the fractions. To illustrate the calculations performed in the conversion, we use the optical data for crude oil 8 shown in Figure 2 as our example. The diluted oil steady-state absorbance was 0.663, and the maltenes steady-state absorbance was 0.345. The indirectly measured asphaltenes absorbance is 81/41 × 0.663 − 0.345, which equals 0.965. The asphaltene weight percentage is 4.95 × 0.965, which is 4.8 wt %. The gravimetrically measured asphaltene content for crude oil 8 was 7.4 wt %. The 2.6 wt % difference was one of the largest differences in the group of 15 crude oils.

Figure 4. Saturate, aromatic, and resin area-to-area comparisons between the large- and the small-column runs. Areas are normalized to the injected maltenes weight for 15 samples. Two columns show nearly identical fractionation of the maltenes, with near-unity correlations. Small column is 8 mm i.d. × 85 mm long, and large column is 11 mm i.d. × 600 mm long.

The saturate, aromatic, and resin weight percentages are determined by estimating the weights from the optically measured peak areas and the response factors. First, the smallcolumn optically measured peak areas are mapped to the corresponding large-column peak areas so that the response factors in Figure 3 can be utilized. The mapping is accomplished by employing the parity relationship demonstrated in Figure 4. The large-column area divided by the largecolumn injected weight is equal to the small-column area divided by the small-column injected weight, written as arealarge areasmall = mlarge msmall (2) arealarge = H

mlarge msmall

areasmall

(3) DOI: 10.1021/acs.energyfuels.6b03274 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels

Figure 5. (Top) Side-by-side comparison of the conventional and the fully automated MF-SARA data for topped oil injections. (Bottom left) SARA unity plot that compares optically determined weight percentages versus the measured weight percentages for 15 samples. (Bottom right) Differences by fraction and sample, listed in order of increasing degree of API gravity.

k mini =

mlarge msmall

weight percentages in blue. Stacked above the saturates on each bar are the aromatics weight percentages in yellow, followed by the resins weight percentages in wine/orange, and finally the asphaltenes weight percentages in black/gray at the top. Plotting the samples in this manner allows one to observe the similar cut points between the SARA fractions for both methods. Alternatively, the data is plotted on a parity graph in the lower left panel of Figure 5. The two methods produce very similar fractionation weight percentages, with a collective RMSE of ±2.6 wt % (n = 60, 15 samples × 4 fractions). The RMSE values by fraction are ±3.8 wt % for saturates, ±2.7 wt % for aromatics, ±2.3 wt % for resins, and ±1.2 wt % for asphaltenes. In Figure 5, the bottom right graph shows a plot of the errors or differences by fraction and by sample, listed in order of increasing degrees of API gravity. Above an API gravity of 21, no fraction exceeds ±5.5 wt % for any of the samples. The maximum error in the data set was for crude oil 4, with a −9.1 wt % saturates error and a 7.0 wt % aromatic error. Also shown in the bottom right of Figure 5 are the boundary lines for 95% confidence±5 wt % (1.96 × RMSE). The figure shows that the SAR scatter is larger than the asphaltene scatter. The difference between the MF-SARA method and the conventional SARA method is within the measurement reproducibility of the ASTM standard methods. The listed repeatability (95% confidence level) of ASTM D2007-11 is ±2.1 wt % for saturates, ±2.3 wt % for aromatics, and ±1.2 wt % for polars/resins (above 5 wt % content). The listed reproducibility (95% confidence level) of ASTM D2007-11 is ±4.0 wt % for saturates, ±3.3 wt % for aromatics, and ±1.8 wt % for polars/resins (above 5 wt % content).11 The ASTM

(4)

Therefore, the large-column area is equal to the small-column area multiplied by a “miniaturization coefficient”, which is approximately 10 as the ratio of injected weights. The smallcolumn area of 9.46 for saturates in Figure 2 would yield an area of 94.6 on the large column. The estimated saturate weight is determined from the response factor equation in Figure 3 94.6 × 4.831e−4 + 0.007which equals 53 mg. Similarly, the estimated aromatic weight is 29 mg, and the estimated resin weight is 21 mg. The total is 103 mg, close to the actual largecolumn runs that used 100 mg. The weights of each fraction enable us to determine the fractional weight percentages in the maltenes: 51.2 wt % for saturates, 28.6 wt % for aromatics, and 20.3 wt % for resins. The SAR fractional percentages are then normalized to the asphaltene content to yield the final SARA percentages: 4.8 wt % asphaltenes, 48.7 wt % saturates, 27.2 wt % aromatics, and 19.3 wt % resins. The measured gravimetric values were 7.4 wt % asphaltenes, 50.4 wt % saturates, 27.0 wt % aromatics, and 15.1 wt % resins. Figure 5 compares the optically determined weight percentages from completely automated MF-SARA runs versus the gravimetrically measured weight percentages for all SARA fractions. Percentages are normalized, totaling 100% for each sample. The top panel of Figure 5 shows the SARA data as a side-by-side comparison per sample, listed in order of increasing degrees of API gravity. For each sample, the left vertical bars are the conventional gravimetric SARA and the right vertical bars are the MF-SARA optical measurements. At the bottom of each vertical bar in the graph are the saturates I


Article

Energy & Fuels reported figures are only for oils with minor n-pentane asphaltene contentless than 0.1 wt %. The repeatability and reproducibility on crude oils with higher asphaltene contentsthose described herehas not been extensively validated, but the standard indicates one can approximate a repeatability of 1.3% and a reproducibility of 7.8%. The repeatability and reproducibility estimates for ASTM D4124-09 have not been reported.12 We observed similar magnitudes of error from internal round-robin studies, and other published SARA methods show similar ±5 wt % error levels.7 We demonstrated that the MF-SARA method produces fractionation weight percentages within the accepted error associated with the conventional SARA methodologies. Reproducibility. Crude oil 6 was used to evaluate the reproducibility of the MF-SARA method and apparatus. The sample was sent to three different laboratory locations (A, B, C), and the sample was analyzed by three different prototypes that were operated by five different employees (location B had multiple operators) over the course of 4 months. The resulting MF-SARA data from each analysis is shown in Table 2. Across

We can estimate the weight percentages of the fractions on a topped-oil basis, considering that 33.4 wt % of crude oil 6 was removed by topping. Assuming that most of the losses come from the saturates and some from the aromatics, we can calculate an “adjusted neat MF-SARA”Table 2. Typically, the lost hydrocarbon is comprised of 70 wt % saturates and 30 wt % aromatics and may be up to 95 wt % saturates and 5 wt % aromatics.3,28,40 Also shown in Table 2 are the MF-SARA data and the conventional SARA data acquired by using topped crude oil 6. The similarity between the topped SARA compositions suggests the MF-SARA apparatus may be able to detect the majority of the volatile fraction of light saturates and aromatics. However, it should be noted that a portion of the volatiles will not be detected. There will be an “optical topping” effect when injecting untopped oils, similar to what was described in the Results section on response factor intercepts. The saturates removed in the topping process are likely to have refractive indices close to that of n-heptane and will similarly go undetected in the case of untopped oil injections. Likewise, the most volatile aromatics, like alkyl benzenes and naphthalenes, will not contribute to UV absorption at 365 nm. Therefore, the “optical topping” combined with the estimated volatile adjustments may overcompensate for compounds actually lost. Topping samples minimizes the differences among heavy and light oils. Nevertheless, it is an interesting finding that suggests the accuracy of the fully automated MF-SARA approach is satisfactory, even when using neat oils. It may be possible to use the MF-SARA method for acquiring SARA compositions on a whole-oil basis with further validation. As there are no established accuracy guidelines for SARA analyses, the presented approach offers an automated SARA measurement method that produces consistent results with good reproducibility and reduced turnaround time that may find industry-wide use.

Table 2. Reproducibility Study of Crude Oil 6; Neat Oil Injections SARA composition (wt %) location and run Lab A-r1 Lab A-r2 Lab A-r3 Lab B-r1 Lab B-r2 Lab B-r3 Lab C-r1 Lab C-r2 Lab C-r3 neat MF-SARA avg. ± std. adj. neat MF-SARAa topped MF-SARAb conv. SARAc

saturates

aromatics

resins

asphaltenes

48.2% 47.9% 47.6% 47.6% 47.4% 47.7% 48.3% 48.4% 48.5% 48.0 ± 0.4

26.5% 26.7% 26.7% 27.0% 27.0% 26.8% 26.5% 26.3% 26.3% 26.6 ± 0.3

19.4% 19.4% 19.6% 19.4% 19.5% 19.4% 19.3% 19.3% 19.3% 19.4 ± 0.1

5.9% 6.0% 6.1% 6.0% 6.1% 6.1% 5.9% 6.0% 5.9% 6.0 ± 0.1

36.9 ± 0.6

25.0 ± 0.4

29.1 ± 0.2

9.0 ± 0.1

38.5

28.0

24.6

8.9

43.7

27.4

20.0

8.9

■

CONCLUSIONS Rapid optical measurements are a viable replacement for the laborious gravimetric techniques in determining fractional amounts of saturates, aromatics, resins, and asphaltenes in crude oil. No bias was detected using 15 samples from around the world, ranging from 12 to 45° API and having SARA compositions that spanned 19.3−73.2 wt % saturates, 17.2− 38.4 wt % aromatics, 6.5−32.3 wt % resins, and 0.1−15.3 wt % asphaltenes. The MF-SARA method provides fractionation results within ±2.6 wt % RMSE, absolute weight percentage error. The automated MF-SARA process enables a complete, time-efficient measurement in 4 h on a topped sample compared to the days associated with gravimetric approaches. Integration of optical spectroscopy, microfluidics, and automation ensures a high level of reproducibility, applicable to both topped and untopped crude oil samples. Reduction of environmental impact of the SARA technique is achievable by lowering the required volumes of harmful aromatic and chlorinated solvents by an order of magnitude. Overall solvent usage was reduced from 2.5 to 3.0 L down to 430 mL, which may eventually be reduced further by integrating the stationary phase onto the chip. The MF-SARA technique also provides improved safety by use of the closed fluidic circuit to shield the operator from solvents. The presented approach is an industrywide improvement for SARA measurement in terms of producing high data quality with reduced turnaround time.

a

Estimate of topped oil SARA from the whole oil SARA on neat crude oil. The crude oil 6 RAT is 66.6%, from Table 1. It is also assumed that the removed volatile fraction was comprised of 70 wt % saturates and 30 wt % aromatics. bMF-SARA data from Figure 5. cConventional SARA data when SAR portion is normalized to 100 wt %.

the nine experimental runs for crude oil 6, the standard deviation was less than ±0.4 wt % for the saturates, less than ±0.3 wt % for the aromatics, and less than ±0.1 wt % for the resins and asphaltenes. For simplicity, we lump the SAR measurements into one metric on reproducibility and the asphaltenes into another. The 95% confidence interval indicates a reproducibility of ±0.8 wt % for the SAR measurements and a reproducibility of ±0.2 wt % for the asphaltene measurement. A more comprehensive library of samples with varying SARA compositions will be evaluated for repeatability and reproducibility, which will be the focus of future work. The interlaboratory data produced in Table 2 was acquired by injecting neat crude oil 6 into the MF-SARA system; the sample contained the volatile fraction (the sample was not topped). Therefore, the average MF-SARA data from the neat oil runs is a report of the SARA fractions on a whole-oil basis. J


Article

Energy & Fuels

■

APPENDIX The following sections detail the optical-to-gravimetric linear relationships for saturates, aromatics, resins, and asphaltenes. Optical measurement of the SARA fractions is fundamentally based on generalizing the optical-to-gravimetric response for each of the subfractions. It is important to recognize the underlying assumptions when using the preceding linear-fitting approach, that is, response factors. Determination of robust and accurate response factors will require verification and validation on a number of samples to ensure broad empirical applicability to the majority of crude oil samples. At ambient pressure and room temperature, it is assumed that most crude oils can be represented by a set of single effective average optical response factors when measured in the manner described. The term “effective” is used to encompass the collective effect of a group of molecular species lumped into a single fractionmathematically represented as a single average value. For the 4 SARA fractions, these are • mass attenuation coefficient for asphaltenes at 590−780 nm • refractive index (at 950 nm) and density for saturates • mass attenuation coefficient for all aromatics at 365−780 nm • mass attenuation coefficient for all resins at 455−780 nm

which can also be stated as Wasph = RFasphC7A asphC7 RFasphC7 =

Accurately determining the effective saturate refractive index at ambient conditions would require a detailed knowledge of the saturate composition. The effective refractive index of a mixture of saturates can be calculated using ideal volumetric mixing laws at ambient conditions, such as the Lorentz−Lorenz equation42−44 nm2 − 1 nm2

kasphl

nm2 − 1 nm2 + 2

k1 =

k2 =

(A2)

where cm−asphC7 [g·L ] is the mass concentration of asphaltenes diluted at 40:1 equiv, kasph [L·g−1·cm−1] is the effective mass attenuation coefficient of the n-heptane asphaltenes, l [cm] is the optical path length of the flow cell, and AasphC7 is the absorbance of asphaltenes diluted at 40:1 (v:v). The weight percentage of asphaltenes in the original crude oil, Wasph [wt %], can be determined as follows

Wasph =

masph moil

·100 =

cm − asphC7·(Voil + Vs) ρoil ·Voil

41 1 · A asphC7 ·100 1000ρoil kasphl

n12

+2

+ ϕ2

n22 − 1 n22

+2

+ ... + ϕn

nn2 − 1 nn2 + 2

= ϕsat(k1 − k 2) + k 2

(A8)

2 nsat −1 2 nsat +2

(A9)

2 nhept −1 2 nhept +2

(A10)

where nsat is the effective refractive index of saturates, nhept is the refractive index of n-heptane, and k1 and k2 are their respective constants. We can then use Taylor’s theorem to simplify eq A8 and produce a first-order linear approximation between the refractive index of the mixture and the saturate volume fraction (i.e., nm versus ϕsat). This is a valid approximation as we are anticipating small refractive index changes about n-heptane (small saturate content compared to elution solvent volume), exemplified by the sensor measurement range of ±1 × 10−3 RIU about the reference fluid (Knauer Smartline 2300). The refractive index linear approximation is

−1

Wasph =

n12 − 1

(A7)

(A1)

A asphC7

+2

= ϕ1

where nm is the refractive index of the mixture and n1−nn is the refractive index of each individual component along with the respective volume fraction ϕ1−ϕn. In a SARA experiment, the saturates are carried past the refractive index sensor in a stream of n-heptane. The refractive index is measured in reference to nheptane using a differential refractive index sensor. As such, further simplifications can be made to eq A7, and it can be shown that the differential refractive index of saturates should be linearly proportional to the saturate volume fraction. Restating eq A7 and assuming a simple two-component system comprising a volume fraction of saturates (ϕsat) and a volume fraction of n-heptane (ϕhept = 1 − ϕsat) yields

where I, I0, k, cm, and l represent the intensity of the transmitted light, intensity of the incident light, effective mass attenuation coefficient, effective mass concentration, and optical path length, respectively. The Beer−Lambert law applies at the limit of infinite dilutions, where it is assumed molecules do not interact with each other. The MF-SARA device uses volumetric metering to combine the crude oil with solvent or titrant. To highlight the assumed physical parameters when measuring asphaltene content by optical absorbance, we rephrase the Beer−Lambert relationship stated in eq A1 to determine the mass concentration in 40:1 nheptane 1

(A6)

Saturates

Asphaltenes are known to follow the Beer−Lambert law in organic solvents.41 The Beer−Lambert law states that there is a linear correlation between optical absorbance and concentration

cm − asphC7 =

41 1 · ·100 1000ρoil kasphl

where masph [g] is the mass of asphaltenes, moil [g] is the mass of oil, Voil [L] is the volume of oil, Vs [L] is the volume of solvent/precipitant, ρoil [g·cm−3] is the density of crude oil (along with the 1000 factor for converting L to mL), and RFasphC7 [wt %·au−1] is the empirical response factor for the nheptane asphaltenes acquired from the correlation in Figure 3.

Asphaltenes

⎛I⎞ A = −log10⎜ ⎟ = k·cm·l ⎝ I0 ⎠

(A5)

·100

ΔRI = (nm − nhept) ≈ kRI·ϕsat

(A3)

kRI = (A4) K

(A11)

2 2 2 (nhept nhept + 2)2 ⎛ nsat − 1⎞ −1 ⎜ ⎟ − 2 2 6nhept ⎜⎝ nsat nhept +2 + 2 ⎟⎠

(A12)


Article

Energy & Fuels

values that are not intended to be exact but that can serve as guidelines to ensure our experimental values are within orders of magnitude for reasonably similar molecules. For example, we can arbitrarily use a simple three-ring aromatic hydrocarbon, such as anthracene (C14H10) that has a molar mass of 178.23 g/ mol and a molar attenuation coefficient of 1500 L·M−1·cm−1 at 365 nm.47 This yields a mass attenuation coefficient for anthracene of 8.4 L·g−1·cm−1. Therefore, using our 5 mm optical path length, the calculated aromatic response factor would be 0.99 × 10−5 g·(Δabs·s)−1. For the resins, we can arbitrarily use perylene (C20H12) as an example, which is a fivering polycyclic aromatic hydrocarbon with a molar mass of 252.32 g/mol and a molar attenuation coefficient of 650 L·M−1· cm−1 at 450 nm.47 For perylene, the mass attenuation coefficient of 2.6 L·g−1·cm−1 and a 5 mm path length yield a resin response factor of 3.21 × 10−5 g·(Δabs·s)−1.

Next, we can integrate the differential refractive index measurements (ΔRI area) over the elution volume/time to obtain the volume of saturates in the collection vial, assuming constant flow rate, as Vsat =

∫0

=

∫0

= FR =

V

ϕsat dV t

ϕsat

∫0

dV dt dt

t

ϕsat dt

FR ΔRIarea kRI

(A13)

msat = RFsatΔRIarea RFsat =

(A14)

■

ρsat FR kRI

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.energyfuels.6b03274. Sample weight remaining versus topping time for three crude oils, GC data for crude oils before and after topping, GC-MS analysis of the saturates fraction for crude oil 6, GC-MS analysis of the aromatics fraction for crude oil 6, summary of the GC-MS analysis for the saturates and aromatics fractions for crude oils 4, 6, 7, 10, and 14, summary of the elemental analysis for the saturates, aromatics, resins, and asphaltenes fractions for crude oils 1, 2, 8, 9, and 12, H/C atomic ratios for the saturates, aromatics, resins and asphaltenes fractions for crude oils 1, 2, 8, 9, and 12, elemental analysis for the saturates, aromatics, resins, and asphaltenes fractions for crude oils 1, 2, 8, 9, and 12, SAR weight percentages for 5 samples comparing the fractionation results for different stationary phases, brief summary of the ASTM methods for reference (PDF)

where Vsat is the saturate volume, V is the total elution volume (saturates + n-heptane), ϕsat is the instantaneous saturate volume fraction, t is the elution time, msat is the total mass of saturates, ρsat is the average density of the saturates, and FR is the flow rate. To provide a response factor estimate we assume the saturates have an effective density of 0.80 g·cm−3 and an effective refractive index of 1.45 (nD20), which are near that of pentacosane or C25.45 This is a reasonable estimate as the crude oil was topped, thereby removing components below an initial boiling point of 260 °C; the sample compositions are approximately C14+. The flow rate was 2.5 mL/min for the MF-SARA experiments. A refractive index of 1.387 (nD20) is used for n-heptane. With these physical parameters, we calculate an estimated saturate response factor of 5.41 × 10−4 g·(ΔmRIU·s)−1. Aromatics and Resins

The aromatics are eluted next, followed by the resins. Both are measured with UV−vis absorption spectroscopy. Equation A1, the Beer−Lambert law, is applicable and can be used to determine the aromatic and resin masses. We integrate the instantaneous absorbance measurements over the elution volume/time to obtain the total collected mass, assuming constant flow rate, stated as m=

∫0

V

cm dV = FR

∫0

t

cm dt = FR

∫0

t

■

RFaro/res =

*Phone: 617-768-2152. E-mail: fmostowfi@slb.com. ORCID

F A dt = R A area k·l k·l

Farshid Mostowfi: 0000-0002-6542-167X Notes

The authors declare no competing financial interest.

■

(A17)

ACKNOWLEDGMENTS The authors first acknowledge Artur Stankiewicz and Simon Andersen for informative feedback and expert review. Helpful peer review by Winston Robbins was greatly appreciated. We also acknowledge the many side conversations and ongoing support from Jose Zacharia, Oleg Medvedev, John Nighswander, Eric Lehne, Javed Alley, Shahnawaz Molla, Asok Kumar Tharanivasan, Cedric Floquet, Sharath Chandra Mahavadi, Nisha Nandanan, Joshua Larry, and Kevin James Smith. We appreciate the excellent service of Dean Mills and Ben Zimmer from Enable Ltd., who programmed much of the underlying LabVIEW firmware. Dolomite Ltd. provided highlevel technical expertise and competence regarding chip fabrication and interface manufacturing. Finally, the authors

FR karo/res·l

AUTHOR INFORMATION

Corresponding Author

(A16)

m = RF ·A area

ASSOCIATED CONTENT

S Supporting Information *

(A15)

(A18)

where m is the total mass (aromatics or resins), V is the total elution volume, cm is the effective mass concentration, t is the elution time, FR is the flow rate, A is the instantaneous absorbance, l is the optical path length of the flow cell, k is the effective mass attenuation coefficient (aromatics or resins), Aarea is the timewise integrated absorbance area, and RF is the response factor. There are no representative molecules that can be used for accurately estimating the aromatics and resins response factors, as these values arise from the variation and summation of many overlapping UV−vis/Urbach tails.46 However, we can calculate L


Article

Energy & Fuels

means of infrared and near-infrared spectroscopy. Energy Fuels 2001, 15 (5), 1304−1312. (24) Meléndez, L. V.; et al. Prediction of the SARA analysis of Colombian crude oils using ATR-FTIR spectroscopy and chemometric methods. J. Pet. Sci. Eng. 2012, 90−91, 56−60. (25) Sanchez-Minero, F.; et al. Predicting SARA composition of crude oil by means of NMR. Fuel 2013, 110, 318−321. (26) Molina, V. D.; Uribe, U. N.; Murgich, J. Correlations between SARA fractions and physicochemical properties with 1H NMR spectra of vacuum residues from Colombian crude oils. Fuel 2010, 89 (1), 185−192. (27) Boysen, R. B.; Schabron, J. F. The automated asphaltene determinator coupled with saturates, aromatics, and resins separation for petroleum residua characterization. Energy Fuels 2013, 27 (8), 4654−4661. (28) Adams, J. J.; Schabron, J. F.; Boysen, R. Quantitative Vacuum Distillation of Crude Oils to Give Residues Amenable to the Asphaltene Determinator Coupled with Saturates, Aromatics, and Resins Separation Characterization. Energy Fuels 2015, 29 (5), 2774− 2784. (29) Bissada, K. K.; et al. Group-type characterization of crude oil and bitumen. Part I: Enhanced separation and quantification of saturates, aromatics, resins and asphaltenes (SARA). Org. Geochem. 2016, 95, 21−28. (30) Kharrat, A. M.; Indo, K.; Mostowfi, F. Asphaltene content measurement using an optical spectroscopy technique. Energy Fuels 2013, 27 (5), 2452−2457. (31) Schneider, M. H.; et al. Measurement of Asphaltenes Using Optical Spectroscopy on a Microfluidic Platform. Anal. Chem. 2013, 85 (10), 5153−5160. (32) Sieben, V.; Kharrat, A.; Mostowfi, F. Novel measurement of asphaltene content in oil using microfluidic technology, SPE 166394. SPE Annual Technical Conference and Exhibition, ATCE 2013, New Orleans, LA; SPE, 2013. (33) Sieben, V. J.; et al. Asphaltenes yield curve measurements on a microfluidic platform. Lab Chip 2015, 15 (20), 4062−4074. (34) Sieben, V. J.; et al. Microfluidic Approach for Evaluating the Solubility of Crude Oil Asphaltenes. Energy Fuels 2016, 30 (3), 1933− 1946. (35) ASTM D7996-15, Standard Test Method for Measuring Visible Spectrum of Asphaltenes in Heavy Fuel Oils and Crude Oils by Spectroscopy in a Microfluidic Platform; ASTM International: West Conshohocken, PA, 2015; 10.1520/D7996-15; www.astm.org. (36) Bouquet, M.; Hamon, J. Y. Determination of asphaltene content in petroleum products for concentrations below 20000 ppm down to 150 ppm. Fuel 1985, 64 (11), 1625−1627. (37) Fukui, Y.; et al. Determination of Asphaltene Contents in Residual Oils by Dual Wavelength Spectrophotometry. Sekiyu Gakkaishi 1989, 32 (4), 183−189. (38) Wallace, D.; et al. Evaluation of some open column chromatographic methods for separation of bitumen components. Fuel 1987, 66 (1), 44−50. (39) Bastow, T. P.; van Aarssen, B. G. K.; Lang, D. Rapid small-scale separation of saturate, aromatic and polar components in petroleum. Org. Geochem. 2007, 38 (8), 1235−1250. (40) Cookson, D. J.; Lloyd, C. P.; Smith, B. E. A novel semi-empirical relationship between aromaticities measured from 1H and 13C n.m.r. spectra. Fuel 1986, 65 (9), 1247−1253. (41) Mostowfi, F.; et al. Asphaltene nanoaggregates studied by centrifugation. Energy Fuels 2009, 23 (3), 1194−1200. (42) Buckley, J. S.; et al. Asphaltene Precipitation and Solvent Properties of Crude Oils. Pet. Sci. Technol. 1998, 16 (3−4), 251−285. (43) Mehra, R. Application of refractive index mixing rules in binary systems of hexadecane and heptadecane withn-alkanols at different temperatures. Proc. - Indian Acad. Sci., Chem. Sci. 2003, 115 (2), 147− 154. (44) Tasić, A.Ž .; et al. Use of mixing rules in predicting refractive indices and specific refractivities for some binary liquid mixtures. J. Chem. Eng. Data 1992, 37 (3), 310−313.

are grateful for the client support and sample donations that enabled this study.

■

REFERENCES

(1) Wiehe, I. A.; Kennedy, R. J. Oil compatibility model and crude oil incompatibility. Energy Fuels 2000, 14 (1), 56−59. (2) Sinnathamb, C. M.; Nor, N. M. Relationship between SARA fractions and crude oil fouling. J. Appl. Sci. 2012, 12 (23), 2479−2483. (3) Kharrat, A. M.; et al. Issues with comparing SARA methodologies. Energy Fuels 2007, 21 (6), 3618−3621. (4) Mullins, O. C.; et al. Asphaltenes, Heavy Oils, and Petroleomics; Springer, 2007. (5) Speight, J. G. The Chemistry and Technology of Petroleum; Taylor & Francis, 1999. (6) McLean, J. D.; Kilpatrick, P. K. Comparison of Precipitation and Extrography in the Fractionation of Crude Oil Residua. Energy Fuels 1997, 11 (3), 570−585. (7) Wu, W.; et al. Errors and Repeatability in VSARA Analysis of Heavy Oils (SPE 146107). SPE Heavy Oil Conference Canada; Society of Petroleum Engineers: Calgary, Alberta, Canada, 2012. (8) Fan, T.; Wang, J.; Buckley, J. S. Evaluating Crude Oils by SARA Analysis. SPE/DOE Thirteenth Symposium on Improved Oil Recovery, Tulsa, OK, April 13, 2002; Society of Petroleum Engineers, 2002. (9) Jewell, D. M.; et al. Ion-exchange, coordination, and adsorption chromatographic separation of heavy-end petroleum distillates. Anal. Chem. 1972, 44 (8), 1391−1395. (10) Corbett, L. W. Composition of asphalt based on generic fractionation, using solvent deasphaltening, elution-adsorption chromatography, and densimetric characterization. Anal. Chem. 1969, 41 (4), 576−579. (11) ASTM D2007-11, Standard Test Method for Characteristic Groups in Rubber Extender and Processing Oils and Other Petroleum-Derived Oils by the Clay-Gel Absorption Chromatographic Method; ASTM International: West Conshohocken, PA, 2011; 10.1520/D2007-11; www. astm.org. (12) ASTM D4124-09, Standard Test Method for Separation of Asphalt into Four Fractions; ASTM International: West Conshohocken, PA, 2009; 10.1520/D4124-09; www.astm.org. (13) ASTM D6560-12, Standard Test Method for Determination of Asphaltenes (Heptane Insolubles) in Crude Petroleum and Petroleum Products. ASTM International: West Conshohocken, PA, 2012; 10.1520/D6560-12; www.astm.org. (14) Suatoni, J. C.; Swab, R. E. Rapid hydrocarbon group type analysis by high performance liquid chromatography. J. Chromatogr. Sci. 1975, 13 (8), 361−366. (15) Radke, M.; Willsch, H.; Welte, D. H. Class separation of aromatic compounds in rock extracts and fossil fuels by liquid chromatography. Anal. Chem. 1984, 56 (13), 2538−2546. (16) Radke, M.; Willsch, H.; Welte, D. H. Preparative hydrocarbon group type determination by automated medium pressure liquid chromatography. Anal. Chem. 1980, 52 (3), 406−411. (17) Grizzle, P. L.; Sablotny, D. M. Automated liquid chromatographic compound class group-type separation of crude oils and bitumens using chemically bonded aminosilane. Anal. Chem. 1986, 58 (12), 2389−2396. (18) Chaffin, J. M.; et al. The use of HPLC to determine the saturate content of heavy petroleum products. J. Liq. Chromatogr. Relat. Technol. 1996, 19 (10), 1669−1682. (19) Miller, R. Hydrocarbon class fractionation with bonded-phase liquid chromatography. Anal. Chem. 1982, 54 (11), 1742−1746. (20) Robbins, W. K. Quantitative Measurement of Mass and Aromaticity Distributions for Heavy Distillates 1. Capabilities of the HPLC-2 System. J. Chromatogr. Sci. 1998, 36 (9), 457−466. (21) Fan, T.; Buckley, J. S. Rapid and accurate SARA analysis of medium gravity crude oils. Energy Fuels 2002, 16 (6), 1571−1575. (22) Fuhr, B. J.; et al. Comparison of bitumen fractionation methods. Energy Fuels 2005, 19 (4), 1327−1329. (23) Aske, N.; Kallevik, H.; Sjöblom, J. Determination of saturate, aromatic, resin, and asphaltenic (SARA) components in crude oils by M


Article

Energy & Fuels (45) Riazi, M. R.; Al-Sahhaf, T. A. Physical Properties of n-Alkanes and n-Alkylhydrocarbons: Application to Petroleum Mixtures. Ind. Eng. Chem. Res. 1995, 34 (11), 4145−4148. (46) Mullins, O. C.; Mitra-Kirtley, S.; Zhu, Y. The Electronic Absorption Edge of Petroleum. Appl. Spectrosc. 1992, 46 (9), 1405− 1411. (47) Freidel, R. A.; Orchin, M. Ultraviolet Spectra of Aromatic Compounds; John Wiley & Sons Inc., 1951; p 708.

N


Optical Measurement of Saturates, Aromatics, Resins, And

Recommend Documents