Article pubs.acs.org/EF
Applications of Hydrocarbon Group-Type and Class-Type Analysis via Simulated Distillation-Mass Spectrometry for Process Upgrading Monitoring Lante Carbognani,*,† Roberto Meneghini,‡ Eumir Hernandez,† Joaquin Lubkowitz,‡ and Pedro Pereira-Almao† †
AICISE, Chemical and Petroleum Engineering Department, Schulich School of Engineering, University of Calgary, Calgary, Alberta, T2N 1N4, Canada ‡ Separation Systems Inc., 100 Nithingale Lane, Gulf Breeze Florida 32561, United States ABSTRACT: Characterization of petroleum samples in terms of boiling point distributions is at the core of the oil business. In addition, knowledge of chemical properties like molecular weight (MW) and hydrocarbon group-type as well as class-type distributions are also important parameters for monitoring upgrading processes. This work studied the feasibility of using gas chromatography coupled to flame ionization and mass spectrometry detection (GC-FID-MS) for providing all the former mentioned parameters in a fast and simple simultaneous approach that requires less than 1 h for completion. Comparison with routine thin layer chromatography with flame ionization detection (TLC-FID) and standardized supercritical fluid chromatography (SFC) for hydrocarbon group and class-type analyses validated the approach and, furthermore, allowed one to highlight advantages or disadvantages for the compared techniques. Upgrading processes carried out with atmospheric and vacuum distillate feedstocks were monitored with the mentioned characterization tools. The application of these techniques was found suitable for analyzing petroleum distillates comprised within the C5−C60 carbon range. GC-FID-MS was found suitable for samples containing low amounts of polar hydrocarbons, in addition was determined capable to discriminate HC-class-types for complex samples arising from hydroprocessing, catalytic upgrading, and physically separated distillation cuts. On the other hand, SFC and TLC-FID yielded restricted applicability in the light or heavy distillation ends.
1. INTRODUCTION Distillation is the most important physical separation technique implemented within oil operations since the petroleum industry inception more than 1 century ago.1 Laboratory scale physical distillation following standard methodologies2,3 is the basis for crude oil evaluation, providing fundamental information for its further valorization. Since physical distillation is expensive, labor intensive, and time-consuming, faster chromatographic alternatives known as SimDist (Simulated Distillation) were developed;4 methodology has been standardized even for very large residual hydrocarbons spanning up to 60 or 100 carbon atoms per molecule.5,6 SimDist routinely provides boiling point distribution profiles for petroleum samples and oil derived products from upgrading processes, and it is the preferred choice for calculating upgrading yields.7 Besides distillation properties, knowledge about the chemical nature of sample components before and after processing is deemed of utmost importance for a comprehensive process understanding, as extensively discussed in the Altgelt and Boduszynski monograph.8 The relative compositional comparison of “HC-class-types” within paraffinic and aromatic hydrocarbon “group-types” for unknown samples has been historically practiced after matrix simplification using physical separation with solvent treatments and subsequently followed by preparative liquid chromatography.9−11 Chromatographic isolated saturates and aromatic HC-group-type concentrates are conventionally analyzed for “HC-class-types”, i.e., cyclic/ noncyclic paraffins, mono, di, tri, and polyaromatic species via © 2012 American Chemical Society
mass spectrometry (MS). Very often these analyses depend on specific ASTM methods conceived for mandatory preisolated “HC-group-types”, i.e., saturates12 and aromatics13 from saturates, aromatics, resins, asphaltenes (SARA) separated hydrocarbon groups. MS methodologies for analysis of whole samples (no prior HC-group-type separation required) were a next logical step conceived for HC-class-type analysis. After the pioneering works using low-resolution MS (Robinson14) or high resolution (Gallegos and Teeter15), several MS methodologies for unseparated samples have been described, as discussed in a review article.16 However, these MS approaches commonly demand the use of complex mass spectrometers and highly skilled operators. The idea of using commercially available gas chromatographs coupled to reliable quadrupole mass spectrometers (GC-MS) and mass detector devices has made tremendous strides in the use of GC-MS. Coupled GC-MS systems provide two analysis dimensions, i.e, the time domain separation (chromatogram) plus the molecular selective information (MSpectrogram). Several authors have discussed these systems in the open literature, providing important operational details as well as reporting good results which are in agreement with other analytical techniques.17−19 Recently, an interface has been developed which is able to split the column effluent into two streams Received: January 26, 2012 Revised: March 2, 2012 Published: March 12, 2012 2248
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directed either to the flame ionization detector (FID) or to the MS, producing signals of similar intensity20 avoiding mass discrimination. The system provides SimDist-MS with software developed for both applications.20 Generally, high energy electron impact ionization (70 eV) is used within the described GC-MS systems which produces significant ion fragmentation that requires the development of complex algorithms for sound quantitative analysis. Soft ionization techniques like field ionization MS (FIMS), which mostly provide molecular ions, have been also described. However, HC class-type analysis still requires the development of dedicated computer programs for successful quantitative analysis.21 GC-MS systems still have unsolved aspects such as analysis carried out over less than 100% sample which occurs in cases for which analytes have not enough volatility for their successful injection and elution under the set up GC conditions. Currently, neutral molecules composed of up to 100 carbon atoms can be successfully analyzed, i.e., compounds that distill at equivalent boiling points of about 720 °C. HC samples possessing abundant heteroatomic polar fractions, also known as resins or polars, pose problems in GC systems, since polar HCs are irreversibly retained within injection system components. Furthermore, breakthrough from the inlet to the column, at the column head, cause extensive degradation of the column properties. Polars (resins) are not comprehensively determined with current available programs, since the existence of standard large molecular weight (MW) compounds for calibration purposes are not commercially available. Thus, samples containing resins are often analyzed via the following techniques: high-performance liquid chromatography (HPLC)off line MS,8 nuclear magnetic resonance (NMR) techniques capable of handling even vacuum residua and asphaltenes samples,22,23 and fast techniques like thin layer chromatography with FID detection (TLC-FID).24 Chromatographic techniques such as HPLC and TLC-FID, have the disadvantage that volatility is also an issue, restricting the analysis to fractions boiling above ∼220−250 °C, i.e., compounds larger than C13− C15. Smaller MW compounds are lost in the TLC-FID analysis protocol and any time solvent evaporation is implied in the HPLC procedure. This study was carried out to explore the feasibility of using a commercial GC-FID-MS system designed for providing boiling point distributions and HC-class-type analysis in a single run, i.e., SimDist-MS.20 The application of the technique seemed amenable since the technique can successfully handle wide boiling range samples spanning from about C5−C60. Several sets of HC distillates containing low amounts of polar hydrocarbons (no asphaltenes) were studied and the results compared with those determined via routine analysis with TLC-FID or standardized supercritical fluid chromatography (SFC).25 Selected examples from process upgrading monitoring illustrate the applications of GC-FID-MS and allowed us to comparatively ascertain the advantages or disadvantages of the GC-FID-MS versus the TLC-FID and the SFC techniques.
Figure 1. Full range gasoil hydroprocessing monitoring. Conversion of heavy ends (343 °C+) to lighter products and abundance of fractions 343 °C+ indicated. Selected samples identified with solid arrows were characterized in detail, while the sample shown with the empty arrow was physically distilled into preparative cuts.
2.2. Gas Chromatography with Flame Ionization (FID) and Mass Spectrometry (MS) Detection. An Agilent 7890 gas chromatograph provided with FID detection and a 5975 XL EI/CI Inert MSD mass detector was used for both simulated distillation and hydrocarbon class-type analysis. The FID detector response was set to 1 for all hydrocarbon types. The EI (electron impact ionization) was set up at 70 eV for the present study. One capillary column 5 m × 0.53 mm i.d. × 0.1 μm (PDMS) was used. The effluent from the column was split into the two detectors via an Agilent two-way microfluidic splitter (Agilent G3180B). Operation of the splitter has been presented elsewhere.20 Near column injection was achieved with a Separation Systems temperature programmable inlet. The injector operated in the oven-track mode. Samples were diluted in CS2 (2% w/w) and 0.2 μL/run injected. The column oven was programmed from 40 to 380 °C at 10 °C/min, then held for 12 min. The helium carrier flow rate was set up to 12 mL/min. Simulated distillation calculations were performed according to ASTM D72135 as well as D7500, using SimDist Expert version 9 software from Separation Systems. Aromatic and Saturate Analysis (ASA) software from Separation Systems was employed for HC-class-type analysis. ASA software calculations were based on a previous method published by C. J. Robinson.14 2.3. Supercritical Fluid Chromatography (SFC). SFC was carried out with a Selerity Technologies Inc. model 4000 chromatograph. Chromatographic grade CO2 was used as the eluent. The setup chromatographic conditions were 200 atm and 40 °C, allowing a flow-rate of about 100 μL/min. A silicagel packed column 1 mm i.d. × 50 cm length was used. Sample volumes of 0.2 μL were used. Setup conditions for the FID detector were 400 °C, air (50 atm) and H2 (20 atm). ASTM D5186 methodology was followed for setting up the analysis protocol and reporting results.25 2.4. Thin Layer Chromatography-Flame Ionization Detection (TLC-FID). A model MK-6 Iatroscan instrument provided with a “Peak Simple” chromatographic data system was used for this study. S-III silica chromarods were used for analyses. The rods were preactivated by burning at least twice before sample spotting and development. A volume of 1 μL of sample solution prepared in toluene/chloroform 1/1 v/v (10 mg/mL) was manually spotted over the chromarods in order to perform the SAR analyses. Saturates were eluted with n-heptane developed to
2. EXPERIMENTAL SECTION 2.1. Samples. Five sets of samples were studied, comprising light gasoils (LGO), vacuum gasoils (VGO), light cycle oils (LCO), hydroprocessed gasoils (HP-GO), and distillation cuts isolated from one selected HP product. The studied samples do not contain asphaltenes; some of their properties are included in Table 1 and, will be discussed in detail within the Results and Discussion section. 2249
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Table 1. Properties Determined for the Studied Samples T (°C) for %offc
sample type heavy gasoils
light gasoils light cycle oils
hydroprocess. distill. cuts
hydroprocess. full gasoils
sample identification
MWb (amu)
5
50
LMH VGOa C.200-400Ca C.400-530Ca AT 250-516Ca AB300−450Ca AB300-580Ca HVGOh VGO A VGO B VGO C VGO D DF20606i LGO ULS LCOj LS LCOj HS LCOj LCO HP LCOk HP product HPIP-235Cm HP235-280C HP280-343C HP343C+ feedstock HP 22% conv. HP 40% conv. HP 50% conv.
368 276 438 357 309 361 637 385 357 377 371 205 244 213 211 239 211 215 292 140 207 257 411 349 290 262 219
283 263 386 278 333 342 478 279 267 265 268 174 200 200 174 189 180 175 123 74 237 287 363 177 125 101 104
403 333 452 398 361 388 548 413 394 403 399 256 307 263 252 299 255 267 336 175 265 319 430 392 333 300 242
95
S ppm wt
N ppm wt
ηd @ 25 °C (cP)
522 414 532 510 417 512 615 543 518 546 539 345 383 363 381 388 363 364 505 234 288 351 531 533 505 495 467
38 120 5 334 10 320 30 852 1 281 6 507 −n 5 477 951 5 272 973 −n −n
