U.S. patent application number 13/167816 was filed with the patent office on 2012-06-21 for generation of model-of-composition of petroleum by high resolution mass spectrometry and associated analytics.
This patent application is currently assigned to EXXONMOBIL RESEARCH AND ENGINEERING COMPANY. Invention is credited to Kathleen E. Edwards, Anthony S. Mennito, Kuangnan Qian, Roland B. Saeger.
Application Number | 20120153139 13/167816 |
Document ID | / |
Family ID | 46233134 |
Filed Date | 2012-06-21 |
United States Patent
Application |
20120153139 |
Kind Code |
A1 |
Qian; Kuangnan ; et
al. |
June 21, 2012 |
GENERATION OF MODEL-OF-COMPOSITION OF PETROLEUM BY HIGH RESOLUTION
MASS SPECTROMETRY AND ASSOCIATED ANALYTICS
Abstract
A method to determine the model-of-composition of a vacuum resid
wherein the resid is separated into eight fractions, saturates,
aromatics, sulfides and polars by a combination of soft ionization
methods.
Inventors: |
Qian; Kuangnan; (Skillman,
NJ) ; Edwards; Kathleen E.; (Freehold, NJ) ;
Mennito; Anthony S.; (Flemington, NJ) ; Saeger;
Roland B.; (Runnemede, NJ) |
Assignee: |
EXXONMOBIL RESEARCH AND ENGINEERING
COMPANY
Annandale
NJ
|
Family ID: |
46233134 |
Appl. No.: |
13/167816 |
Filed: |
June 24, 2011 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61423797 |
Dec 16, 2010 |
|
|
|
Current U.S.
Class: |
250/282 |
Current CPC
Class: |
G01N 33/2835 20130101;
H01J 49/0027 20130101 |
Class at
Publication: |
250/282 |
International
Class: |
H01J 49/26 20060101
H01J049/26 |
Claims
1. A method to determine the model-of-composition of a heavy
petroleum or hydrocarbon samples comprising a. obtaining molecular
ions or pseudo molecular ions, such as protonated ions,
deprotonated ions, cation or anion adduct of parent molecule of
said heavy petroleum or hydrocarbon sample by soft ionization
method; b. determining elemental formula of said molecular ions or
pseudo molecular ions and quantifying corresponding concentrations
using high resolution mass spectrometry; and c. reconciling the
output from step (b) with other analytical measurements that
determine hydrocarbon and petroleum properties to obtain a
model-of-composition.
2. The method of claim 1 wherein said heavy petroleums or
hydrocarbon samples are separated into asphaltenes and deasphalted
oils (DAO).
3. The method of claim 2 wherein said DAO are separated into
chemical meaningful classes including saturates, aromatics,
sulfides and polars to improve certainty in assigning chemical
structures to the molecular formulas obtained by mass
spectrometry.
4. The method of claim 3 wherein said aromatics are separated into
aromatic ring class fractions including 1-ring aromatics (ARC1),
2-ring aromatics (ARC2), 3-ring aromatics (ARC3),4-ring+ aromatics
(ARC4+) to improve certainty in assigning chemical structures to
the molecular formulas obtained by mass spectrometry.
5. The method of claim 1 wherein said heavy petroleums or
hydrocarbon samples are separated by on-line chromatography-high
resolution mass spectrometry.
6. The method of claim 1 wherein ionization is performed by one or
multiple ionization methods with or without chromatographic
separation.
7. The method of claim 1 wherein said ionization step is a soft
ionization where molecular ion or pseudo molecular ion structures
remain intact after ionization.
8. The method of claim 1 wherein said ionization step is performed
by electrospray ionization.
9. The method of claim 1 wherein said ionization step is performed
by atmospheric pressure chemical ionization.
10. The method of claim 1 wherein said ionization step is performed
by atmospheric pressure photoionization (or photon ionization).
11. The method of claim 1 wherein said ionization step is performed
by matrix assisted laser desorption ionization.
12. The method of claim 1 wherein said ionization step is performed
by direct laser desorption ionization.
13. The method of claim 1 wherein said ionization step is performed
by field desorption ionization.
14. The method of claim 1 wherein high resolution is defined as
M/.DELTA.M.sub.FWHM>10,000.
15. The method of claim 1 wherein average resolution is preferred
to be greater than 100,000.
16. The method of claim 1 wherein average resolution is preferred
to be greater than 300,000.
17. The method of claim 1 wherein average resolution is preferred
to be greater than 500,000.
18. The method of claim 1 wherein heavy petroleum and hydrocarbon
sample is a vacuum gas oil, vacuum resid or petroleum products of
similar boiling point range.
19. The method of claim 1 wherein said reconsolidation step uses
lumps to normalize concentrations.
20. The method of claim 1 wherein said reconciliation step use bulk
elemental properties include: hydrogen, sulfur, nitrogen, nickel
and vanadium content.
21. The method of claim 1 wherein said reconciliation step use bulk
composition and structural properties include: % Aromatic carbon
(Ca), Average aromatic cluster size (C#), Amount of C in long
chains, Degree of chain branching, organic forms of sulfur,
pyrrolic, pyridinic and quaternary nitrogens.
22. The method of claim 1 wherein said reconciliation step use
molecular properties include: MCR (or CCR) content, molecular
weight distribution by FDMS and boiling point distribution by
SIMDIS.
Description
[0001] This is a Non-Provisional Application based on Provisional
Application 61/423,797 filed Dec. 16, 2010.
BACKGROUND OF THE INVENTION
[0002] The present invention is a method to determine a
model-of-composition for petroleum and petroleum related products.
In particular the petroleum is a vacuum resid (VR) or vacuum gas
oil (VGO) or petroleum with a similar boiling point range.
[0003] A vacuum gas oil is a crude oil fraction that boils between
about 343.degree. C. to 537.degree. C. A vacuum residuum is a
residuum obtained by vacuum distillation of a crude oil and boils
above a temperature about 537.degree. C.
[0004] Petroleum samples are complicated hydrocarbon mixtures
containing paraffins, cyclic paraffins, multiring aromatics, and
various heteroatomic hydrocarbons (most commonly O, S, and N).
Virgin petroleum crude oils contain molecules of a wide boiling
point range from highly volatile C.sub.4 hydrocarbons to
nonvolatile asphaltenes. Analysis of petroleum composition of
various boiling ranges is necessary for inputs to many subsequent
processes.
SUMMARY OF THE INVENTION
[0005] Petroleum streams are complex mixtures of hydrocarbons
containing enormous numbers of distinct molecular species. These
streams include any hydrocarbon stream from processes that change
petroleum's molecular composition. The streams are so complex, and
have so many distinct molecular species that any molecular
approximation of the composition is essentially a model, that is, a
model-of-composition (MoC).
[0006] Petroleum oils and high-boiling petroleum oil fractions are
composed of many members of a relatively few homologous series of
hydrocarbons (6). The composition of the total mixture, in terms of
elementary composition, does not vary a great deal, but small
differences in composition can greatly affect the physical
properties and the processing required to produce salable products.
Petroleum is essentially a mixture of hydrocarbons, and even the
non-hydrocarbon elements are generally present as components of
complex molecules predominantly hydrocarbon in character, but
containing small quantities of oxygen, sulfur, nitrogen, vanadium,
nickel, and chromium. Therefore, in the present invention petroleum
and hydrocarbon will be used interchangeably.
[0007] The present invention is a method to determine the
model-of-composition of a heavy petroleum or hydrocarbon sample.
The method includes the steps of obtaining molecular ions or pseudo
molecular ions of the sample by soft ionization, determining
molecular ion formulas and quantifying corresponding concentrations
and then reconciling this quantification with other analytical
measurements to obtain a model-of-composition.
[0008] In a preferred embodiment, one or multiple soft ionization
methods are used to generate molecular ions or pseudo molecular
ions for petroleum molecules of different polarities and
classes.
[0009] Pseudo molecular ions include protonated ions, deprotonated
ions, cation or anion adduct of parent molecule of the heavy
petroleum or hydrocarbon sample.
[0010] In a preferred embodiment, elemental formulas and
concentrations of molecular ions or pseudo molecular ions are
determined by high resolution mass spectrometry
[0011] In a preferred embodiment, the petroleum are separated into
asphaltenes and deasphalted oils (DAO) before mass spectrometric
analysis. A deasphalted oil remains after the asphaltene fraction
is removed by the addition of a low boiling hydrocarbon liquid such
as n-pentane or n-heptane.
[0012] In a preferred embodiment, the DAO are separated into
saturates, aromatics, sulfides, and polars before mass
spectrometric analysis.
[0013] In a preferred embodiment, aromatics are separated into
aromatic ring classes (ARC), 1--Ring Aromatics (ARC1), 2--Ring
Aromatics (ARC2), 3--Ring Aromatics (ARC3), and 4--Ring Aromatics
Plus (ARC4+) before mass spectrometric analysis.
[0014] In another embodiment, the petroleums are separated and
analyzed by on-line separation mass spectrometry.
[0015] In a preferred embodiment, the petroleum sample is a vacuum
resid or a sample that boils above about 1000.degree. F.
[0016] In another embodiment, the petroleum sample is a vacuum gas
oil or a sample that boils between about 650.degree. F. to
1000.degree. F.
BRIEF DESCRIPTION OF THE FIGURES
[0017] FIG. 1 shows the separation of two vacuum resids into eight
composition lumps.
[0018] FIG. 2 shows the use of multiple ionization methods to
generate molecular ions or pseudo molecular ions of different
petroleum classes. Analyses were done without chromatographic
separations.
[0019] FIG. 3 shows the ionization of aromatic ring classes by
Atmospheric Pressure Photoionization (APPI) for Cold Lake VR ARC
fractions (a) full range (b) M/Z of 688.
[0020] FIG. 4 shows the ionization of 1250.degree. F.+ molecules
asphaltenes and deasphalted oil (DAO) by laser desorption.
Molecular weight species beyond 1500 g/mol are new species that
cannot be volatized by APPI.
[0021] FIG. 5 shows the ionization of saturate molecules by field
desorption.
[0022] FIG. 6 shows the ultra-high mass resolving power by Fourier
transform ion cyclotron resonance mass spectrometry (FTICR-MS)
needed to resolve petroleum molecules.
[0023] FIG. 7 shows the assignments of molecular formulas for an
asphaltene sample.
[0024] FIG. 8 shows the layers of chemical information provided by
FT ICR-MS.
[0025] FIG. 9 shows the reconciliation of the chemical distribution
with the advanced analytical protocol.
[0026] FIG. 10 shows APPI ionizations.
[0027] FIG. 11 shows the effect of nebulizer and capillary
temperature.
[0028] FIG. 12 shows APPI of asphatenes at 350 F and 450 F
nebulizer temperatures.
[0029] FIG. 13 shows solvent effect on ESI.
[0030] FIG. 14 shows the effect of accumulation time on dimers in
ESI.
[0031] FIG. 15 shows the heteroatom classes of Cold Lake VR
Aromatic Ring Class (ARC) fractions.
[0032] FIG. 16 shows a comparison of HC Z-number distribution
between VR and VGO.
[0033] FIG. 17 shows Z-number and molecular weight distributions in
Cold Lake aromatic ring fractions.
[0034] FIG. 18 shows the summary of sulfide species in Cold
Lake.
[0035] FIG. 19 shows Z-number distribution of sulfide
molecules.
[0036] FIG. 20 shows the VR basic and acidic compound classes.
[0037] FIG. 21 shows Z-number and molecular weight distributions of
bases and acids in DOBA VR.
[0038] FIG. 22 shows compound classes in Cold Lake VR
asphaltenes.
[0039] FIG. 23 shows Z-number and molecular weight distribution of
Cold Lake asphaltene molecules.
[0040] FIG. 24 shows an example of on-line chromatography mass
spectrometry configuration. ELSD: Evaporative Light Scattering
Detector
[0041] FIG. 25 shows HPLC-FTICR-MS Chromatogram and Average Mass
Spectra
[0042] FIG. 26 shows Comparison of Results from HPLC-ELSD and
HPLC-FTICR MS Using APPI
DESCRIPTION OF THE PREFERRED EMBODIMENT
[0043] The present invention is a method to generate a
model-of-composition for petroleum and petroleum related products
using high resolution mass spectrometry and associated analytical
techniques.
[0044] Petroleum samples are analyzed by high resolution mass
spectrometry (HRMS) to resolve or partially resolve nominal mass
overlap in the samples. Mass resolution here is defined as
R=M/.DELTA.M.sub.FWHM where/.DELTA.M.sub.FWHM is defined as mass
peak width at 50% peak height. Mass resolving power (RP) and mass
resolution are used interchangeably in this work. A minimum of
10,000 mass resolution is needed to resolve important overlaps
including 12H.about.C doublet as listed in Table 1. In this work,
data are collected in a broadband acquisition mode (a mass range of
100 to 3000 Da). Preferably, Fourier transform ion cyclotron
resonance mass spectrometry (FTICR-MS) with an average mass
resolving power (RP>300K) is utilized for the analysis. Samples
may be analyzed directly or after separation by off-line or on-line
chromatography, or solubility fractionation. Petroleum samples or
fractions are ionized by one or combined soft ionization methods to
generate molecular ions or pseudo-molecular ions that are
representing different classes of petroleum molecules. Empirical
formula can be determined without ambiguity within the accuracy of
mass analysis window and restrictions of heteroatom combinations.
Chromatographic separation may be used to generate petroleum lumps
with different aromatic ring structures and/or chemical moieties.
The separation also enhances dynamic range of the HRMS analysis.
Molecular structure assignments are made based on empirical formula
and aromatic ring classes. Quantitations are made by normalizing
total components to the HPLC lumps. At the end, composition may be
reconciled so that average composition and properties are
consistent with that measured by bulk measurement technologies,
such as NMR and elemental analysis.
[0045] In the past, a magnetic sector mass spectrometer was
commonly used to determine petroleum composition. For example, MS50
has been the workhorse in the High Detail Hydrocarbon Analysis
(HDHA) protocol. In general, a sector MS provides limited mass
resolution. 10K to 50K can be normally achieved when used electron
ionization (EI) mode and 1K to 5K when used in Field Ionization
(FI) mode. More recently time of flight (TOF) mass spectrometer
with RP around 5K has been used to determine petroleum
compositions. EI produce too much fragmentation during the
ionization process and cannot be used to determine molecular ion
composition. The low mass resolution in FI mode prohibits
resolutions of many overlapping masses in petroleum. Consequently,
it is hard to make unique assignments of molecular formula for the
molecular ions. Chromatographic (HPLC or GC) separations are
necessary to assist mass spectrometry characterization. Although
successful applications have been demonstrated and applied to
petroleum analysis, the upper boiling point limit of these
analytical protocols are typically below 1000.degree. F. (VGO or
below). Even in this boiling range, there are still many
ambiguities in formula and structure assignments. There is no
method for petroleum that boils above 1000.degree. F. The
technology described here filled the gap in petroleum vacuum resid
characterization. With FTICR-MS and use of multiple ionization
methods, we are able to develop a model-of-composition for
petroleum vacuum resid.
[0046] The overall method is to use a combination soft ionization
methods to generate molecular ions or pseudo molecular ions for
petroleum molecules of different polarities and classes. Pseudo
molecular ions are defined as protonated or deprotonated molecular
ions, cation or anion adduts of molecular ions. FTICR-MS resolves
and determines masses with high accuracy (error<0.2 ppm).
Concentrations of the masses are determined by the signal magnitude
of corresponding masses. Empirical formulas were assigned based on
the accurate masses and restrictions of heteroatom combinations.
Chromatographic separations may be used to increase dynamic range,
assist quantification and structure assignments. Reconciliation may
be conducted to match the average composition with that determined
via bulk measurements.
[0047] The following is a typical work process to generate a
model-of-composition for petroleum using high resolution mass
spectrometry [0048] 1. Separations of petroleum molecules into like
species or molecular lumps, such as [0049] a. Deasphalted oil (DAO)
and asphaltenes [0050] b. Saturates, aromatics, sulfides and polars
[0051] c. Aromatic ring classes [0052] 2. Generation of molecular
ions or pseudo molecular ions [0053] a. Use of field
desorption/field ionization to ionize saturate molecules [0054] b.
Use of APPI/APCI to ionize aromatic petroleum molecules. [0055] c.
Use of positive ion ESI (PEST) to ionize basic nitrogen molecules
[0056] d. Use of negative ion ESI (NESI) to ionize acidic molecules
[0057] e. Use of laser desorption ionization or matrix assisted
laser desorption to ionize high boiling molecules (molecules boils
above 1300 F). [0058] 3. Determination of compound class, Z
distribution, carbon number distribution and stoichiometry of
molecules by FTICR-MS [0059] a. Resolve all mass peaks [0060] b.
Accurate mass analysis of molecular ions or pseudo molecular ions
by conducting external and internal calibration [0061] c. Assign
molecular formulas to the masses above a defined signal to noise
threshold using a mass tolerance of 0.6 mDa. Only C, H, N, S, O, Ni
and V are allowed. Maximum number of N, S, O are limited to 4.
Maximum number of Ni and V are limited to 1. [0062] d. Determine
abundances of molecules based on FTICR-MS signal magnetude of the
corresponding molecule ions or pseudo molecule ions [0063] e. Group
molecules and their abundances by heteroatom contents, homologous
series (Z-number) and molecular weights [0064] 4. Assemble full
composition by combining compositions from various molecular lumps
and ionization methods [0065] 5. Reconcile with other analytical
data, such as [0066] a. Field Desorption MS for Molecular Weight
(MW) distribution [0067] b. Bulk Properties [0068] i. Elementals
[0069] ii. High temperature simulated distillation (HT-SIMDIS)
[0070] iii. Microcarbon residue (MCR) or conradison carbon (CCR)
Residue [0071] c. Average structures by NMR [0072] i. % Aromatic
carbon (Ca) [0073] ii. Average aromatic cluster size (C#) [0074]
iii. Amount of C in long chains [0075] iv. Degree of chain
branching [0076] d. Heteroatom types by X-ray Photoelectron
Spectroscopy (XPS) [0077] i. Organic forms of sulfur [0078] ii.
Pyrrolic, pyridinic and quaternary nitrogens Separations of
Petroleum Molecules into Like Species
[0079] Although petroleum samples can be analyzed directly by
FTICR-MS to generate a composition, separation of petroleums into
like species helps to improve dynamic range of mass analysis,
facilitate quantitation and structural assignments. For vacuum
resid, deasphalt is normally the first step before further
chromatographic separation. HPLC can separate petroleum into
saturates, aromatics, sulfides and polars. Aromatics may be further
divided into ring classes. FIG. 1 shows the separation of two
vacuum resid into eight composition lumps. Deasphalt and HPLC
separations can be performed off-line or on-line with FTICR-MS.
Generation of Molecular Ions or Pseudo Molecular Ions
[0080] Soft ionization methods are used to generate molecular ions
or pseudo molecular ions. Commonly used ionization methods include
but not limited to Electrospray Ionization (ESI), Atmospheric
Pressure Chemical Ionization (APCI), Atmospheric Pressure
Photoionization (APPI), Matrix Assisted Laser Desorption Ionization
(MALDI) and direct laser ionization (LDI). Ionizations can be
operated in both positive and negative ion mode. Among those
ionization techniques, APPI and ESI were found to be most useful
and are extensively explored in this work. APPI ionizes both
aromatic and polar aromatic molecules mostly via charge transfer
reactions (minor protonations have also been observed). However, it
does not ionize saturate structures (especially paraffinic
structures) due to high ionization potentials of analyte molecules.
Saturate molecules can be ionized by field desorption or field
ionization. APCI produces similar products as in APPI. MALDI and
LDI can ionize high molecular weight and high boiling molecules
(e.g. 704.degree. C.+). Compositions from various ionization
methods can be combined.
[0081] FIG. 2 shows the use of multiple ionization method to
generate molecular ions for neutrals, bases and acids by APPI, PESI
and NESI, respectively. FIG. 3 shows the ionization of aromatic
ring classes by APPI. FIG. 4 shows ionization of 677.degree. C.+
molecules by laser desorption ionization mass spectrometry. FIG. 5
shows ionization of saturate molecules by field desorption
ionization
Determine Compound Classes, Z Distribution, Total Carbon Number
Distribution and Stoichiometry of Molecules by FTICR-MS
[0082] FTICR-MS provides accurate mass analysis of petroleum of a
wide molecular weight range. Internal calibration using sample
peaks are normally performed. Mass accuracy of 0.2 ppm can be
achieved after internal calibration. An average mass resolving
power greater than 300,000 is necessary to resolve petroleum
molecules. FIG. 6 demonstrated ultra-high mass resolving power
(>500,000) over a wide mass range (200-1200 Da) achieved by
FTICR-MS. FIG. 7 shows assignments of molecular formula for an
asphaltene samples with error less than 0.2 mDa.
[0083] FTICR MS provides three layers of chemical information for a
petroleum system as shown in FIG. 8. The first level is
heteroatomic classes (or compound classes), such as hydrocarbons
(HC), 1 sulfur molecules (1S), 1 nitrogen molecules (1N), 2 oxygen
molecules (2O), 1 nitrogen 1 oxygen molecules (1N1O), etc. The
second level is Z-number distribution (or homologous series
distribution) within each compound class. Z is defined as hydrogen
deficiency as in general chemical formula,
C.sub.cH.sub.2c+ZN.sub.nS.sub.sO.sub.o. The more negative the
Z-number, the more unsaturated the molecules. The third level of
information is the total carbon number distribution or molecular
weight distribution of each homologue. If compound core structure
is known, total alkyl sidechain information can be derived by
subtracting carbon number of cores.
Assemble-Full Composition by Combining Compositions from Various
Molecular Lumps and Ionization Methods
[0084] Molecular composition of petroleum is too complex to be
determined adequately by a single FTICR MS analysis. Instead, a
petroleum sample is subjected to an advanced analytical protocol
that includes multiple steps and analyses (see schematic in FIG.
9). If the sample's initial boiling point is at or above
1000.degree. F., asphaltenes are separated from the sample first.
The deasphalted oil (DAO), is further separated using a
high-performance liquid-chromatographic (HPLC) technique. The
fractions that elute from this HPLC technique include: saturates,
aromatic-ring classes (ARC) 1-4, sulfides, and polars. Each of
these fractions, including asphaltenes, are analyzed by a variety
of techniques, including: FTICR MS, field-desorption mass
spectrometry (FDMS), nuclear magnetic resonance (NMR), elemental
analysis, and other bulk properties, APPI FTICR MS is used to
estimate the distribution of chemical formulae within the ARC1-4,
sulfides, and asphaltene fractions. The molecular composition of
the polar fraction is known to be dominated by molecules containing
basic nitrogen, and containing organic acid groups. Here, the
distribution of chemical formulae is estimated by analyzing the DAO
by NESI (negative ion ESI) FTICR MS, and by PESI (positive ion ESI)
FTICR MS, then superimposing the two analyses.
Reconcile/Leverage with Other Analyticals
[0085] The chemical formulae distribution determined by FTICR MS
analysis of the separated fractions detailed above must be
reconciled to all analyses within the advanced analytical protocol
shown in FIG. 9. Each fraction's FTICR MS analysis must be
extrapolated to higher molecular weights, and lower hydrogen
deficiency classes (Z-number), to match the molecular weight
distribution predicted by FDMS analysis. The total abundance of
elements in each fraction, e.g. carbon, hydrogen, sulfur, nitrogen,
oxygen, nickel, and vanadium, as predicted from the FTICR
MS-derived chemical formulae must be reconciled to that measured by
elemental analysis. This reconciliation is done using the
constrained entropy maximization procedure. Reconciliation to
high-temperature is feasible through use of appropriate property
targets in the above procedure, and through the use of a
correlation that relates boiling point temperatures to chemical
formulae. Assignment of molecular (e.g. structure oriented lumping
(SOL)) lumps to each chemical formula is aided by other measured
properties, e.g. microcarbon residue, NMR, and heteroatom types
identified by X-ray Photoelectron Spectroscopy (XPS).
[0086] Appendix I provides more details on the determination of
heavy petroleum composition using multiple ionization methods and
Fourier transform ion cyclotron resonance mass spectrometry.
[0087] Appendix II provides more details on the molecular formula
distributions of vacuum resid reconciled to the heavy hydrocarbon
model-of-composition analytic protocol.
APPENDIX I
Determination of Heavy Petroleum Composition Using Multiple
Ionization Methods and Fourier Transform Ion Cyclotron Resonance
Mass Spectrometry
Introduction
[0088] The primary goal of this research is to establish the next
generation mass spectrometry platform for molecular
characterization of heavy hydrocarbons with boiling points greater
than 1000.degree. F. These hydrocarbon molecules are often referred
as the "bottoms of the barrel" as they cannot distill via
conventional vacuum distillation tower. A more common name of this
non-distillable fraction is called vacuum residua or vacuum resid
(VR). Relative to a vacuum gas oils (VGO), VR exhibits very
different chemical and physical characteristics. They present much
higher analytical challenges, especially in the area of molecular
level characterization. The first challenge is their high boiling
points and high molecular weights. Nominally, the boiling points of
VR molecules are above 1000.degree. F. and molecular weights range
from 300 Da to 2000 Da (versus 100 to 800 Da of VGO). The high
molecular weights of VR arise from both alkyl chain extension (CH2
increments) and poly aromatic ring growth. Traditional thermal
vaporization and ionization methods are inefficient to convert VR
molecules into intact molecular ions for detection. The second
challenge is their low solubility. VR typically contain asphaltenes
(defined as n-heptane insolubles in this work). The range of
asphaltenes content is from 0 to 40%. The low solubility and high
asphaltenes contents are largely arising from its rich heteroatom
content (NSO) and low H/C ratio. The third challenge is the huge
number of molecules in VR (50 to 100 times more than that in VGO in
terms of mass distinguishable species) and significant increases in
NSO and metal contributions. Mass spectrometry performance needs to
be maximized in terms of mass resolution, mass accuracy and dynamic
range to account for all molecules in VR. Finally, VR molecules are
likely to contain multi-core structures (versus mostly single cores
in VGO), making structure assignment difficult.
[0089] Mass spectrometric characterization of hydrocarbons has been
the subject of research for over the past six decades. In the past,
a sector mass spectrometer has been the major work horse for
providing molecular information. In general, a sector MS provides a
dynamic resolution (at mass of 100 Da) ranging from 10K to 50K when
combined with electron ionization technology and 1K to 5K when used
in Field Ionization (FI) mode. Its resolution decreases rapidly as
molecular weight increases. FTICR-MS provides a quantum leap in the
mass resolution and mass accuracy. For example, a 12 tesla FTICR-MS
can easily obtain a mass resolution of 350K at a mass of 500 Da.
Its mass accuracy can tell the mass difference of one electron
(0.54 mDa). This capability enables resolution of almost all
hydrocarbon nominal mass overlaps (Table 1) across entire mass
range of interests. As stated before, the primary challenge in
FTICR-MS applications for heavy petroleum characterization are the
effective volatization and ionization of the high boiling and low
solubility molecules. In addition, effective and non-bias
transmission of ions from the ion source into the FTICR cell is
also critical to the quantification aspect of the technique.
[0090] The overall strategy of our characterization is to leverage
chromatographic separations to improve FTICR-MS in terms of dynamic
range, quantification and structure assignments. This report will
discuss APPI ionization of model compounds, aromatic ring class
fractions, sulfides and asphaltenes. We will also discuss ESI
ionization of polar molecules.
Experimental
Instruments
[0091] Bruker APEX-Qe is a hybrid quadrupole-FTICR MS with a 12
tesla actively shielded superconducting magnet. The instrument
combines the power of ultra-high resolution FTICR with a linear
hexapole-quadrupole-hexapole (hQh) ion trap technology. The hQh ion
trap serves multiple purposes. First it allows efficient cooling
and homogenization of ion kinetic energy (in the 1st hexapole) so
that the ions entering ICR cell have similar linear velocity which
is very critical for ultra-high resolution and ultra-high accuracy
mass measurements. Secondly, ions can be purified or concentrated
by the quadrupole mass analyzer for subsequent fragmentation (in
the second hexapole) and ultra-high resolution analysis (in the
FTICR cell). The fragmentation capability enables determination of
heavy petroleum multi-core structures.
APPI Conditions and Sample Preparations
[0092] About 4 mg of petroleum sample are dissolved in 20 ml of
toluene to form a 200 ppm solution. The solution was introduced
into the APPI source using a Cole-Palmer syringe pump and a 250
.mu.l syringe. The flow rate is normally controlled at 120
.mu.l/hour. The source was manufactured by Syagen and comprised of
a heated capillary needle and Krypton UV lamp with ionization
energy of 10.6 eV. Nitrogen is used for both nebulizing gas and
drying gas. Nebulizing gas flow rate is normally between 1 to 3
L/min while drying gas flow rate is normally between 2 to 7 L/min.
The flow rates are adjusted to maximize APPI-FTICR signals.
Nebulizing gas temperature varies from 350.degree. C. to
450.degree. C. For VR, 450.degree. C. has been generally adopted to
maximize the signal of high boiling molecules. Toluene is used as
both solvent and chemical ionization agent. We did not observe any
thermal chemistry in APPI. This is mainly due to the short
residence time of the sample ions.
ESI Conditions and Sample Preparations
[0093] Optimal sample concentrations depend on nitrogen and acid
levels. In positive ion ESI, .about.20 mg of VR sample is first
dissolved in 20 ml toluene. 3 ml of the solution is diluted with 17
ml of a toluene/ACN mixture (15% toluene). The final analyte
concentration is about 150 ppm. The final toluene concentration is
about 30%. 20 to 100 ul of formic acid was added to the solution to
promote liquid conductivity. The desired electrospray current is
greater than 10 uA to maintain spray stability. In negative ion
mode, .about.20 mg of VR sample is first dissolved in 20 ml
toluene. 3 ml of the solution is diluted with 17 ml of
toluene/methanol mixture (15% toluene). The final sample
concentration is 150 ppm. 20 to 100 ul of NH4OH is added to promote
liquid conductivity and achieve desired electrospray current of
>10 uA. The liquid sample is delivered into ESI source by a
syringe pump with a flow rate of 120 ul/hour. Nitrogen is used for
both nebulizing and dryer gases. The nebulizing temperature is at
ambient and the drying gas temperature is set at 200.degree. C.
Samples
[0094] Samples analyzed in this report are derived from a series of
deasphalt and HPLC separations. Deasphalt process has been
previously described.sup.1, which divides VR into asphaltenes and
deasphalted oils (DAO). HPLC separation further divides DAO into
aromatic ring classes (1 to 3 ring and 4-ring+), sulfides and
polars.sup.2,3.
Data Analysis and Integration
[0095] In FTICR MS, the excited cyclotron motion of the ions is
detected on receiver plates as a time domain signal that contains
all the cyclotron frequencies that have been excited. Fourier
transformation of the time domain signal results in the frequency
domain signal that can be converted into a mass spectrum. In this
work, the mass range was set at m/z 300 to 3000. The dataset size
is set to 4 Megawords. Ion accumulation time is 0.5 to 2 sec. 1000
data sets were co-added to generate the final spectrum. Bruker Data
Analysis (DA) software is used to find the mass peak list with
signal-to-noise ratio (S/N) greater than 6. The mass peak list is
further analyzed for identification of hydrocarbon molecules.
External mass calibration was performed using a blend of eight
in-house synthesized aromatic compounds covering a mass range from
.about.350 to 1800 Da. In general, 2 ppm mass accuracy can be
achieved with external calibration. Bruker DA molecular formula
tool assisted in identifying major homologous series. Internal
calibration was then performed using the identified homologous
series. On average, .about.0.2 ppm mass accuracy can be achieved
with internal mass calibration.
[0096] Mass peak list containing columns of exact masses, signal
magnitudes, mass resolving powers and signal-to-noise ratios were
further processed to generate elemental formula
(C.sub.cH.sub.2c+ZN.sub.nS.sub.sO.sub.o). Data are organized into
heteroatom classes and homologous series.
Results and Discussions
Soft Ionizations of Heavy Petroleum Molecules
[0097] Apex-Qe FTICR MS is equipped with multiple ionization
techniques, Electrospray Ionization (ESI), Atmospheric Pressure
Chemical Ionization (APCI), Atmospheric Pressure Photoionization
(APPI) and Matrix Assisted Laser Desorption Ionization (MALDI).
Among those ionization techniques, APPI and ESI were found to be
most useful and are extensively explored in this work. APPI ionizes
both aromatic and polar aromatic molecules mostly via charge
transfer reactions (minor protonations have also been observed).
However, it does not ionize saturate structures due to their high
ionization potentials. ESI has been extensively explored for polar
characterization. APCI produces more complex ionization products
for petroleum (including extensive protonation and charge
transfer). MALDI and Laser Desorption Ionization (LDI) have shown
potential for ionizing high molecular weight polymers, asphaltenes
and waxes.
Ionization of Aromatic Molecules by APPI
[0098] FIG. 10 demonstrates the basic principles of APPI. The
sample solution is dispersed into fine droplets and vaporized by
co-spraying with a nebulizing gas through a heated stainless
needle. The sample molecules are further desolvated by a counter
flow of drying gas. The gas phase solvent and analyte molecules are
ionized via UV photoionization. Since analyte molecules are present
in a much lower level (200 ppm), the gas phase contains primarily
solvent molecules. Consequently, direct photoionization produces
mostly solvent molecule ions and very few analyte ions. The latter
are mostly ionized by secondary ion-molecule reactions in the
source region. In the current applications, toluene is used as
solvent as it can dissolve most of the sample types including
asphaltenes. Toluene has an ionization potential (IP) of 8.8 eV and
can be directly ionized by Krypton photon source (10.6 eV). On the
other hand, the IP of toluene is higher than that of all the
aromatic molecules except benzene as shown in Table 2. The toluene
molecular ions react with analyte molecules via ion-neutral
collisions. For most aromatic molecules, electron transfer will
take place as shown in Scheme I, resulting in the formation of
analyte radical molecular ions.
##STR00001##
[0099] The energy deposition of Scheme I is determined by the IP
differences between the analyte and toluene. For almost all
aromatic molecules, the energy deposition is sufficiently low that
analyte molecular ions are formed without fragmentation. This soft
ionization is important for VR analyses due to the complexity of
the sample compositions. Low levels of protonation have been
observed for low molecular weight polar molecules. Protonation can
be pronounced when more polar solvents (such as methanol and
acetonitrile) are used.
[0100] Sample volatilization in APPI is a combined nebulizing and
heating process. Nebulizing temperature has a large impact on the
volatilization. Once ions are formed, they are transported into the
source chamber for further manipulation via a heated capillary
tube. FIG. 11 shows the temperature effects of APPI. An Arab Heavy
distillate fraction (BP 1120-1305.degree. F. (604-707.degree. C.))
is analyzed by APPI-FTICR at different nebulizer (NEB) and
capillary (CAP) temperatures. Mass spectra show a large increase in
the higher mass intensity as nebulizing temperature is changed from
200.degree. C. to 350.degree. C. No change was found as the
temperature was further increased to 400.degree. C. The results
suggest that 350.degree. C. nebulizing temperature is sufficient to
volatize and ionize molecules with BP up to 1300.degree. F. MS
signals show no difference between 200.degree. C. and 300.degree.
C. capillary temperature, indicating that once ions are formed,
re-condensation will not occur during the time period of our
analysis.
[0101] When an n-heptane asphaltenes of Cold Lake VR (-50% of the
material boils above 1380.degree. F. (749.degree. C.) based on high
temperature simulated distillation) was subjected to the same
tests, we notice the need for much higher NEB temperature. FIG. 12
compares the mass spectra of a VR asphaltenes between 350.degree.
C. and 450.degree. C. NEB temperatures. Asphaltenes signals are
barely visible at 350.degree. C. and are very significant at
450.degree. C. Since the maximum NEB temperature is 500.degree. C.,
we have chosen 450.degree. C. as our default operation temperature
to avoid over heating the system and potential thermal
decomposition.
Ionization of Polar Molecules by ESI
[0102] ESI has been widely explored for ionization of petroleum
samples. It is also widely accepted that positive ion ESI (PESI)
selectively ionizes basic nitrogen compounds via protonation while
negative ion ESI (NEST) selectively ionizes acids, phenols and
non-basic nitrogen compounds via de-protonation. In ESI, a large
potential of approximately 2,000 to 4,000 V is applied to a
capillary needle through which a sample solution containing
electrolyte (e.g. formic acid for positive ion or NH.sub.4OH for
negative ion) are introduced. A counter electrode is maintained at
0 V, thus creating a strong electric field between it and the
capillary. The electric field permeates the solution at the
capillary needle tip and causes separation of the ions in solution.
In positive ion conditions, negative ions move toward the center of
the capillary whereas positive ions are enriched at the surface of
the liquid at the capillary tip. The repulsion of the excess
charges at the surface and the pull of the electric field form a
"Taylor cone" at the tip of capillary. As the charge repulsion
overcomes the surface tension of the liquid, a fine spray of
charged droplets is created. As those droplets pass through a
heated capillary within the mass spectrometer, the solvent
evaporates, increasing the surface charge density. Coulombic
repulsion causes droplets to fission into successively smaller
daughter droplets, resulting in the eventual removal of all solvent
molecules to yield unhydrated gas-phase ions (charge residual
model) or direct ejection of ions into gas phase (ion evaporation
model).
[0103] For ESI applications in petroleum, solvents are normally
binary mixtures containing both petroleum-friendly solvent and
ESI-friendly solvent, such as toluene/acetonitrile (positive ion
mode) or toluene/methanol (negative ion mode). For VGO samples,
toluene content can be as low as 5% without significant sample
precipitation. For VR DAOs and asphaltenes, we have observed large
solid precipitation using the conventional mix adopted for VGO
analysis. All VR samples are soluble in 100% toluene. However,
toluene does not spray under the ESI conditions. To obtain a steady
ESI current, a maximal 50% toluene may be used. FIG. 13 showed the
impact of toluene concentration on ESI responses of a Cold Lake VR
DAO. As toluene concentration decreases, total ESI signal
increases, particularly in the lower molecular weight region. The
responses of the higher molecular weight species is decreasing.
When we examine the detailed mass spectra (FIG. 13 (b)), it becomes
clear that more condensed aromatic nitrogens were not detected in
the case of 5% toluene, mostly likely due to the precipitation.
16.75% Toluene showed a broader mass distribution among the three.
Despite minor precipitation of this solvent condition, the spectra
showed overall better ESI performance. In our normal practice
toluene concentration is normally controlled between 15 to 25%.
[0104] A uniform response factor is assumed for ESI although we
realize there are significant variations in positive ion ESI
responses for various nitrogen compound types.sup.4. In negative
ion ESI of acids, the uniform response assumption is not far from
reality. Previous research has shown that TAN measurements based on
stearic acid match well with that of titration of total
acids.sup.5. Similar to APPI applications, FTICR is mainly used to
provide Z-distribution of homologues and heteroatom distribution of
polar species in petroleum samples. The nitrogen concentrations are
normalized to elemental nitrogen and acids are normalized to the
TAN measurements. In our research, positive and negative ion ESI
are used to detect bases and acids in VR. These molecules are used
to construct basic nitrogen and acid compositions.
[0105] ESI is a soft ionization method which is also known to
retain non-covalent structures in condensed phase. FIG. 14 shows an
example of formation of non-covalent dimers and effect of ion
accumulation on these dimers. The experiment is a positive ion ESI
of a Arab heavy distillate (975-1120.degree. F.). When accumulation
time is very short (<0.5 Sec), the presence of dimer ions are
evident. The increase of ion accumulation time in the hexapole ion
trap provides sufficient ion-neutral collisions to disrupt the
non-covalent interactions, even with very low ion kinetic energy
(near thermal velocity). In normal ESI operations, ion accumulation
time is typically maintained greater than 1 sec to reduce the
probability of non-covalent interactions.
Compound Classes, Z Distribution, Total Carbon Number Distribution
and Stoichiometry of Molecules
[0106] FTICR MS provides three layers of chemical information for a
petroleum system. The first level is heteroatomic classes (or
compound classes), such as hydrocarbons (HC), 1 sulfur molecules
(1S), 1 nitrogen molecules (1N), 2 oxygen molecules (2O), 1
nitrogen 1 oxygen molecules (1N1O), etc. The second level is
Z-number distribution (or homologous series distribution). Z is
defined as hydrogen deficiency as in general chemical formula,
C.sub.cH.sub.2c+ZN.sub.nS.sub.sO.sub.o. The more negative the
Z-number, the more unsaturated the molecules. Another commonly used
term is called double bond equivalent (DBE). For a typical
petroleum system, DBE=1-(Z-n)/2 where n is the number of nitrogen
atoms. The third level of information is the total carbon number
distribution or molecular weight distribution of each homologue. If
compound core structure is known, total alkyl sidechain information
can be derived by subtracting carbon number of cores.
Characterization of VR and Fractions
[0107] VRs are separated into eight fractions prior to MS
characterization. These are saturates, 1, 2, 3, and 4+ ring
aromatics, sulfides, polars and asphaltenes. Saturates are
characterized by Field Desorption ionization coupled with a
moderate resolution mass spectrometer. Positive and negative ion
ESI-FTICR analyses of DAO are used to re-construct polar
compositions.
Analyses of Aromatic Ring Class Fractions and Sulfides
[0108] APPI is used to ionize all aromatic ring class fractions and
sulfide fraction. APPI-FTICR mass spectra of Cold Lake aromatic
ring class fractions are shown in FIG. 3. M/z values of ARC 1 range
from 450 to 1300 while that of ARC 4 range from 400 to 1200.
Average MW decreases as ring class increases. This is mainly due to
boiling point effects. For a given boiling point, more condensed
aromatics have lower molecular weight. The fact that the upper mass
of ARC4+ in FIG. 3 is lower than that of ARC 1, indicates some high
molecular weight species in ARC4+ were not vaporized and ionized. A
detailed view (3(b)) of m/z 688 shows a mass distribution shift
toward the left side (more condensed), similar to that observed in
VGO. Fewer components are observed in ARC 1 and 2, suggesting the
effectiveness of the HPLC separation. Both ARC 3 and ARC 4+ contain
a large number of peaks, indicating the complexity of these
fractions. As ring class increases, H/C ratio decreases and S
content increases.
[0109] FIG. 15 shows the total compound classes observed by
APPI-FTICR. The complexity of these fractions increase dramatically
with ring class. Hydrocarbons are the major components of ARC 1.
1S, 2S and 3S contributions gradually increase as the ring class
increases. Oxygenates were observed in all ARC fractions. Most
oxygenates are 1O, 2O and 1S1O. In ARC 4+, 1N1O, 1S2O and 2S1O were
also observed. 4-ring+ aromatic fraction contains up to 4 sulfur
atoms per molecule. Sulfur incorporation clearly accompanied with
aromatic ring growth. Substantial 1N and 1N1S molecules are
observed in ARC4+. Nitrogen-containing molecules were detected in
both ARC 3 and ARC 4+. Based on the nature of the chromatographic
separation and our previous evaluation of VGO data, we believe that
these nitrogen compounds are mostly non-basic nitrogens.
[0110] One of the most important data that FTICR-MS can provide to
heavy hydrocarbon model-of-composition is the Z-number
distribution. Z numbers can be used to construct molecules with
additional input from NMR. FIG. 16 and compare the differences in Z
distribution between VR and VGO of Cold Lake crude for HC class. A
set of benchmarking aromatic structures were drawn to illustrate
degrees of unsaturations. In the case of hydrocarbons (FIG. 16),
the Z-distributions of ARC 1 and ARC 2 are very similar despite
large differences in their MW distributions. The results suggest
that hydrocarbon cores in ARC1 and ARC2 are probably similar
between VGO and VR. Starting from ARC 3, the Z distribution of VR
is becoming more negative. Even more striking differences in Z
distribution were observed for ARC 4+ where VR Z values are much
more negative than that of VGO.
[0111] FIG. 17 shows image plots of ARC1-4+ compositions (HC,
1-4S). X-axis is the molecular weight (MW). Y-axis is the Z-number.
Abundances of molecules are represented by the color scheme. Again,
from ARC1 to ARC4+, the complexity and number of molecules
increases. For example, ARC1, 2, 3, and 4+ contains 3460, 6238,
7661 and 9988 unique molecules (excluding .sup.13C and .sup.34S
isotopes). Molecular weight growth in ARC1 and 2 are primarily
governed by CH.sub.2 extension. While ARC3 and ARC4+ show notable
influence of Z-number on molecular weight, indicating aromatic ring
growth contributed to the size or molecular weight of the
molecules.
[0112] FIG. 18 and FIG. 19 show sulfide compound classes and
Z-number distribution. As expected. Sulfur containing species are
predominant. The Z-number distribution covers a wide range,
indicating the presence of polyaromatic sulfides.
Analysis of Polar Molecules
[0113] Basic nitrogens in DAO are measured by positive ion ESI.
Neutral nitrogens and acids were measured by negative ion ESI. FIG.
20 shows basic and acidic compound classes in DOBA VR. Doba is a
low sulfur crude and therefore 1N species predominate the class
distribution. High sulfur VR can contain substantial amounts of
1N1S, 1N2S and 2N species. Image plot is shown in FIG. 21. An
examination of Z-number distribution of basic 1N class revealed the
presence of 1 ring to 11 ring basic nitrogen aromatic compounds.
Doba VR shows a high level of acids. Since VR has experienced
thermal stress during vacuum distillation. It is expected that some
acids were destroyed by the thermal process. The Z-distribution of
acids shows the most abundant core structures are dicyclics. Z
number up to -32 has been observed, suggesting the presence of up
to 4 ring aromatic structures. The Z distribution of neutral
nitrogens shows aromatic ring number ranges from 3 to 10.
Analysis of Asphaltenes
[0114] A substantial amount of asphaltenes will boil above
1300.degree. F. and may not be ionized by APPI. Alternative
ionization methods, such as, MALDI and LDI, are helpful to
determine those not seen by APPI. The compound classes in
asphaltenes (FIG. 22) are extremely complicated. The most striking
feature is that there is not one dominating class. Pure
hydrocarbons are present in a small amount. 1S to 4S molecules were
detected at abundant levels. 1N, 1N1S, 1N2S and 1N3S molecules were
also observed. The total number of molecules (excluding .sup.13C
and .sup.34S isotopes) in asphaltenes is about 200,000, 10 times
higher than that in ARC4+. Image plot (FIG. 23) reveals strong
influence of Z-number on molecular weight, indicating asphaltenes
molecular weight growth is primarily driven by polyaromatic ring
growth. Z-number distributions of asphaltenes molecules are
extremely broad (from Z=-6 to -80) and centered around Z=-40 (six
ring aromatics). HC class shows a bimodal Z-number distribution.
Some of the Z>-18 molecules are clearly not n-heptane
insolubles. These molecules are co-precipitated during the
deasphalting process.
On-Line Chromatography-Mass Spectrometry
[0115] Analyses can be conducted using on-line chromatography mass
spectrometry. By definition, on-line separation means that
separated fractions are not physically collected after separation
but directly transferred and analyzed by mass spectrometer. On-line
chromatography mass spectrometry made the analysis more efficient
in cost and time. We demonstrated the feasibility by coupling an
HPLC system with FTICR-MS using APPI. FIG. 24 shows an example of
the configuration. Liquid eluting from HPLC is divided into two
streams by a splitter. Most liquid goes to the light scattering
detector (ELSD). A small portion is infused directly into the APPI
source of the FTICR-MS. Both chromatograms are recorded. The total
ion chromatogram of a VGO sample is shown in FIG. 25 (top). An
example of solvent program is given in the chromatogram. The sample
are separated into saturate, ARC1-4+, sulfides and polars by HPLC.
The effluents are directly ionized by APPI and mass analyzed by
FTICR-MS. The average mass spectra of the eluted fractions are
given in FIG. 25 (bottom). Quantification of the 7 lumps can be
done by peak area integration. FIG. 26 compares the chromatograms
from ELSD and APPI-FTICR MS. The chromatograms look very similar.
The peak areas of the 7 lumps are also very similar. APPI cannot
ionize saturate petroleum molecules.
CONCLUSIONS
[0116] We have developed FTICR-MS methods to characterize VR and
isolated fractions. FTICR-MS provides heteroatom class distribution
and Z-distribution that can be used to construct
model-of-composition for heavy hydrocarbons, in conjunction with
the MW distribution by FDMS, aromatic carbon content by NMR, S and
N content by elemental, XPS and XANES analyses. Atmospheric
pressure photoionization (APPI) using toluene as a solvent was
identified to be the most effective ionization method for aromatic
fractions, sulfides and asphaltenes. High vaporizing temperature
(450.degree. C.) assisted with nebulizing gases enables
volatilization of molecules with boiling points as high as
1300.degree. F. Electrospray ionization (ESI) is found to be the
method of choice for polar molecules. At present, saturate
hydrocarbons were analyzed by field desorption (FD) combined with a
moderate mass resolution (.about.5000) mass spectrometer. FDMS is
also used to provide molecular weight distributions for all VR
fractions.
[0117] In analysis of VR, FTICR-MS provides composition of
petroleum in terms of hydrogen deficiency (Z), heteroatom content
(SNO) and total carbon number distribution. The detailed
fractionation helps to narrow Z distributions of VR and
significantly enhances the dynamic range of FTICR-MS. The
ultra-high resolution enabled us to resolve mass overlaps and
determine stoichiometry of molecules accurately. On average, we
have detected about 3,000-200,000 species per fraction. A total of
300,000 molecules per VR have been resolved and measured in terms
of specific elemental formulae. Z values as high as -80 have been
detected, corresponding to structures containing 12 aromatic rings.
The combination of APPI and ESI-FTICR and FDMS generated highly
detailed composition of VRs that can be further reconciled with
other analytical data.
REFERENCES
[0118] 1. Qian, K.; Edwards, K. E.; Mennito, A. S.; Ferrughelli, D.
T., Observation of Vanadyl Porphyrins and Sulfur-Containing Vanadyl
Porphyrins in a Petroleum Asphaltene by Atmospheric Pressure Photon
Ionization Fourier Transform Ion Cyclotron Resonance Mass
Spectrometry. Rapid Commun. Mass Spectrom. 2008, 22, (14),
2153-2160 [0119] 2. Chawla, Birbal; Green, Larry A. HPLC separation
and quantitation of heavy petroleum fractions. PCT Int. Appl.
(2010), 41 pp. CODEN: PIXXD2 WO 2010114587 A1 20101007 CAN
153:485056 AN 2010:1252505 [0120] 3. Chawla, Birbal; Green, Larry
A. Multi-dimensional HPLC separation technique (star7) for
quantitative determinations of 7 fractions in heavy petroleum
streams boiling above 550 F. U.S. Pat. Appl. Publ. (2010), 21 pp.
CODEN: USXXCO US 2010218585 A1 20100902 CAN 153:363112 AN
2010:1103985 [0121] 4. Qian, K. E., Edwards, Kathleen E.; Diehl,
John H.; Green, Larry A., Fundamentals and Applications of
Electrospray Ionization Mass Spectrometry for Petroleum
Characterization. Energy & Fuels 2004, 18, (6), 1784-1791.
[0122] 5. Qian, Kuangnan; Edwards, Kathleen E.; Dechert, Gary J.;
Jaffe, Stephen B.; Green, Larry A.; Olmstead, William N.
Distributed total acid number in petroleum and petroleum fractions
by electrospray mass spectrometry.
TABLE-US-00001 [0122] TABLE 1 Common mass overlaps Common Mass
Difference Resolution Needed Doublets (mDa) at m/z 800
.sup.12C~H.sub.12 93.4 8,565 .sup.32S~C.sub.2H.sub.8 90.1 8,879
.sup.16O~CH.sub.4 36.0 22,222 .sup.13CH~.sup.14N 8.2 97,561
.sup.32SH.sub.4~C.sub.3 3.4 235,294
TABLE-US-00002 TABLE 2 Ionization potentials of hydrocarbon
molecules Compounds IP (eV) Hexane 10.1 Cyclohexane 9.9 Decane 9.7
n-Butyl cyclohexane 9.6 Decalin 9.4 Benzene 9.2 Toluene 8.8 n-Butyl
benzene 8.7 Indane 8.6 Naphthalene 8.1 Benzothiophene 8.1
Dibenzothiophene 8.0 Phenanthrene 7.9 n-Butyl naphthalene 7.8
Chrysene 7.6
APPENDIX II
Molecular Formula Distributions of Vacuum Resid Reconciled to the
HHMoC Research Analytical Protocol
[0123] An algorithm that computes the weight percent distributions
of molecular formulae within vacuum residuum (VR, or resid) is
disclosed in this Appendix. These molecular formula distributions
are reconciled to the heavy hydrocarbon model of composition
(HHMoC) Research Analytical Protocol (see below). This
reconciliation is a critical step in the assignment of a molecular
lump library to resid fractions, and subsequent delivery to
composition-based resid upgrading models.
[0124] In the reconciliation algorithm, the FTICR-MS data are
blended by fraction weight, then autotuned to satisfy property
constraints. These property constraints are taken from the HHMoC
research analytical protocol. They include: fraction weight, and
weight percent of hydrogen, sulfur, nitrogen, nickel and vanadium
in HHMoC fractions with available data.
HHMoC Research Analytical Protocol
[0125] In the HHMoC research analytical protocol (see schematic in
FIG. 9), n-heptane separates a resid sample into de-asphalted oil
(DAO), and asphaltene fractions. Next, a high-performance
liquid-chromatographic (LC) technique separates the DAO into
saturates, ARC1-4, sulfides, and polars. These seven
[0126] DAO fractions, and the asphaltene fraction, are analyzed by
a variety of methods. In each HHMoC fraction except DAO saturates
and polars, ultra-high resolution Atmospheric-pressure
Photoionization Fourier Transform Ion Cyclotron Resonance mass
spectrometry (APPI-FTICR-MS) measures the molecular formula
distribution. A VR molecule's molecular formula is given by
C.sub.cH.sub.2c+ZS.sub.sN.sub.nO.sub.oNi.sub.niV.sub.v (1)
[0127] Here, a molecule's carbon number is c, its hydrogen
deficiency class Z, and s, n, o, are the stoichiometric
coefficients of sulfur, nitrogen and oxygen, respectively.
APPI-FTICR-MS has also detected organometallic compounds within
selected VR fractions. These organometallic (porphyrin) compounds
contain one atom each of either nickel, or vanadium [4]. In the
molecular formula (I), the stoichiometric coefficients of nickel,
and of vanadium, are ni, v, respectively.
[0128] In lieu of Eqn. (1), we report the molecular formulae of a
molecule derived from FTICR-MS analysis as a triplet of three
attributes: the molecule's nominal mass, MW (g/mol), its hydrogen
deficiency class, Z, and its molecular type, T. The molecular type
T takes a naming convention that includes the number of heteroatoms
(s,n,o), and metal atoms (ni,v) in a resid molecule (see Table 2).
This reporting convention is equivalent to Eqn. (1); the carbon
number c of a molecule can be uniquely determined because a
molecule's nominal mass equals the sum of the nominal mass in each
atom type within the said molecule, where the nominal mass in each
atom type equals its known atomic mass (C=12, H=1, S=32, N=14,
Ni=59, V=51) multiplied by the number of atoms of that type
(c,2c+Z, s,n,ni,v). From this atomic mass balance, the carbon
number, c reads:
c=(MW-(Z+32s+14n+16o+59ni+51v))/14 (2)
[0129] Negative- and positive-ion electrospray (NEST- and PESI-)
FTICR-MS is performed on the DAO fraction to detect heteroatom-rich
molecules that elute in a variety of LC fractions. NESI-FTICR-MS
can detect non-basic nitrogen and acids; PESI-FTICR-MS detects
primarily basic nitrogen compounds. At present, the distribution of
molecules comprising the DAO polar fraction is assumed to be the
superposition of the NESI- and PESI-FTICR-MS spectra; APPI-FTICR-MS
spectra of selected DAO polar fractions have been obtained on a
non-routine basis, but are not reported here.
Reconciliation Algorithm
[0130] Inputs to the reconciliation algorithm, and computations
performed in the algorithm are detailed below.
[0131] a) Inputs
[0132] Inputs to the reconciliation algorithm are taken from the
HHMoC research analytical protocol (see FIG. 1). Mass-spectrometry
(MS) inputs include: APPI-FTICR-MS analysis of the DAO ARC1-4, DAO
sulfides, and asphaltene fractions, NESI/PESI-FTICR-MS analysis of
the DAO. As mentioned above, superposition of the NESI- and
PESI-FTICR-MS analysis of the DAO is used to synthesize an FTICR-MS
analysis of the DAO polars fraction. APPI-FTICR-MS analysis of this
polars fraction has been conducted on a number of samples in the
current HHMoC VR library, but not on a routine basis. Weights on a
100% resid basis of each HHMoC fraction are obtained by material
balance of the de-asphalting and DAO LC separation steps.
[0133] Elemental properties of selected HHMoC fractions used as
inputs include: hydrogen, sulfur, nitrogen, nickel and vanadium
content. Hydrogen contents of asphaltenes and of the following DAO
fractions are measured by combustion (ASTM D 5291): saturates,
aromatics, sulfides, and polars. Nitrogen content of asphaltenes,
and the aromatics, sulfides, and polar fractions of the DAO are
also measured using the ASTM D 5291 technique. At present, the
sulfur content of all HHMoC fractions, except DAO saturates, are
measured by ASTM D 2622 X-ray fluorescence. Nickel and vanadium
content, among other metals, is typically measured on the total
resid, asphaltene, and DAO fractions using the ASTM D 5708
technique.
[0134] b) Computational Details
[0135] In the new reconciliation algorithm, we compute the
molecular formula distribution of molecules that are made
consistent with the HHMoC research analytical protocol (see above).
This distribution is expressed mathematically as wt % abundance of
molecular lumps, as is done in SOL modeling applications. Unlike
SOL, the description of a molecular lump in this work takes only
sufficient information to identify its HHMoC fraction, and its
molecular formula per the three-attribute convention detailed in
Section 2. Thus, the weight percent abundance (100 wt % resid
basis) of a molecular lump in this work is expressed as w(f, MW, Z,
T). The HHMoC fraction index takes positive integers, f=1, 2, 3, .
. . 11 and is defined in Table 3.
TABLE-US-00003 TABLE 3 HHMoC Fraction Indices Fraction Index, f DAO
saturates 1 DAO ARC1 2 DAO ARC2 3 DAO ARC3 4 DAO ARC4 5 DAO
sulfides 6 DAO polars 7 asphaltenes 8 DAO aromatics 9 DAO 10 resid
11
[0136] Molecular types, T, depend on the stoichiometric
coefficients of heteroatoms, s,n,o and of metals ni,v. To date, a
total of 35 molecular types appear in HHMoC applications (see Table
4).
TABLE-US-00004 TABLE 4 Heteroatom Stoichiometric Coefficients of
Molecular Types in HHMoC Applications Stoichiometric Stoichiometric
coefficients coefficients Type, T s n o ni v Type, T s n o ni v HC
0 0 0 0 0 1S2N 1 2 0 0 0 1S 1 0 0 0 0 1S4N 1 4 0 0 0 2S 2 0 0 0 0
3S1O 3 0 1 0 0 3S 3 0 0 0 0 3S1N 3 1 0 0 0 1N 0 1 0 0 0 3S1N1O 3 1
1 0 0 1S1N 1 1 0 0 0 4S1N 4 1 0 0 0 1O 0 0 1 0 0 2O 0 0 2 0 0 1N2O
0 1 2 0 0 4O 0 0 4 0 0 4N1O1V 0 4 1 0 1 1N1O 0 1 1 0 0 1S1O 1 0 1 0
0 1S4N1O1V 1 4 1 0 1 1S1N1O 1 1 1 0 0 2N 0 2 0 0 0 2S1O 2 0 1 0 0
2N1O 0 2 1 0 0 2S1N 2 1 0 0 0 3N1O 0 3 1 0 0 2S1N1O 2 1 1 0 0
1S2N1O 1 2 1 0 0 4S 4 0 0 0 0 1S2O 1 0 2 0 0 5S 5 0 0 0 0 4N1Ni 0 4
0 1 0 3N 0 3 0 0 0 1S4N1Ni 1 4 0 1 0 4N 0 4 0 0 0
[0137] Nominal molecular weight, MW, can take any positive integer.
However, nominal molecular weights appearing in FTICR-MS spectra
rarely exceed 3000 g/mol. Hydrogen deficiency class, Z takes
integers Z=2, 1, 0, . . . -.infin.. For molecules that have even
numbers of nitrogen atoms, i.e. the stoichiometric index n=0, 2, 4,
. . . , the hydrogen deficiency class Z and the nominal molecular
weight MW are even integers. For molecules with odd numbers of
nitrogen atoms, i.e. n=1, 3, 5, . . . , hydrogen deficiency class Z
and molecular weight MW are odd integers.
[0138] In first step of the reconciliation algorithm, a vector of
initial molecular lump abundances w*(f, MW, Z, T) are set equal to
the values measured by FTICR-MS analyses of selected HHMoC
fractions f=2, 3, . . . 11 (see Table 1). As noted in Section 3a,
the initial molecular lump abundance in the DAO polars fraction
w*(f, MW, Z, T) is synthesized by blending the NESI- and
PESI-FTICR-MS analysis of the DAO fraction. In the DAO saturates
fraction, the initial molecular lump abundances w*(f, MW, Z, T)
made equal to that of its FDMS spectra, where the hydrogen
deficiency classes Z are assumed to equal the nominal hydrogen
deficiency class X. Next, the initial molecular lump abundances
w*(f, MW, Z, T) are adjusted to reconciled values w(f, MW, Z, T).
This adjustment is done such that the loss of information entropy
is minimized, such that the reconciled values w(f, MW, Z, T)
satisfy a list of linear property constraints
i = 1 N a ji w i = b j for j = 1 , 2 , , NP ( 3 ) ##EQU00001##
[0139] Here, a.sub.ji is the density of property j in molecular
lump i, and b.sub.j is the measured value of property j. (see Table
3). Each molecular lump i is identified by its HHMoC fraction, f,
and the three attributes MW, Z, and T. In the constrained
optimization of information entropy, one solves the following
Euler-Lagrange equation to determine a set of Lagrange multipliers
A.sub.k:
i = 1 N a ji w i * exp ( - 1 + k = 1 NP .lamda. k a ki ) = b j exp
( - .eta. j .lamda. j ) for j = 1 , , NP ( 4 ) ##EQU00002##
[0140] The softness parameters .eta..sub.j are zero to denote hard
constraints. Otherwise, they are non-zero to facilitate convergence
of the Euler-Lagrange Eqn. (4) when selected measured properties
b.sub.j have significant uncertainty; non-zero values of these
parameters are typically chosen by trial-and-error (see Table
5).
TABLE-US-00005 TABLE 5 Property Balance Constraints in HHMoC
Autotuning Step Index of HHMoC Non-zero values of Softness Property
value, b fractions, f (see Table 1) property density, a parameter,
.eta. Total weight (100 wt % All fractions, i.e. a = 1 for all
molecules 0 resid basis) f = 1, 2, 3, . . . , 11 Fraction wt %,
total resid All fractions except DAO a = 1 for all 0 basis
saturates, i.e. molecules in fraction f f = 2, 3, 4, . . . , 11
Hydrogen wt % in All fractions, i.e. a = weight fraction 1.0E-06
fraction, total resid f = 1, 2, 3, . . . , 11 hydrogen for all
basis molecules in fraction f Sulfur wt % in fraction, All
fractions except DAO a = weight fraction 1.0E-06 total resid basis
saturates, i.e. sulfur for all f = 2, 3, 4, . . . , 11 molecules in
fraction f Nitrogen wt % in f = 6, 7, 8, 9 only a = weight fraction
1.0E-06 fraction, total resid nitrogen for all basis molecules in
fraction f Nickel wt % in f = 8, 10 if data a = weight fraction 0
fraction, total resid available; nitrogen for all basis f = 11
otherwise molecules in fraction f Vanadium wt % in f = 8, 10 if
data a = weight fraction 0 fraction, total resid available;
vanadium for all basis f = 11 otherwise molecules in fraction f
[0141] The vector of reconciled lump weights w(f, MW, Z, T) is
determined by post-processing the solution of Eqn. (E-2):
w i = w i * exp ( - 1 + j = 1 NP a ij .lamda. j ) for i = 1 , , N (
4 ) ##EQU00003##
* * * * *