Molecular Composition of Shale Oil - American Chemical Society

Chapter 5

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Molecular Composition of Shale Oil James W. Bunger,* Christopher P. Russell, and Donald E. Cogswell JWBA, Inc., Salt Lake City, Utah, USA 84152-0037 *[email protected]

Molecular compositions of shale oils differ widely among deposits and retort technologies. Shale oils invariably contain high concentrations of heteroatom-containing compounds, and these characteristics will strongly influence approaches to processing of shale oil to marketable products. An advanced analytical method for identifying and quantifying molecular composition of shale oil, the Z-BaSIC™, method is illustrated and results are given. Results show that like conventional petroleum, compound types can be readily described by a limited number of homologous series. Detailed knowledge of composition will assist in the development of effective process steps needed to assimilate vast shale oil resources into the market-place.

Introduction Shale oil is the pyrolysis product of kerogen, a primitive, high heteroatomcontaining organic material found in oil shale. For example, Estonia kerogen is high in oxygen, Jordanian and Israeli kerogen is high in sulfur, and US kerogen is high in nitrogen. The molecular composition of the shale oils derived from these kerogen-containing ores reflects the high heteroatom content of their precursor material. Shale oil may be used for three principal purposes. It may be simply burned as a fuel. This is possible when sulfur and nitrogen contents are low, as with Estonia shale oil. It may be upgraded and fed to a petroleum refinery to make conventional fuels and petroleum products. Upgrading is needed not only to stabilize the olefins but to remove heteroatoms of sulfur, nitrogen and metals. Or

© 2010 American Chemical Society In Oil Shale: A Solution to the Liquid Fuel Dilemma; Ogunsola, O., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2010.


it may be fed to a chemical refining process to extract and produce specialty and commodity chemicals, where the extraction raffinate is made into fuels (1, 2). The value of shale oil for its respective markets depends strongly on its molecular composition, as well as the process technology available for upgrading or refining. Processing technologies are by no-means clearly established, and much of the development work in the future will be aimed at finding the optimum technologies and process conditions that yield products for the target markets. For these reasons, it is useful to know the molecular composition of shale oil so as to understand what separations and conversions are economically desirable. This paper describes the results of an analytical method, called Z-BaSIC™ to quantify the molecular composition of shale oil.

Brief Description of Z-BaSIC Z-BaSIC™ is an acronym for the Z-Based Structural Index Correlation method. Z-BaSIC describes the molecular composition of shale oil (or crude oils) in numerical form. More detailed descriptions of the method can be found in references (3–5). First, compound types are classified by the generalized empirical formula:

Where ‘z’, ‘u’, ‘v’, ‘w’, ... are integer values that classify an individual molecule by a z-vector. The ‘n’ value is the primary variable that defines a homologous series. As ‘n’ → ∞, all properties, Pi, approach the value for the corresponding property of an infinitely long paraffin. This adds confidence to the correlations of properties for heavy ends, where pure compound databases do not exist. The use of an empirical formula as a classification system and the definition of ‘n’ as the primary structural index correlating variable is the scientific foundation of the Z-BaSIC™ method. Identification of the Z-BaSIC parameters for components in a mixture is made using capillary gas chromatography equipped with mass-, sulfur- and nitrogen-specific detectors (GC-MSD). A methodology has been developed using parent ions from 70ev electron impact ionization (mass selective detector) to classify the compound by z-vector (class). Within a class, variations in ‘n’ are rigorously associated with variations in MW by 14 atomic mass units (-CH2). Where more than one z-vector gives rise to a common ion, GC retention time is used to distinguish between the z-vectors. Nitrogen and sulfur specific detectors are used to obtain the heteroatom distribution with respect to pseudoparaffin number (i.e. boiling point). Quantification of the composition is accomplished by first measuring the elemental composition, density and boiling point distribution (determined by HTSD). A least-error fit is sought whereby the concentrations of the basket of compounds found by GC-MSD agrees with the measured data. The use of the

104 In Oil Shale: A Solution to the Liquid Fuel Dilemma; Ogunsola, O., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2010.

density property is possible because of the correlations of the ‘n’ parameter with physical properties for a given z-vector. The combined information is used to prepare a composition-property, or ‘cp’ file. This file can then be used as input to a suite of software programs used to calculate properties, report molecular composition, and simulate refinery processes such as distillation, blending, and conversion processing. Z-BaSIC may also be used to prepare high-fidelity pseudocomponent files as input for LP models and process simulators.


Results Bulk Properties A sample of pilot plant oil produced by the EcoShale™ process on a Utah field site was analyzed by the Z-BaSIC method. EcoShale is a developing technology of Red Leaf Resources that involves indirectly heating a bed of oil shale using pipes buried in the bed. The pipes carry combustion gases in a closed loop. As oil is produced some oil drains to the bottom, where it is pumped, while vapors are collected overhead and condensed. The EcoShale 32 shale oil sample is a representative composite of the total oil produced. Measured input data is shown in Table 1. Note the high nitrogen and low sulfur contents, typical of Green River formation shale oil. ‘cp’ files (earlier generation versions) have also been prepared on a Colorado surface retort shale oil (Unocal 23) and an Estonia surface retort (Kukersite 8) shale oil, and their input data is also given in Table 1. It is clear from the bulk properties that large differences exist between various deposits and large variations result from different retort technologies applied to the same deposit. Whereas, the EcoShale process (a variation on a modified in-situ, MIS, approach) utilized 90 days to achieve temperatures between 700-750 °F, the Colorado and Estonia surface retorts achieve temperatures of greater than 900 °F in less than 1 hour. Under slow heating conditions the Ecoshale 32 oil is higher in hydrogen and lower in boiling range than the Unocal 23. The variations in heteroatom content have yet to be explained, and could relate to deposit variations, or possibly differences in analytical accuracy (the Unocal 23 oil was analyzed nearly 20 years ago). Measured high temperature simulated distillation data (HTSD) for EcoShale 32 are given in Table 2. Note that approximately 66 % of the oil boils between 304 and 676 °F, equivalent to the diesel fuel boiling range of C9 to C21. The high middle distillate yield results from the slow heating, as Unocal 23 shale oil sample only yields about 40% over this same range (detailed data not shown).


Table 1. Property data on three shale oils Property - units

EcoShale 32 Utah

Unocal 23 Colorado

Estonia Kukersite 8


Measured input data for Z-BaSIC file construction Carbon – wt%

85.26

85.87

88.31

Hydrogen – wt%

12.45

11.74

8.06

Nitrogen – wt%

1.55

1.30

0.1

Basic Nitrogen – wt%

1.08

0.73

NA

Sulfur – wt%

0.249

0.918

0.557

Oxygen – wt%

1.24

0.17

2.98

0.8643

0.9148

1.0189

32.2

23.2

7.4

11.55

11.3

10.3

198

245

226

Non-detect

3.0

0.2

10% point °F

330

384

528

50% point °F

560

716

702

90% point °F

801

935

915

Kinematic Viscosity @ 37.78 °C - cSt

4.00

23.3

259

Kinematic Viscosity @ 50.0 °C - cSt

3.04

NA

NA

Dynamic Viscosity @ 37.78 °C - cP

3.39

21.5

266

Dynamic Viscosity @ 50.0 °C - cP

2.55

14.4

136

Density @ 15.5 °C – g/cc API gravity - degrees

Additional property data on whole oils - Z-BaSIC output data UOP K factor Average MW - Dalton Conradson Carbon wt % D-2887 distillation data

ND = non-detect NA= not analyzed

Summary Molecular Composition A summary of the molecular composition for three shale oils is given in Table 3. For the EcoShale oil about 50% of the oil is saturated hydrocarbons, and that another 34% of the oil is nitrogen and oxygen types. These types, principally pyridines and pyrroles, are candidates for production of commodity and specialty chemicals by extraction and refining of the extract (1, 2). Only 15-16% of the oil is comprised of sulfur compounds and aromatic hydrocarbons. The Unocal 23 exhibits lower paraffins and higher aromatics. The Kukersite oil is extremely high in oxygen compounds, reflecting the potential value of that oil for producing phenols and resorcinols (2, 6). 106 In Oil Shale: A Solution to the Liquid Fuel Dilemma; Ogunsola, O., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2010.


Table 2. EcoShale 32 HTSD

What is clear from these analyses is that oil compositions may be highly variable from one process to another and from one deposit to another. Measurable differences have been seen between oils produced by the same technology and deposit, but under different process conditions. Differences also exist during the progress of reaction, from beginning to end (data not shown).

Detailed Molecular Composition The detailed molecular composition of EcoShale 32 is given in Tables 4 (a), 4 (b), 4 (c) and4 (d) . (This is one table, but broken up to fit the pages and make the entries readable.) The values given in the table are in weight percent of the compound type and carbon number indicated. The sum of all carbon numbers is given in the ‘totals’ column, and is repeated on each part. Dashes “-” found in the 107 In Oil Shale: A Solution to the Liquid Fuel Dilemma; Ogunsola, O., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2010.

Table 3. Summary of molecular composition EcoShale 32 wt %

Unocal 23

Kukersite (Estonia) wt %

26.614

17.454

0.167

3.546

NA

NA

23.757

26.852

5.474

monoaromatics

4.553

12.122

15.905

diaaromatics

2.941

4.599

12.995

polyaromatics

0.567

1.368

4.909

sulfur compounds

1.821

6.916

3.728

pyrrolics

8.587

10.753

ND

pyridinics

17.706

10.2

ND

phenolics

8.399

1.267

30.717

Unidentified & >C36

1.506

8.471

26.104

99.997

100.002

99.999

Compound type paraffins olefins


naphthenes

Total NA = not analyzed ND = non-detect

table indicate that the compound type is infeasible for that carbon number. Zeros “0” indicate that the type and carbon number were sought, but if present, were below the detection limits of the GC-MSD. Inspection of the table shows that shale oil can be described by homologous series of about 60 z-vectors, or compound types. For the most part, each type shows a single maximum in concentration, although that is not rigourously true for all molecular types. In our experience with a wide range of hydrocarbon mixtures, the total number of different z-vectors found for a variety of crude oils, bitumens and pyrolysis oils is less than about 100.

Discussion The data shown in the Table 4 (a) imply a precision in analysis that does not, in fact, exist. The ‘cp’ file may contain more than 20,000 lines, and it becomes necessary to work in scientific notation. A higher number of decimal figures is required to avoid rounding discrepancies. One could argue with the concentration of any one of the entries. However, for sake of instruction, if one entry in the matrix is changed to a different value, then all other entries in the entire table will change slightly. This is because the sum of all the entries must agree with the input data (elemental composition, density, and boiling point distribution). Thus, the quantitative solution is a least-error one, rather than a more deterministic one. 108 In Oil Shale: A Solution to the Liquid Fuel Dilemma; Ogunsola, O., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2010.


Table 4 (a). Compound type composition of EcoShale 32

Likewise, if a compound type is not analyzed (such as the olefins for two of the shale oils), to the extent that such compounds exist in the oil, the concentrations of all other compounds are adjusted such that the distribution, properties and elemental composition still agree with the measured values. The consequence is that the composition portrayed is an accurate representation of the important chemical characteristics of the oil. Said another way, if the absolute concentrations of a given species are incorrect, there are offsetting concentrations of other types that keep the file consistent with measured values. 109 In Oil Shale: A Solution to the Liquid Fuel Dilemma; Ogunsola, O., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2010.


Table 4 (b). Compound type composition of EcoShale 32 (cont.)

A powerful capability of Z-BaSIC is that once a reference ‘cp’ has been created for the basket of compounds found in the oil, then changes in oil composition can be tracked by entering new input data. A file adjuster has been written which allows the concentration of all components to be either increased or decreased over the smallest distance possible to agree with the new measured 110 In Oil Shale: A Solution to the Liquid Fuel Dilemma; Ogunsola, O., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2010.


Table 4 (c). Compound type composition of EcoShale 32 (cont.)

data. By this means insight into the conversion chemistry can be gained by correlating the change in compound types with changes in process conditions. Molecular composition also gives insight into the conversion chemistry occurring. Rapid heatup results in production of higher molecular weight oils and discourages secondary reactions such as dehydrogenation and condensation 111 In Oil Shale: A Solution to the Liquid Fuel Dilemma; Ogunsola, O., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2010.


Table 4 (d). Compound type composition of EcoShale 32 (cont.)

(coking). Slower heatup results in lower molecular weight compounds being produced, but produces more coke because of the enhanced secondary reactions.


Summary


As the world inevitably moves to produce abundant oil shale resources, details of reaction kinetics, composition, upgrading processes, product development and manufacture will unfold. It may be possible to develop new markets to take advantage of the heteroatom functionalities present. Once production is established, refineries can count on a consistent quality feedstock. Consistency in quality is a characteristic upon which markets place value, as evidenced by the ready marketing at sound prices enjoyed by Alberta syncrudes.

Acknowledgements The supply of shale oil samples from Red Leaf Resources, Eesti Energia, Viru Keemia Grupp, and Unocal is gratefully acknowledged. Permission from Red Leaf Resources to publish the detailed composition of EcoShale 32 is acknowleged. The financial support of the US Dept. of Energy contract number DE-AC2193MC29240 is acknowledged. The authors gratefully acknowledge the on-going encouragement and helpful guidance of the late Hugh Guthrie, DOE COTR, a friend and mentor.

References 1.

2. 3.

4.

5.

6.

Bunger, J. W.; Cogswell, D. E.; Russell, C. P. Value-Enhancement Extraction of Heteroatom-Containing Compounds from Kerogen Oil. Prepr. Am. Chem. Soc., Div. Fuel Chem. 2001, 46, (2), 573−576; July. Bunger, J. W., et al. Shale Oil Value Enhancement Research. Final Technical Report, DOE contract DE-AC21-93MC29240, April 2007. Bunger, J. W.; Devineni, P. A. V.; Russell, C. P.; Oblad, A. G. Structure of Future Jet Fuels - A Model for Determining Physical and Chemical Properties from Molecular Structure. Prepr. Am. Chem. Soc., Div. Pet. Chem. 1987, 30, (1). Devineni, P. A. V.; Bunger, J. W.; Russell, C. P. Prediction of Optimum Structure for JET Fuel Components using the Z-BaSIC Method. Prepr. Am. Chem. Soc., Div. Pet. Chem. 1989, 34, (4), 858−866. Bunger, J. W.; Russell, C. P.; Cogswell, D. E. Quantitative Description of the Molecular Composition of Crude Oil .Prepr. Am. Chem. Soc., Div. Pet. Chem. 2001, 46 (4), 355−360; August. Koel, M.; Bunger, J. Overview of Program on US-Estonia Science and Technology Cooperation on Oil Shale Research. Oil Shale 2005, 22, (1), 65−79.


Molecular Composition of Shale Oil - American Chemical Society

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