Energy Intensity and Greenhouse Gas Emissions from Thermal

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Energy Fuels 2010, 24, 4581–4589 Published on Web 08/04/2010

: DOI:10.1021/ef100410f

Energy Intensity and Greenhouse Gas Emissions from Thermal Enhanced Oil Recovery Adam R. Brandt*,† and Stefan Unnasch‡ †

Department of Energy Resources Engineering, 367 Panama Street, Green Earth Sciences 065, Stanford University, Stanford, California 94305-2220, and ‡Life Cycle Associates, LLC, Portola Valley, California 94028 Received April 2, 2010. Revised Manuscript Received July 27, 2010

Thermal enhanced oil recovery (TEOR) is used worldwide to increase the production of viscous heavy oils. The most common TEOR method injects steam into the subsurface reservoir to reduce the viscosity of the crude oil and allow it to flow. Production of steam for TEOR consumes energy, affecting the energy efficiency and greenhouse gas (GHG) emissions of oil production. This paper calculates the energy efficiency and GHG emissions of TEOR. Results are generated for generic cases and for California-specific cases. GHG emissions in the generic cases range from ≈105 to 120 g of CO2/MJ [gasoline basis, full fuel cycle, lower heating value (LHV) basis] when co-produced electricity displaces natural-gas-fired combined-cycle electricity. The carbon intensity varies with the energy demand of TEOR, the fuel combusted for steam generation, the amount of electric power co-generated, and the electricity mix. The emission range for co-generation-based TEOR systems is larger (≈70-120 g of CO2/MJ) when coal is displaced from the electricity grid (low) or coal is used for steam generation (high). The emission range for the California-specific cases is similar to that for the generic cases.

duced by U.S. Department of Energy laboratories and consulting firms.4-8 These reports indicate that well-to-tank (WTT) GHG emissions from conventional crude oil production, refining, and delivery can vary by a factor of 2 or more (e.g., 12-30 g of CO2/MJ of refined fuel delivered). Of particular importance are emissions from tertiary petroleum extraction methods, also called enhanced oil recovery (EOR). The most important EOR technology (by volume of crude produced) is TEOR, which is applied to heavy, viscous crude oils. TEOR heats the petroleum in the subsurface, reducing its viscosity and allowing it to flow from the reservoir. Commercial-scale production of heavy crude oil by thermal means first occurred in California, with experimentation occurring as early as 1901. The first modern steam injection project was at the Yorba Linda field in 1960.9,10 After the success of this experiment, steam injection expanded quickly, such that 1964 and 1965 each saw the construction of more than 50 new projects in California.9

Introduction Increasing regulation of greenhouse gas (GHG) emissions creates the need to assess GHG emissions from liquid fuel production systems.1,2 Effort in this area has shifted from largely academic interest in life-cycle assessment (LCA) of GHG emissions from liquid fuel cycles to the adoption of LCA as a compliance tool in GHG regulations. For example, the California Low Carbon Fuel Standard (LCFS) requires the average life-cycle GHG intensity (including upstream and refining emissions) to decline 10% on a production-weighted basis by 2020, relative to a 2010 baseline.3 GHG emissions from conventional transportation fuels can vary significantly. This variation impacts the calculation of the baseline emission intensity for GHG regulations. Emissions from conventional (petroleum-based) fuels vary because of (1) differences in the management of production operations, such as disposal of non-marketable methane, (2) use of secondary recovery (e.g., waterflooding) and tertiary recovery [e.g., thermal enhanced oil recovery (TEOR)] technologies, (3) varying reservoir characteristics, such as depth, location (e.g., onshore versus offshore), size, or reservoir porosity and permeability, and (4) varying crude qualities, such as density and contaminant concentration (e.g., sulfur or metals), which affect extraction and refining energy intensity. This variation in GHG emissions from petroleum production and refining has been explored recently in reports pro-

(4) Gerdes, K. J.; Skone, T. J. An Evaluation of the Extraction, Transport and Refining of Imported Crude Oils and the Impact on Life Cycle Greenhouse Gas Emissions; Office of Systems, Analysis, and Planning, National Energy Technology Laboratory (NETL): Pittsburgh, PA, March 27, 2009; DOE/NETL-2009/1362. (5) Gerdes, K. J.; Skone, T. J. Consideration of Crude Oil Source in Evaluating Transportation Fuel GHG Emissions; National Energy Technology Laboratory (NETL): Pittsburgh, PA, 2009. (6) Keesom, W.; Unnasch, S.; et al. Life Cycle Assessment Comparison of North American and Imported Crudes; Jacobs Consultancy and Life Cycle Associates for Alberta Energy Resources Institute: Chicago, IL, July 2009. (7) Rosenfeld, J.; Pont, J.; et al. Comparison of North American and Imported Crude Oil Life Cycle GHG Emissions; TIAX LLC and MathPro, Inc. for Alberta Energy Research Institute: Cupertino, CA, 2009. (8) Larson, R.; Wang, M. Q.; et al. World Resour. Rev. 2005, 17 (2), 220–242. (9) California Department of Conservation: Division of Oil, Gas, and Geothermal Resources (CDC-DOGGR). Summary of Operations: California Oil Fields; CDC-DOGGR: Sacramento, CA, 1966. (10) Rintoul, W. Drilling Ahead: Tapping California’s Richest Oil Fields, 1st ed.; Valley Publishers: Santa Cruz, CA, 1981.

*To whom correspondence should be addressed. Fax: þ1-650-7252099. E-mail: [email protected]. (1) Farrell, A.; Sperling, D.; et al. A Low-Carbon Fuel Standard for California: Part 1;Technical Analysis; Institute for Transportation Studies: Berkeley, CA, Aug 1, 2007. (2) Farrell, A.; Sperling, D.; et al. A Low-Carbon Fuel Standard for California: Part 2;Policy Analysis; Institute for Transportation Studies: Berkeley, CA, Aug 1, 2007. (3) California Air Resources Board (CARB). Proposed Regulation to Implement the Low Carbon Fuel Standard;Staff Report: Final Statement of Reasons; CARB: Sacramento, CA, Dec 2009. r 2010 American Chemical Society

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efforts. Energy inputs and emissions are tracked over the fuel cycle from feedstock extraction to vehicle fuel combustion. WTW energy inputs and emissions include the following: (i) crude oil production, (ii) crude oil transport, (iii) refining, (iv) refined fuel delivery, and (v) refined fuel combustion. GHG emissions from TEOR result primarily from fuels combusted for steam generation. The amount of energy required to convert water to steam for injection depends upon the steam pressure and steam quality (Table 1).17 A key parameter for the economics of TEOR is the steam/oil ratio (SOR). The SOR is the steam volume required to induce production of a barrel (bbl) of incremental oil (bbl of cold water converted to steam per bbl of induced incremental crude oil production). Incremental oil is oil produced in excess of baseline oil volumes, which are modeled projections of what would have been produced without the application of TEOR. SOR varies with field characteristics, the TEOR method applied (e.g., steamflood versus cyclic steam stimulation), and the maturity of a TEOR operation. The SORs for all California TEOR projects are presented in Table 2.18 The production-weighted average SOR for all California TEOR fields in 2006 was 5.13 bbl of steam/bbl of oil. SOR includes liquid water injected (steam is not generated or injected at 100% quality in California TEOR operations). The efficiency of steam generation differs with the technology used to generate the steam, weather, and feedwater properties. In once-through steam generators (OTSGs), the water moves through the steam generator in a single pass. Because of scaling concerns, these generators produce steam with a maximum quality of ≈80%.17 OTSGs have a thermal efficiency [lower heating value (LHV) basis] of steam generation, ηsteam, given by

Figure 1. Global TEOR incremental production (in 2008) and numbers of active projects, steam injection only (kbbl/day). In situ combustion (“fireflood”) and hot water injection are TEOR methods of secondary importance and are not considered here. Data from Moritis.13

Globally, TEOR was adopted rapidly: steam injection was adopted in Venezuela in the late 1960s, in Canada in the late 1960s and 1970s, in China starting in the early 1980s and increasing to 140 kilobarrels (kbbl)/day by 1991, and in Indonesia with >300 kbbl/day Duri field in 1984.11,12 Currently, TEOR is the most important form of EOR on a global basis. Reported global incremental production from TEOR operations, including steam-assisted gravity drainage production of Canadian bitumen, was 1200 kbbl/day in 2008 or about 1.5% of global liquid fuel production.13 Figure 1 shows a plot of TEOR projects by country, excluding in situ combustion projects and hot water injection. Current expansion efforts in TEOR are focused in Alberta and Saudi Arabia.14 Because of the need to properly account for GHG emissions from TEOR for regulatory compliance purposes, we have developed a model of TEOR production that allows for analysis of GHG emissions from a given TEOR project. This model uses a small number of project parameters to generate GHG emission estimates. This paper provides a description of the methods used to calculate GHG emissions [consistent with the greenhouse gases, regulated emissions, and energy use in transportation (GREET) framework for oil production] and estimates overall well-to-wheel (WTW) emissions for six generic TEOR cases and three California-specific TEOR cases.

ηsteam ¼

Esteam ðMJÞ Ecomb ðMJ LHVÞ

ð1Þ

where Esteam represents the energy required for steam generation at the given generation pressure, Esteam = hfg þ Δhf - Erec. Here, Erec represents thermal energy recovered from warm incoming water (measured relative to the Δh baseline temperature). Erec can also be recovered from blowdown water if generators produce 100% quality steam and, therefore, must reject hot solute-rich water to prevent scaling. Ecomb is the combustion energy, on a LHV basis. ηsteam is generally 80-85%19 and is a function of the excess combustion air and the flue gas temperature upon exit from the generator.20 Higher efficiencies are limited by the need to keep flue gas temperatures above the acid dewpoint (≈150 °C, depending upon stack conditions and fuel composition).20 Co-generation projects in TEOR projects typically combine natural gas combustion turbines with steam generation from turbine exhaust using heat recovery steam generators (HRSGs). Such systems have two metrics of efficiency. The steam generation efficiency is defined as above. The efficiency of electricity ηelect production is defined as ηelect ¼

Experimental Section The analysis presented here follows the framework of the GREET model, California LCFS, and other WTW LCA

Eelect ðMJÞ Eelect ðMJ LHVÞ

ð2Þ

with output of electricity Eelect in megajoules. These two partial efficiencies can be combined into a total co-generation efficiency, ηcogen ηcogen ¼

(11) Leonard, J. Oil Gas J. 1984, 82 (14), 83. (12) Moritis, G. Oil Gas J. 1998, 96 (16), 49. (13) Moritis, G. Oil Gas J. 2008, 106, 15. (14) Chevron hosts Saudi and Kuwaiti Senior Petroleum Officials at the Onshore PNZ Large Scale Steamflood Pilot Project. http://www. eyeofdubai.com/v1/news/newsdetail-36174.htm (accessed on Nov 16, 2009). (15) Wang, M. Q. GREET Model 1.8b; Argonne National Laboratory: Argonne, IL, 2008; http://www.transportation.anl.gov/publications/transforum/v8/v8n2/greet_18b.html. (16) California Air Resources Board (CARB). Detailed CA-GREET Pathway for California Reformulated Gasoline Blendstock for Oxygenate Blending (CARBOB) from Average Crude Refined in California; CARB: Sacramento, CA, Feb 27, 2009; p 52.

Eelect ðMJÞ þ Esteam ðMJÞ Ecomb ðMJ LHVÞ

ð3Þ

(17) Hong, K. C. Steamflood Reservoir Management: Thermal Enhanced Oil Recovery; PennWell Publishing Company: Tulsa, OK, 1994. (18) California Department of Conservation: Division of Oil, Gas, and Geothermal Resources (CDC-DOGGR). 2006 Annual Report of the State Oil and Gas Supervisor; CDC-DOGGR: Sacramento, CA, 2007. (19) Burger, J.; Sourieau, P.; et al. Thermal Methods of Oil Recovery, 3rd ed.; Gulf Publishing Company: Houston, TX, 1985. (20) Prats, M. Operational aspects of steam injection processes. In Enhanced Oil Recovery: Processes and Operations; Donaldson, E. C., Chilingarian, G. V., Eds.; Elsevier: Amsterdam, The Netherlands, 1989.

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Table 1. Energy Required for Steam Generationa source

energy demand (MJ/bbl)

notes

author calculation author calculation Green and Willhite39 Hong17 Hong17

346 382 369 320 333

60% quality steam at 500 psia 80% quality steam at 500 psia rule of thumb for energy content of TEOR steam p 58, adjusted by authors for different reference temperature p 91, for maximum output from a 50 mmBtu generator

a

Units are MJ/bbl of steam, measured as bbl of cold water equivalent (CWE), 42 gallons of water at standard temperature.

Table 2. SOR by Field for California TEOR Projects for 200618 a field

crude gravity (deg API)

incremental oil (kbbl)

injection, cyclic steam stimulation (kbbl of H2O)

injection, steam flood (kbbl of H2O)

total steam injected (kbbl of H2O)

SOR

Arroyo Grande Belridge, North Belridge, South Coalinga Cymric Jasmin Kern Front Kern River Lost Hills Lynch Canyon McKittrick Midway-Sunset Mount Poso Orcutt Oxnard Placerita Poso Creek Round Mountain San Ardo total or average

14 34.3 26 25.3 20.8 14 14 13.1 26.7 11 15.5 18.2 15.4 15.5 22.9 15.2 13.0 18.2 11.5 17.8

552 64 13840 4692 3359 1 1037 30000 1750 64 1755 32543 3 16 50 1000 101 1736 2812 95375

190.0 67.8 4196.5 1638.3 38854.0 0 482.1 16373.7 593.1 96.8 1088.6 56815.4 0 106.2 134.0 3225.4 2720.8 0 1809.8 128392

3282.2 0 65691.4 26997.1 16951.2 168.0 7,159.2 76073.3 10049.3 0 7053.3 113250.5 254.7 0 0 7088.4 602.8 7184.5 19068.6 360874

3472.1 67.8 69887.8 28635.4 55805.3 168.0 7641.2 92446.9 10642.4 96.8 8141.8 170066.0 254.7 106.2 1334.0 10313.8 3323.5 7184.5 20878.4 489267

6.29 1.06 5.05 6.10 16.61 168.00 7.37 3.08 6.08 1.51 4.64 5.23 84.90 6.64 2.68 10.31 32.91 4.14 7.42 5.13

a Crude gravity is a representative value for field from the California Department of Conservation: Division of Oil, Gas, and Geothermal Resources (CDC-DOGGR) (can vary by pool in the field).40 Total SOR is production-weighted average SOR.

Theoretical co-generation efficiencies were calculated by Berry and Good.21 Figure 2 plots ηsteam, ηelect, and ηcogen for cases from Berry and Good and cases from this analysis. The normalized energy consumption ratio for steam production, Rsteam (MJ consumed/MJ of incremental crude oil produced), is therefore equal to Esteam SOR Rsteam ¼ ð4Þ ECηsteam where again Esteam is the energy consumed for steam and EC is the energy density of the crude oil (MJ LHV/bbl). The case for co-generation is equivalent. Another factor affecting GHG emissions from TEOR is the fuel type used for steam generation. Fuels consumed include produced crude oil, natural gas, coke, coal, and agricultural residue, with the most common fuel being natural gas. The carbon intensities Cfuel for these fuels range from 55.2 to 99.4 g of CO2/ MJ LHV for natural gas and petroleum coke, respectively, with other fossil fuels in between these values.15 The product of Rsteam and Cfuel is direct CO2 emissions per megajoule of incremental oil. These are gross emissions associated with steam generation; to calculate full system impacts of TEOR, exported power must be given an emission credit (i.e., gross emissions are reduced to net emissions). Avoided emissions depend upon the carbon intensity of the displaced electricity Celect (g of CO2/MJ of electricity) and ηelect. Therefore, net CO2 emissions from TEOR steam generation are Ceff ¼ Rsteam Cfuel - ηelect Rsteam Celect ð5Þ

Figure 2. Co-generation efficiencies reported by Berry and Good21 and calculated in this paper from empirical data. These are higher heating value (HHV) basis (e.g., latent heat of vaporization is included in the waste heat portion of the figure). Efficiencies are converted to LHV basis for inclusion in calculations.

where in the case of OTSG or other non-co-generation schemes, ηelect = 0. Similar calculations are performed for minor GHG constituents (e.g., CO and N2O) using GREET model emission factors.15 In addition to thermal demands for TEOR, the electricity demand for TEOR is also included as an energy input, using an estimate of 20 kWh/bbl of oil produced.22 GHG emissions from crude oil refining depend upon the refinery configuration, the crude stream processed, the product

(21) Berry, J. P.; Good, W. K. Cogeneration potential in western Canada. In International Heavy Oil Symposium; Society of Petroleum Engineers: Calgary, Alberta, Canada, 1995; Vol. SPE 30246.

(22) Electric Power Research Institute (EPRI). Enhanced Oil Recovery Scoping Study; EPRI: Palo Alto, CA, 1999; TR-113836.

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Figure 3. Relationship between API gravity of crude oil and refining GHG emissions (derived from data in Keesom et al.).6 Right axis includes allocation of refinery emissions to reformulated gasoline blendstock for oxygenate blending (RBOB).

This analysis applies standard factors from the GREET model to other portions of the WTW fuel cycle. Transport of crude oil to the refinery is included as part of the upstream energy burden, with a 300 mile pipeline transport assumed for all cases. Fuel transport energy consumption and emissions are from the CA GREET model.15 Crude oil production and transport emissions are adjusted by GREET loss factors for fuel distribution. The results are comparable to the GREET approach,15 with the Jacob’s Consultancy approach for refining. The inputs for the California empirical cases reflect oil production, power generation resources, and transport, consistent with California characteristics. Generic Case Definitions. Six generic cases are modeled (see Table 3). These cases include two steam generation technologies: (1) OTSG with no electric power co-production and (2) cogeneration of steam and electric power using a modern simple cycle gas turbine with HRSG.21 Two cases are examined for simple steam generation (low = high efficiency and low environmental impact; high = low efficiency and high environmental impact). For the co-generation cases, a baseline case is calculated, as well as low and high bounding cases. Also included is a no-export version of the base case, wherein only enough electricity is produced to satisfy the onsite demand, thus eliminating electricity exports. Steam characteristics and SORs for generic cases are given in Table 1.24 The SORs range from 3 (good) to 6 (marginally economic). The generic co-generation cases assume modern, efficient cogeneration systems. Turbine performance is as specified by Kim, including a mid-performance turbine and a “current state of the art” turbine.25 These generic cases use Kim’s turbines B and C (in high and low co-generation cases, respectively), with their average used in the baseline co-generation case. For turbines B and C, ηelect,B = 0.309 and ηelect,C = 0.361, specific power = 274.2 and 382.5 kJ/kg, and turbine exhaust temperatures = 545 and 607 °C, with compressor and exhaust pressure losses of 4% in both cases, respectively.25 Hot exhaust gas is transferred to a HRSG, which transfers thermal energy to steam with radiative losses of 2.5% and outlet temperatures of 150 °C.26 The resulting efficiencies (HHV basis) are plotted in Figure 2.

slate, and auxiliary fuels consumed in refining (e.g., source of supplemental H2). Currently available fuel cycle models, such as the GREET model from Argonne National Laboratory, do not allow for variation in refinery GHG emissions with crude quality, a major shortcoming for heavy, high-sulfur crudes produced using TEOR (GREET is not intended to apply to one crude feed stream but, instead, represents U.S. national average crude inputs and refinery conditions). To overcome this difficulty, emissions from refining are calculated using a linear model of GHG emissions as a function of American Petroleum Institute (API) gravity (Figure 3).6 This linear model is fit to data derived from Figure 15-5 of Keesom et al.6 Keesom et al. provide energy inputs and outputs for model refinery runs of 11 crude streams, ranging in API gravity from 8.4 to 36.6° API. Figure 3 shows two linear fits to the data. The right axis reflects the GHG intensity of refined gasoline, which takes into account the distribution of emissions to refined products and is shown on a per megajoule basis. The model uses the ratio between crude feed inputs and product outputs for Arab medium crude to RBOB (see Table 5.17 in Keesom et al.).6 The value is ≈1.15 MJ of crude feed/MJ of product outputs. This ratio between products and crude feed will differ by crude input stream and product slate output. See the Supporting Information for more details on the emission model accounting for upstream, refining, and combustion emissions. Comparing the aggregate energy flows between Keesom et al. and Energy Information Administration (EIA) data provides a helpful assessment of the comparability of the two approaches.6,23 Figure 4 illustrates energy balances of the overall U.S. refinery mix (including average input crude quality and energy density), as well as those from the Keesom et al. model of refining Arab medium crude. Note that the consumption of external energy inputs (e.g., natural gas consumed for hydrogen production) is larger in the Keesom et al. case, with a corresponding larger production of waste heat. Magnitudes of non-liquid energy outputs (e.g., petrochemical feedstocks) are labeled with δ. Also, aggregate energy flows are only one driver of GHG intensity of refining; other factors, such as fuel mix and refinery configuration (e.g., coking versus hydrotreating), affect the GHG intensity of refining.

(24) Cengel, Y. A.; Boles, M. Thermodynamics: An Engineering Approach, 5th ed.; McGraw-Hill: New York, 2006. (25) Kim, T. S. Energy 2004, 29 (1), 71–85. (26) Ganapathy, V. Industrial Boilers and Heat Recovery Steam Generators: Design, Applications and Calculations; Marcel Dekker: New York, 2003.

(23) Wang, M. Q. Estimation of Energy Efficiencies of U.S. Petroleum Refineries (plus associated spreadsheet); Center for Transportation Research, Argonne National Laboratory: Argonne, IL, March 2008.

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Figure 4. Comparison of Keesom et al. energy balance and U.S. total refinery flows from EIA data. Totals may not sum exactly because of rounding. δ represents the unknown quantity of other products (non-liquid products) produced in the Keesom et al. refinery. Table 3. Generic Case Definitionsa OTSG, low

OTSG, high

co-generation, baseline

co-generation, no electricity export

co-generation, low

co-generation, high

technology

OTSG

OTSG

SOR API gravity of crude (deg) steam heat content (MJ/bbl) steam efficiency percentage, ηsteam electricity efficiency percentage, ηelect co-generation efficiency percentage, ηcogen electricity production driven by

3 15 325 85

6 15 337.5 80

SCGT co-generation 4.5 15 337.5 45.3 33.5 78.8

SCGT co-generation 4.5 15 337.5 45.3 33.5 78.8

SCGT co-generation 3 15 325 45.0 36.1 81.1

SCGT co-generation 6 15 350 45.7 30.9 76.6

steam demand

power demand

steam demand

steam demand

a

Efficiencies are on a LHV basis. In all cases, displaced power is from natural gas combined cycle (NGCC).

addition to NGCC are studied, because the marginal resource can vary considerably by location and analysis approach taken. Alternative cases include pulverized coal, U.S. average, California average, as well as a NGCC and new renewables mixture.30 California-Specific Cases. Three California-specific cases are also analyzed (see Table 4 for case definitions). Ideally, such cases would be based on a production-weighted average of all California TEOR projects, but data limitations prevent the creation of such an aggregate result (see the Supporting Information for additional discussion of calculations and data availability for California TEOR). The analysis cases include an average California-specific case, as well as high and low bounding cases. These cases generate bounding parameters from two large California TEOR fields (Midway-Sunset and Kern River). Data used include 48 California TEOR co-generation projects, of which 3 are discarded as outliers. These projects had atypical (very high) electric/steam ratios, suggesting that they are primarily power generation facilities, with minor amounts of steam co-production. Such facilities are not typical of thermal EOR projects and were therefore removed. The power generation efficiencies (ηelect) implied by reported power capacities and fuel consumption rates reported to the CDC-DOGGR are plotted as a histogram in Figure 5A,18 while the actual operating efficiencies for 40 of the 45 projects were computed from EIA generation and fuel consumption

For the generic co-generation cases, there is uncertainty associated with varying the amount of electricity exported to the grid. Generic co-generation cases assume that enough power is generated to co-generate the required amount of steam for EOR. The generic no-export case assumes that only enough power is generated to power onsite operations (e.g., 20 kWh/ bbl), while the rest of the steam is provided by duct firing of natural gas in the HRSG. For refining in the generic cases, crude quality is assumed to be 15° API. The emissions from refining 15° API gravity oil are bracketed in the low and high bounding cases by the 95% prediction interval associated with the fitted linear regression model ((1.3 g of CO2/MJ). Power Generation Mix. A range of power generation resources for displaced power are studied. Several approaches have been taken on displaced power in WTW LCA studies.15,27-29 The generic cases assume displacing NGCC power, which has the advantage of maintaining a system boundary that involves only natural gas as fuel for the TEOR and power generation system. This approach is consistent with a marginal analysis used in most fuel LCA studies. The results for several fuel types in (27) Edwards, R. Well-to-Wheels Analysis of Future Automotive Fuels and Powertrains in the European Context: Well-to-Tank Report; JRC/ CONCAWE/EUCAR: Luxembourg, 2000. (28) Unnasch, S.; Browning, L.; et al. Refinement of Selected FuelCycle Emissions Analyses: Final Report; California Air Resources Board (CARB): Sacramento, CA, 2001. (29) California Air Resources Board (CARB). Detailed CA-GREET Pathway for California Reformulated Gasoline Blendstock for Oxygenate Blending (CARBOB) from Average Crude Refined in California; CARB Stationary Source Division: Sacramento, CA, Feb 27, 2009.

(30) California Air Resources Board (CARB). Detailed CaliforniaModified GREET Pathway for California Average and Marginal Electricity; CARB Stationary Source Division: Sacramento, CA, Feb 27, 2009.

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Table 4. California-Specific Case Definitionsa

OTSG fraction (%) SCGT co-generation fraction (%) SOR API gravity of crude (deg) steam heat content (MJ/bbl) OTSG steam efficiency percentage, ηsteam co-generation electricity efficiency percentage, ηelect co-generation steam efficiency percentage, ηsteam co-generation total efficiency percentage, ηcogen fuel for steam production displaced electricity fuel type a

CA, average

CA, low

CA, high

60 40 5.13 17.3 337.5 82.5 26.9 39.2 66.1 natural gas NGCC

20 80 3.08 13.1 325 82.5 30.2 34 64.2 natural gas NGCC

66 33 5.23 18.2 350 82.5 25.8 45.3 71.1 natural gas NGCC

Efficiencies are on a LHV basis.

43% of the reported steam injected could be produced. Therefore, in the California-specific average case, 60% of California steam is assumed generated at OTSG facilities and 40% at SCGT co-generation facilities, with a statewide-average producing SOR of 5.13 bbl of steam/bbl of oil by Table 2. Low and high California-specific cases are created using data from the Kern River and Midway-Sunset fields (see Table 4). The fraction of co-generation versus OTSG was calculated similarly to the California-wide case.33 Steam generation capacities reported for the Midway-Sunset field indicate that ≈33% of the steam would be able to be co-generated, while in the Kern River field ≈80% could be co-generated. SORs and crude qualities for these fields are also listed in Table 4. In both of these cases, we assume SCGT co-generation. The California average case uses the production-weighted average API gravity for California as a whole, using data from Table 2. The California low and high cases use API gravities of crude from Kern River and Midway-Sunset fields.

Results and Discussion Generic Cases. The resulting emissions from the generic cases are presented in Figure 6. A large range occurs between gross impacts of generic cases. The net impacts exhibit a much smaller range. For example, In the case co-generation, low, large amounts of electric power are co-produced using natural gas, which then offsets electric power from CCGT and reduces net emissions. In the no-electricity export cases, gross emissions are lower because less power is produced but net emissions are higher, reflecting the lack of offsetting benefit from power production. To explore the uncertainty in the co-generation emission results, Figure 7 explores causes of emission variation, with changes presented relative to the base co-generation case. Important factors were found to be the type of power offset and the fuel source used and, secondarily, the SOR. The inclusion of coal, as either a displaced power source or the fuel for TEOR, causes wide variation in net emissions. The effect of SOR is dampened by co-generated power; a higher SOR results in more displaced power from the grid, partially offsetting the higher steam requirement. California-Specific Cases. Results from California-specific cases are shown in Figure 8. Note that the net emission result from the California case is within the generic case range. The displaced power is assumed to be NGCC power, the marginal power source on the California grid. California LCFS calculations were performed using a NG/21% renewable portfolio standard mix.

Figure 5. Power generation efficiencies (ηelect) for California cogeneration projects. (A) Efficiencies implied by rated power capacity and fuel consumption rates, as reported by CDC-DOGGR18 data sets. (B) Actual operating efficiencies calculated from EIA electricity generation and fuel consumption data.31,32

data, plotted in Figure 5B.31,32 In the average California-specific case, co-generation efficiencies equal the average efficiency, weighted by steam production capacity. Realized efficiencies in the California-specific cases are lower than the default cases, because of these systems being installed largely in the 1980s and early 1990s when gas turbines were less efficient. Because of air quality regulations, virtually all steam production in California is fueled with natural gas (with ≈5% fired with coal and petroleum coke). Additionally, if all co-generation facilities operated at rated steam production capacities, at most (31) Energy Information Administration (EIA). Annual Electric Generator Data;Form EIA 860 Database; EIA: Washington, D.C., 2009. (32) Energy Information Administration (EIA). Existing Generating Units in the United States by State, Company and Plant, 2006; EIA: Washington, D.C., 2009.

(33) California Department of Conservation: Division of Oil, Gas, and Geothermal Resources (CDC-DOGGR). Annual Report of the State Oil and Gas Supervisor; CDC-DOGGR: Sacramento, CA, 2005.

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Figure 6. Generic case results from the TEOR emission model (LHV basis). Net emissions include full fuel cycle with credit for co-produced electric power.

efficiencies are due to higher electricity production efficiencies (compare 30.9 and 36.1% to 26.4%) and higher turbine exhaust temperatures, where modern turbines modeled have exhaust temperatures of 545 and 607 °C, as compared to the exhaust temperature reported by Berry and Good of 505 °C.21 Regulatory Impacts of Comparison to Conventionally Produced Crude Oils and Other Transportation Fuel Pathways. These emission estimates are compared to those from the GREET model for conventional oil production in Figure 9. This figure includes the full uncertainty range, including the potential for displacing coal-fired electricity (resulting in reduced emissions compared to conventional oil). Note that TEOR emissions are generally higher, except in cases where significant power exports displace coal power from the grid. Note that the use of TEOR without co-generation increases per megajoule of GHG emissions to ≈125% of those from conventional crude oil, while the use of co-generation can result in emissions that are as low as conventional oil production emissions (or even lower in the case of displacing 100% coal electricity, as seen in Figure 7). Given that many argue that the marginal fuel resource is no longer conventional petroleum, it is also of use to compare TEOR-produced fuels to fuels from other hydrocarbon sources. Figure 9 compares TEOR life-cycle emissions to those from tar sands,34 carbon-dioxide-based enhanced oil recovery (CO2 EOR),35 oil shale,36,37 and coaland gas-based synthetic fuels.38 CO2 EOR can exhibit a wide range of CO2 emissions, depending upon the operational parameters. The referenced values are for current operations, where CO2 sequestration is not emphasized. Under

Figure 7. Effect of variation in model parameters, relative to the cogeneration base case (see Figure 6). The effect of SOR varies with displaced power type (e.g., in cases where coal electricity is displaced, net emissions decline with increasing SOR). Coal and produced oil fuel source cases assume fuels are burned in a cogeneration system with efficiency equal to other cases. This is strictly not true, because they would be used in a boiler-based co-generation system (with somewhat different steam/power output ratios), but this simplifying assumption is made for comparability to other cases.

A key difference between the California and generic cases is the efficiency of the combined cycle systems. California co-generation systems were installed in the 1980s and 1990s and, therefore, will have efficiencies closer to those reported by Berry and Good than the generic cases, which are based on more modern turbines (see Figure 2 or compare efficiencies in generic co-generation cases to efficiencies reported for CA median case in Tables 3 and 4). These higher

(34) Charpentier, A. D.; Bergerson, J.; et al. Environ. Res. Lett. 2009, 4 (014005), 14. (35) Jaramillo, P.; Griffin, W. M.; McCoy, S. T. Environ. Sci. Technol. 2009, 43 (21), 8027–8032. (36) Brandt, A. R. Environ. Sci. Technol. 2008, 42 (19), 7489–7495. (37) Brandt, A. R. Energy Fuels 2009, 23 (12), 6253–6258. (38) Jaramillo, P.; Griffin, W. M.; Matthews, H. S. Environ. Sci. Technol. 2008, 42 (20), 7559–7565.

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Figure 8. California-specific case results (LHV basis). Net emissions include full fuel cycle with credit for co-produced electric power.

This variation between TEOR and other fuel sources has effects on proper interpretation of life-cycle GHG emissions from these fuels, as well as on the policy considerations involved in assigning GHG emissions to fuels for regulations such as the LCFS.1,2 Policy considerations include calculating baseline emissions for regulatory benchmarks, grandfathering of high-carbon-intensity crude oils, and the determination of the displaced electricity carbon intensity. First, policies must include the carbon intensity of thermally produced oil in baseline GHG estimates for produced fuels. When these fuels are included in the baseline, producers could meet percentage reductions in fuel GHG intensity by improving the efficiency of TEOR (through cogeneration, for example) or shifting production from TEOR to other production technologies. California regulations (CA LCFS) address TEOR by including it in the baseline assessment of the GHG intensity of conventional fuels. Another key determinant of emissions from TEOR for regulatory purposes is the treatment of credits for co-produced electricity. The proper value of these credits will vary greatly depending upon the location of production and the time of day. Different assumptions can be made for the fuel mix displaced by co-produced electricity, including national average fuel mix, regional (grid-scale) average, regional (grid-scale) marginal electricity source, and regional longrun displacement. The national average fuel mix has been used previously for convenience, but it offers a poor representation of actual impacts. Despite the straightforward ordering suggested by Figure 9, uncertainty exists with regard to which oil alternative allows the lowest GHG fuel production. For example, there is potential for co-generation or carbon capture and storage for some fuels (e.g., CTLs), which may or may not be included in the cited life-cycle GHG estimates. Additional work should be performed to analyze the global TEOR emission profile, as well as to study mitigation methods that might reduce these emissions. Possible mitigation options include fuel switching of natural gas for produced oil or coal or the application of solar-thermal steam

Figure 9. GHG emissions from TEOR compared to a variety of fossil-based substitutes for conventional petroleum. The range for TEOR is from Figure 7, with coal electricity displacement on the low end and coal-fired TEOR on the high end. Comparisons are necessarily approximate, because system boundaries and treatment of co-produced electricity differ between studies. The conventional oil value is from GREET.15 CO2 EOR values and gas-to-liquid (GTL) and coal-to-liquid (CTL) values are from Jaramillo et al.,35,38 including upstream extraction GHG emissions from extraction of natural gas or coal. Tar sands values are from Charpentier et al., and values from GREET and GHGenius models (low and high, respectively) are for both mining and in situ.34 Values for oil shale are for in situ conversion (low) and ex situ conversion (high).36,37,41

carbon regulation, projects would be operated as joint oil production/CO2 sequestration projects and would result in higher volumes of CO2 sequestered. (39) Green, D. W.; Willhite, G. P. Enhanced Oil Recovery; Society of Petroleum Engineers: Richardson, TX, 1998. (40) California Department of Conservation: Division of Oil, Gas, and Geothermal Resources (CDC-DOGGR). California Oil and Gas Fields; CDC-DOGGR: Sacramento, CA, 1982-1998; Vol. 1-3, p 1500. (41) Brandt, A. R.; Boak, J.; Burnham, A. K. Carbon dioxide emissions from oil shale derived liquid fuels. In Oil Shale: A Solution to the Liquid Fuels Dilemma; Ogunsola, O., Ed.; American Chemical Society: Washington, D.C., 2010; ACS Symposium Series, Vol. 1032, pp 219-248.

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generation for EOR, which could result in significant emission reductions.

of the California Air Resources Board or California Energy Commission.

Acknowledgment. This research is an extension of work funded by the California Air Resources Board and the California Energy Commission at Life Cycle Associates LLC. These calculations are the work of the authors and do not represent the views

Supporting Information Available: Analysis methods and details of California-specific data sets used in this study. This material is available free of charge via the Internet at http:// pubs.acs.org.

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