financial return and energy return on investment …financial return and energy return on investment...
TRANSCRIPT
Accepted Manuscript
Financial Return and Energy Return on Investment Analysis of Oil Sands, Shale Oil and Shale Gas Operations
Ke Wang, Harrie Vredenburg, Ting Wang, Lianyong Feng
PII: S0959-6526(19)30728-0
DOI: 10.1016/j.jclepro.2019.03.039
Reference: JCLP 16043
To appear in: Journal of Cleaner Production
Received Date: 15 July 2018
Accepted Date: 04 March 2019
Please cite this article as: Ke Wang, Harrie Vredenburg, Ting Wang, Lianyong Feng, Financial Return and Energy Return on Investment Analysis of Oil Sands, Shale Oil and Shale Gas Operations, (2019), doi: 10.1016/j.jclepro.2019.03.039Journal of Cleaner Production
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT
Financial Return and Energy Return on Investment Analysis of Oil Sands, Shale Oil and Shale Gas Operations
Ke Wang
School of Business, China University of Petroleum (Beijing), Beijing 102249, China
Haskayne School of Business, University of Calgary, Calgary T2N1N4, Canada
Harrie Vredenburg
Haskayne School of Business, University of Calgary, Calgary T2N1N4, [email protected]
Ting Wang
School of Business, China University of Petroleum (Beijing), Beijing 102249, China
Lianyong Feng*
School of Business, China University of Petroleum (Beijing), Beijing 102249, China
* Corresponding author. Tel.: +86 13911236801 Email address: [email protected] (L.Y. Feng).
ACCEPTED MANUSCRIPT
1
Financial Return and Energy Return on Investment Analysis of Oil
Sands, Shale Oil and Shale Gas Operations
Ke Wang a, b, Harrie Vredenburg b, Ting Wang a, Lianyong Feng a,*
a School of Business, China University of Petroleum (Beijing), Beijing 102249, China
b Haskayne School of Business, University of Calgary, Calgary T2N1N4, Canada
Abstract: People’s focus on either financial benefit or ecological benefit makes decisions on
unconventional oil and gas extraction hard. This paper combines the energy return ratio with the
financial return ratio through a comprehensive analysis model, which is more parsimonious and
more objective than other comprehensive analysis models. The model was applied to analyze the
comprehensive energy/financial efficiency of seven sample unconventional petroleum (oil and
gas) companies in North America. Among them, 4 are oil sands operating companies with the
largest oil sands production and 3 are shale oil and shale gas operating companies with the
largest number of drilled but uncompleted shale wells, and complete available data. Results of
our analysis indicated that during the most recent seven years the selected companies' energy
return ratio and financial return ratio of unconventional oil and gas extraction operations show
obviously different tendencies as a result of oil price fluctuations. However, their comprehensive
energy/financial efficiency indicators showed no significant trend, which was different from the
cases for either one of the individual indicators. We demonstrated that a comprehensive indicator
combining both energy and financial efficiency indicators could be more accurate than either one
* Corresponding author. Tel.: +86 13911236801Email address: [email protected] (L.Y. Feng)
ACCEPTED MANUSCRIPT
2
of them individually, to measure the sustainability and the true value of a company or business
unit, recognizing both economic and biophysical value. We concluded by suggesting that the
energy return on investment indicator and the comprehensive efficiency indicator both be
disclosed and audited along with financial and commodity reserves metrics. Such a summary
statistic will be more useful for investors and public policy analysts than the various energy
efficiency statistics buried in the Global Reporting Initiative (GRI) reports voluntarily produced
by various companies. We argued that this summary statistic would provide incentives for
companies to innovate and to improve efficiency as well as meet public policy objectives in
energy and environment even when the commodity price makes it easier to meet financial
objectives.
Key words: Energy Return On Investment; Return On Equity; oil sands; shale oil and shale gas;
energy economics; North America
1. Introduction
Oil sands, shale oil and shale gas, three types of unconventional hydrocarbons, are mainly
produced today in North America (IEA-ETSAP,2010). In recent years, the ‘shale revolution’ in
the United States and Canada has dramatically impacted the energy world. Concurrently, but
with a longer developmental time line, the oil sands industry in Canada has been ramping up oil
production at a rapid rate (CAPP, 2017). These unconventional oil and gas resources are
important to the world energy market as they represent large new sources of supply and they are,
arguably, the main cause of the dramatic rebalancing of global oil and gas markets since late
2014.
ACCEPTED MANUSCRIPT
3
However, there are heated discussions in terms of the extraction of these unconventional
oil and gas resources, especially in recent years, when the world’s concern for climate change
soared and the oil price dropped dramatically since mid-2014 (EIA, 2018). Different groups of
people focus on different aspects of the issue: unconventional oil and gas companies tend to
focus mainly on economic benefit for their stakeholders from the resource extraction, while
environmental groups mainly focus on the ecological issues in the extraction of unconventional
oil and gas. This makes development and investment decision on these resources from a policy
perspective difficult. To make the decisions easier and fairer, this paper tries to develop a more
comprehensive efficiency indicator, which combines both the financial return ratio and energy
return ratio.
Each of the financial return ratio and the energy return ratio has its own limitations. The
fluctuating commodity price has arguably caused distortions in the metrics, primarily financial,
customarily used to assess performance of oil and gas companies, especially those operating in
the new so-called unconventional part of the industry, typically oil sands, shale oil and shale gas.
Therefore, we argue that perhaps this is the time and place to rethink the metrics investors and
public policy makers use to assess these new industry players by combining customary financial
metrics used in the industry with the energy efficiency metric of energy return on investment
developed in the field of energy economics.
Hall et al. (1981) first introduced the concept and term of energy return on investment
(EROI), which refers to the energy returned to the economy and society compared to the energy
required to obtain that energy (Hall and Klitgaard, 2012). Now, EROI is used more and more
frequently by energy researchers concerned with energy efficiency and public policy (Agostinho
and Ortega, 2013; Brandt et al., 2015; Cavalett and Ortega, 2010; Kong et al., 2016a; Kong et al.,
ACCEPTED MANUSCRIPT
4
2018). EROI is a more objective reflection of the efficiency and value of energy extraction. It
overcomes the potential biased conclusion that could be obtained by some people who only
focusing on the financial return ratio. However, EROI by itself is not sufficient to offer
comprehensive information to support investment decision-making (Grandell et al., 2011;
Murphy and Hall, 2010; Shen et al., 2010). As was noted by King and Hall (2011), any energy
producing entity (EPE, i.e., private or publicly-listed public company, national oil company, etc.)
must produce both monetary and energy profit. In addition, Murphy and Hall (2010) further
noted that “to take an ecumenical perspective it is probably best to undertake both financial and
EROI analyses” (P. 103). However, no research has yet been done to respond these calls. Our
paper tries to fill this gap by combining EROI and financial return ratios together into a
comprehensive efficiency indicator. We argue that combining these two disparate metrics will
provide a more accurate assessment of the worth of energy extraction. We also argue that
requiring the reporting of this combined metric by public companies, duly third-party audited
and approved by corporate boards of directors, analogous to strictly financial and reserves
metrics, will not only provide incentives for companies to innovate and improve performance,
but also help support public policy decisions about energy. The Royal Dutch/Shell Nigerian
reserves write-down experience of 2003 and the standardized audited reserves reporting (Webb,
2008) that resulted from it has set an example and provided evidence of the possible positive
impact of standardized and audited reporting of the energy return on investment indicator,
combined with a financial return on investment indicator.
Next, we apply the combined financial and energy efficiency indicator, as well as the
existing individual financial return indicator and energy return indicator, to the operating firm
ACCEPTED MANUSCRIPT
5
level analysis in the newest commercialized oil sands and shale oil and shale gas segments of the
unconventional hydrocarbon industry.
2. Methods and Data
2.1 Methods
People’s focus on only one side of environmental benefit and ecological benefit has made the
investment and development decisions on unconventional oil and gas difficult from a policy
perspective. Therefore, we believe that a comprehensive indicator is needed. In this paper, we
used a comprehensive analysis model which combines the energy return ratio and financial return
ratio together by giving each of the two ratio the same weight. This model is better, we believe,
than the other commonly used comprehensive analysis models in several aspects.
The currently commonly used comprehensive analysis models include the analytic
hierarchy process, the fuzzy synthetic evaluation method, and the grey decision-making model
(Calabrese et al., 2016; Liang et al., 2016; Wu et al., 2017). Most of these models, we assert, are
too complex (sometimes un-necessarily) to be generalized for implementation by government or
companies. In contrast, our model is simpler and better follows the “parsimony” principle of
model building (Giere, 2004; Guilhoto, 2017; Ham and Golparvar-Fard, 2013). In addition, the
commonly used comprehensive analysis models would mostly include subjective evaluations,
thus are always subject to the effects of subjective biases. Contrarily, our model, though simple, is
more objective in reflecting the comprehensive efficiency information. Lastly, our model is more
suitable for cases where limited amounts of data are available, thus has broader applicability.
ACCEPTED MANUSCRIPT
6
There are various ways to measure either energy efficiency or financial efficiency. The
tools that are usually used to measure energy efficiency include simple energy efficiency ratios,
Total Factor Energy Efficiency Index, Data Envelop Analysis and Life Cycle Analysis (Fan et al.,
2017; Von Blottnitz and Curran, 2007). Though some of these tools are quite widely used, often
times, economic factors are still blended into them. Therefore, the calculated results through these
models do not always represent the uncontaminated objective information about “energy return on
energy investment”. In addition, these models can be quite complex and they require much
detailed and hard-to-access information, thus making them difficult to be widely employed. In
contrast, EROI is a parsimonious method to measure energy efficiency since, on the one hand, it
is based on purely objective energy information, while on the other hand, data needed to calculate
EROI is currently required by the Global Reporting Initiative (GRI). More and more companies
are participating in GRI reporting and are disclosing this information. Therefore, EROI is a
method that reflects more objective energy efficiency information, that is easier to implement and
also more comparable among different firms.
The commonly used methods to evaluate financial efficiency include: Key Performance
Indicator, DuPond analysis, Economic Value Added analysis and Balanced Scorecard analysis
(Gumbus and Lussier, 2006; Mittal et al., 2008; Parmenter, 2015; Soliman, 2008). One common
factor among these methods is that they are all based on some financial return ratios. Among
those ratios, the Return on Equity ratio (ROE) is a standard ratio that measures the profitability of
an investment used for profit creation in a corporation and is most-commonly employed to do
financial return analysis for corporations (Satchwell et al., 2015; Won, 2007). Therefore, we use
the ROE ratio to measure financial return in our study.
ACCEPTED MANUSCRIPT
7
2.1.1 Energy Return on Investment
EROI is a useful tool to carry out net energy analysis and to examine the energy efficiency
from a public policy perspective of extracting an energy resource (Murphy and Hall, 2010). The
original and basic equation for calculating EROI is as follows (Hall and Klitgaard, 2012; Murphy
et al., 2011)
(1)𝐸𝑅𝑂𝐼 = 𝐸𝑛𝑒𝑟𝑔𝑦 𝑟𝑒𝑡𝑢𝑟𝑛 𝑡𝑜 𝑠𝑜𝑐𝑖𝑒𝑡𝑦
𝐸𝑛𝑒𝑟𝑔𝑦 𝑅𝑒𝑞𝑢𝑖𝑟𝑒𝑑 𝑡𝑜 𝑔𝑒𝑡 𝑡ℎ𝑒 𝑒𝑛𝑒𝑟𝑔𝑦
Nevertheless, results of the calculation, even for the same kind of energy resource, could
be very different due to the different boundaries of analysis used (Mulder and Hagens, 2008). To
deal with this problem, Mulder and Hagens (2008) put forward a consistent theoretical
framework for EROI analysis, which was then further developed by Murphy et al. (2011). As a
result, a more explicit two-dimensional framework for EROI analysis was proposed and the term
standard EROI (EROIstnd) was created. EROIstnd is defined as the ratio between energy output at
the mine or well mouth and direct plus indirect energy inputs and can be represented as the
following equation:
(2)𝐸𝑅𝑂𝐼𝑠𝑡𝑛𝑑 =𝐸𝑜
𝐸𝑑 + 𝐸𝑖
Where Eo represents the sum of energy outputs expressed in the same units, while Ed and
Ei represent the total direct energy input and indirect energy input, respectively. Getting indirect
energy input (Ei) is challenging since this data is usually not available directly. However,
including it in the EROI model is very important. On the one hand, indirect energy is truly a
necessary part of energy input; on the other hand, recent EROI papers all tend to include indirect
energy input, especially for the EROI papers published after 2011, when a fairly formal
framework for EROI analysis is defined. Different methods have been tried to estimate Ei (Hu et
ACCEPTED MANUSCRIPT
8
al., 2013; Kong et al., 2015; Poisson and Hall, 2013), but most of them are approximations and
not entirely reliable. This paper uses the Environmental Input-Output (EIO) model, the method
we consider most defensible to date, to analyze indirect energy input.
The EIO model is extended from the standard Leontief Input-Output (IO) model in order
to capture energy consumption flows in the economy from a supply chain perspective (Leontief,
1970). Detailed framework description of embodied energy analysis using the EIO can be found
in (Rocco and Colombo, 2016; Liu et al., 2012, Wang et al., 2017). A simplified description of
the essential processes is as below.
The first step is to calculate the total output of one economy:
X =AX + y (3)
Within this function, X is the total economic output vector; y is the final demand vector;
and A is the economy’s direct demand matrix. The demand matrix A describes the relationship
between all sectors of the economy.
Assuming that (I-A) is non-singular, then the total economic output vector X can be
expressed by Eq. (4):
(4)X = (𝐼 ― 𝐴) ―1𝑦
Within this function, I is the identity matrix, is the Leontief inverse. Eq. (4) (𝐼 ― 𝐴) ―1
illustrates the gross output needed to satisfy both the final consumption ‘‘y’’ and the
corresponding intermediate consumption “ ” from each economic sector.(𝐼 ― 𝐴) ―1
ACCEPTED MANUSCRIPT
9
Next, we combined the economic IO model with sectoral embodied energy input by
multiplying the total economic output by each sector’s energy intensity1.
We use E (1×n) to represent the direct energy inputs for each sector from the perspective
of sectoral production, then, the factor vector of the direct energy intensity for each sector, Ω
(1×n), can be represented as: to represent
(5)Ω𝑖 =𝐸𝑖
𝑋𝑖
And the indirect energy consumption per unit of economic output of each sector within
the country, ε (1×n), can be represented as:
(6)𝜀 = Ω((𝐼 ― 𝐴) ―1 ―𝐼)
Research has been done to calculate energy return on investment of oil sands, shale oil
and shale gas extraction at the industry level (Aucott and Meillo, 2013; Brandt et al., 2015;
Wang et al., 2017). However, most data (especially energy input data) used in these industry-
level analyses is simulated and based on rather broad assumptions, and thus may lead to
inaccurate and possibly misleading analyses. However, empirical energy input and energy output
data are available for company-level analysis and can offer better information for more accurate
analysis and more fine-grained public policy insights. These data are usually disclosed by
government regulatory agencies or by companies themselves in their annual corporate social
responsibility (CSR) reports, corporate responsibility (CR) reports or sustainability reports. The
Global Reporting Initiative (GRI) has developed disclosure standards for sustainability reporting
1 Energy intensity mentioned here represents the energy consumption per unit economic output from each sector.
ACCEPTED MANUSCRIPT
10
and by 2015 there were 7,500 organizations using the GRI guidelines (GRI requires companies
to disclose up to 30 energy and environmental indicators) to prepare their sustainability reports.
In addition, the International Petroleum Industry Environmental Protection Association
(IPIECA) and the United Nations Global Compact Council (UNGC) have developed guidelines
to encourage oil and gas companies to disclose energy use and environmental impact data.
Though the energy and environment data published by different energy companies are still not
standardized nor comparable, we do see the trend of increasing availability and accuracy of these
company-level data, as more and more energy companies accepting and following these reports
and standards. In addition, compared with industry-level analysis, which assumes homogeneity
of companies’ performance, company-level analysis focuses on the heterogeneity of performance
of different companies. In other words, with this data it is possible to identify companies that are
performing better and worse with respect to energy efficiency. That, of course, can support
policy makers with more useful information to decide on regulatory incentives and methods to
stimulate technology innovation in the industry to encourage companies to improve their
performance. What’s more, in a world that is increasingly concerned with climate change,
company level analysis can better guide institutional and individual company shareholders to
make investment decisions in companies that perform better on energy efficiency, thereby
providing another economic incentive for firms to improve energy efficiency performance. For
these reasons, EROI analyses at the company level can be argued to be necessary and possibly
more important than EROI analyses at the industry level.
Almost all papers in the EROI literature to date have focused on industry level analysis
(Hall et al. 2014; Hu et al., 2013; Raugei et al., 2012). Only three papers in the extant literature
(Kong er al., 2016b; Nogovitsyn and Sokolov, 2014; Safronov and Sokolov, 2014) focused their
ACCEPTED MANUSCRIPT
11
analyses at the company level. Two of the studies focused on Russian firms and one on Chinese
firms. Considering that company-level analysis is arguably more valuable, we focus on EROI
analysis of shale operating companies and oil sands operating companies in North America. The
boundary of analysis in this paper include only the extraction process of oil sands, shale oil and
shale gas. A simplified version of the engineering process of the extraction of oil sands, shale oil
and shale gas is shown in Figure 1.
Figure 1. Simplified version of the engineering processes of the extraction of oil sands, shale oil
and shale gas
ACCEPTED MANUSCRIPT
12
Note: This figure is partly adapted from figures in Howarth et al. (2011), U.S. Environmental Protection Agency
(2016) and Wang et al. (2017).
2.1.2 EROI, ROE and Comprehensive Efficiency Indicator
While EROI is chosen as an energy efficiency indicator, ROE is chosen to reflect financial return
information of unconventional oil companies in North America. EROI is the most-used indicator
to reflect energy return information of different energy sectors, companies or projects in the
energy economics literature. The ROE is a standard ratio that measures the profitability of an
investment used for profit creation in a corporation, and is commonly employed to do financial
return analysis for corporations (Satchwell et al., 2015; Won, 2007). The equation of ROE is
shown as below:
ROE= (7)𝑛𝑒𝑡 𝑖𝑛𝑐𝑜𝑚𝑒
𝑠ℎ𝑎𝑟𝑒ℎ𝑜𝑙𝑑𝑒𝑟 𝑒𝑞𝑢𝑖𝑡𝑦
For a comprehensive energy/financial efficiency analysis, the non-dimensionalized
(normalized) value of EROI and ROE are multiplied by weights related to their assumed
importance and summed up to arrive at the combined energy and financial efficiency indicator.
The weight distributed to the energy return ratio (EROI) and that assigned to the financial return
ratio (ROE) in this paper are both 0.5, since environment, as represented by EROI to society, and
economy, as represented by ROE to individual financial investors in the economy are assumed to
be equal as advocated by much-cited global policy documents such as the Brundtland report
(Brundtland, 1987).
Since the value scales of EROI and that of ROE are quite different, we have to non-
dimensionalize the two indicator values first in order to make more reasonable energy and
ACCEPTED MANUSCRIPT
13
financial efficiency analysis. Here we choose to use the Min–max normalization, the simplest
normalization technique (Anon, 2015; Jain et al., 2005), to do the non-dimensionalization. Min–
max normalization is best suited for the case where the bounds (maximum and minimum values)
of the scores produced by a matcher are known.
In this case, we can reasonably shift the minimum and maximum scores to 0 and 1,
respectively. However, even if the matching scores are not bounded, we can estimate the
minimum and maximum values for a set of matching scores and then apply the min–max
normalization. Given a set of matching scores , k=1,2,…,n, the normalized scores are 𝑋𝑘
given by
(8)𝑋'𝑘 =
𝑋𝑘 ― 𝑚𝑖𝑛𝑚𝑎𝑥 ― 𝑚𝑖𝑛
2.2 Data collection and handling
A big part of the data used in this paper is obtained from annual reports, corporate social
responsibility (CSR) reports, corporate responsibility (CR) reports and sustainability reports of
each of the companies for the years 2010 through 2016. Another part of the data used in this
paper is obtained from government agencies, e.g., most of the oil sands related data is obtained
from the Alberta Energy Regulator (AER), previously the Energy Resources Conservation Board
of Alberta.
2.2.1 Data of oil sands operating companies
Energy flow data for oil sands operating companies were collected from Statistical Reports (ST)
provided by the AER. AER publishes energy output/input data for in situ oil sands and mining
ACCEPTED MANUSCRIPT
14
oil sands operations separately, and these data are at a project level. We summed project-level
data of oil sands projects belonging to each company to get company-level data. The included
projects of each oil sands operating company for each year are listed in Appendix A.
Energy output data for mining oil sands projects comes from ST 39 (2010-2016),
including: Synthetic Crude Oil (SCO) delivered, bitumen delivered, intermediate hydrocarbons
delivered, paraffinic solvent delivered, diluent naphtha delivered, and electricity exported; while
energy output data for in situ oil sands projects comes from ST 53 (2010-2016), including
bitumen produced and electricity exported. Energy output data is given in different units,
including m3, tonnes and MWh, which are then transferred, based on thermal value of different
kinds of energy output, into the unit of tera joule (TJ) using the transfer indicator given by NEB
(2015) of Canada.
Direct energy input data for mining oil sands projects comes from ST 39, including: coke
(fuel and plant use), process gas (further processing), process gas (fuel and plant use), paraffinic
solvent (fuel and plant use), diluent naphtha (fuel and plant use), Synthetic crude oil (SCO, fuel
and plant use), natural gas purchased, and electricity purchased. The majority of the direct
energy input data for in situ oil sands comes from In Situ Performance Presentation (ISPP)
reports of different in situ oil sands projects in different years (AER, 2010-2016). Since the ISPP
reports of some in situ oil sands projects only give energy consumption data in the form of line
charts or column charts, we used “Engauge Digitizer 4.1” software, where required, to convert
data instead into the form of direct numbers. Direct energy input data of in situ oil sands projects
from ISPP include: natural gas consumption (including natural gas purchased and produced) and
electricity consumption.
ACCEPTED MANUSCRIPT
15
Indirect energy input, which includes energy consumed to run machines, energy used to
generate the steam, inject steam, generate electricity etc., is calculated using the EIO model
described in 2.1.2. Input-Output Tables of the Canadian economy were obtained from the
Canadian Socio-Economic Information Management System (CANSIM) database of Statistics
Canada (2011-2013). Since even the most detailed version (Level L) of the Input-Output table of
Canada only offers data from the “Oil and Gas Extraction” sector, instead of data from the “oil
sands extraction” sector, we were only able to obtain indirect energy intensity for the oil and gas
extraction sector, rather than for the oil sands extraction sector through the EIO model.
Therefore, in our analysis, we used the indirect energy intensity of the oil and gas extraction
industry to replace the indirect energy input intensity of the oil sands extraction sector. In
addition, since the most recently available Input-Output Table is from 2011, we calculated
indirect energy input intensity for the year 2011 and used the same indirect energy input intensity
of 2011 as that of the years following 2011. Production energy consumption (direct energy use)
data, for different sectors of the Canadian economy, was also obtained from CANSIM, Statistics
Canada (2016). A summary of all direct energy input and energy output items considered in this
paper are shown in Appendix B.
The net income of oil sands operations of Suncor Energy Inc., Canadian Natural
Resources Limited (CNRL) and Cenovus Energy Inc. are given directly in their annual reports.
However, it is not possible to directly ascribe shareholder equity for the oil sands business part of
a company as investors buy shares of the entire company including all the company’s business.
Therefore, we estimated the shareholder equity attributable to the company’s upstream oil sands
business by multiplying the shareholder equity of the whole company by the proportion that
upstream oil sands assets represented of total assets of these sample companies. This estimated
ACCEPTED MANUSCRIPT
16
oil sands asset proportion may not equal the oil sands equity proportion for the sample
companies. However, as is noted by Hasan (2013), the size of equity should be proportional to
total asset size for corporations. We hereby consider the use of oil sands asset proportion as a
reasonable estimate.
2.2.2 Data of shale operating companies
All energy output data and some of the direct energy input data of US shale operations are
obtained directly from annual reports, sustainability reports, corporate social responsibility
(CSR) reports or corporate (CR) responsibility reports of the sample companies. For those
companies who do not disclose direct energy input for their US shale business, but only disclose
direct energy input for the whole company (including all business sectors), e.g., Apache
Corporation, and Marathon Oil Corporation in this case, we calculate their direct energy input of
US shale business by multiplying total direct energy input of the whole company (including all
business sectors) by a proportion of shale production (in US) cost (monetary cost) of total
production cost (including production cost of all business sectors) of these companies.
This calculated monetary cost proportion may not exactly be the energy cost (direct
energy input) proportion for the sample companies. However, since the energy use (embodied
energy) is assumed to be proportional to the market-determined dollar value (Gao et al., 2017).
Also, as transformation from monetary cost to energy cost was commonly used in the prior
literature (Kong et al., 2015; Hu et al., 2013), we consider the use of monetary cost proportion as
energy cost proportion here as reasonable.
The indirect energy input is only disclosed by Hess Corporation in its corporate
sustainability reports, so we calculated indirect energy input for US shale operations of the other
ACCEPTED MANUSCRIPT
17
sample companies by multiplying the energy intensity by the capital expenses of shale oil and
shale gas production.
All net income data and most of the shareholder equity data of US shale operations are
obtained directly from annual reports of the sample companies. For those companies who are
engaged in other businesses besides shale oil we calculate their shareholder equity for the part of
US shale business by multiplying the shareholder equity of the whole company with a proportion
of shale assets in the total assets of these companies. This calculated shale asset proportion may
not exactly be the shale equity proportion for the sample companies. However, as is explained in
2.3.1, we consider the use of shale asset proportion as a reasonable estimate.
Marathon Oil Corporation and Apache Corporation are both upstream companies, while
Hess Corporation is an integrated petroleum company and has only started the transformation
into a more focused upstream company since 2010 (Hess Corporation, 2012). Therefore, only
data under the headline “Operations for Oil and Gas Producing Activities” in Hess Corporation’s
reports are used in this paper.
We should note that our analysis results for Marathon Oil Corporation and Apache
Corporation includes the combined results of conventional and unconventional operations in the
United States, since these two companies do not disclose data for conventional operations and
unconventional hydrocarbons in the United States separately. The proportions of conventional oil
and gas production in total production of the two companies for each year are listed in Appendix
C.
ACCEPTED MANUSCRIPT
18
2.3 Sample companies
The four oil sands operating companies used in this paper are Suncor Energy Inc., Canadian
Natural Resources Limited (CNRL), Imperial oil Limited and Cenovus Energy Inc. They are the
largest four companies (ordered by oil sands production of 2016) that are focused on oil sands
extraction in northern Alberta, headquartered in Calgary Canada and have their shares traded on
the Toronto Stock Exchange.
The three shale oil and shale gas companies used in this analysis are: Hess Corporation,
Apache Corporation, and Marathon Oil Corporation. They were chosen based on the data
published by RS (Ross Smith) Energy Group (Doorn, 2016). RS Energy Group ranked the top 10
shale operating companies in each of the four shale basins with the largest number of drilled but
uncompleted wells (DUCs). We have chosen these 3 shale operating companies from the 40
companies based on the data availability of both energy input and output data for shale
operations and the ability to separate shale operating division data from other operating
divisions. These three companies are all on a list of “The 14 Best Stocks for Playing the US
Shale Boom” published by an energy industry investment analyst based at the Swiss bank UBS
(Wile, 2013). Hess Corporation is headquartered in New York City while Marathon Corporation
and Apache Corporation are headquartered in Houston, all in the United States.
More descriptive information of our sample companies is shown in Table 1. The reason
we call the selected companies shale operating companies and oil sands operating companies,
instead of shale companies and oil sands companies, in this paper is that all these companies do
not only focus on one business sector, oil sands or shale oil and shale gas operations, but also
focus on some conventional oil and gas operations. This paper will only focus on the upstream
oil sands or shale operations of these companies.
ACCEPTED MANUSCRIPT
19
Table 1 descriptive information about sample companies
Company name
Headquarter
Location of operations
Firm size (revenue)
Employee number
Firm age
Range of Operations
Unconventional oil and gas production
Total oil and gas production
% of unconventional in total oil and gas production
Apache Corporation
Houston, U.S.
Anadarko and Permian basins, US
US$5.367 billion
3,727 64 Upstream 525 mboe/d 532 mboe/d
99%
Hess Corporation
New York, U.S.
Bakken and Utica, U.S.
US$4.762 billion
2,304 99 Integrated 106 mboe/d 322 mboe/d
33%
MarathonOil
Houston, U.S.
Eagle Ford, Bakken and Oklahoma, US
US$5.522 billion
2,117 131 Upstream 194 mbooe/d 223 mboe/d
87%
Suncor Energy Calgary, Canada
Athabasca, MacKay River and Firebag, Canada
CA$26.807 billion
12,837 99 Integrated 505 mboe/d 623 mboe/d
81%
CNRL Calgary, Canada
Athabasca, Pelican Lake, Wolf Lake and Primrose, Canada
CA$10.523 billion
10,029 45 Upstream 123 mboe/d 820 mboe/d
15%
Cenovus Energy
Calgary, Canada
Athabasca, Cold Lake Canada
CA$12.282 billion
3,500 9 Upstream 153 mboe/d 273 mboe/d
56%
ImperialOil Ltd.
Calgary, Canada
Peace River, Athabasca and Cold Lake, Canada
CA$25.049 billion
5,400 138 Integrated 349 mboe/d 388 mboe/d
90%
Note: 1) The firm size, employee number and production data are all for the year 2016. 2) the
unit mboe in the table indicates 1000 barrel of oil equivalent.
3. Results
Our analysis of sample companies showed different trends for the energy return and financial
return for oil sands operating companies and shale oil and gas operating companies. We show the
ACCEPTED MANUSCRIPT
20
results for oil sands operating companies and shale oil and gas operating companies separately
below.
3.1 Energy/financial efficiency of oil sands operating companies
Figure 2. EROI (left) and ROE (right) of oil sands operating companies
Note: In the legend, Suncor, Cenovus, CNRL and Imperial Oil refer to Suncor Energy Inc., Cenovus Energy Inc., Canadian Natural Resources Limited and Imperial Oil Limited respectively.
According to Figure 2, the EROIs of the four sample oil sands operating companies were
generally flat (with a slight upward trend) during the latest seven years. Cenovus had the highest
EROI, followed by Suncor, Imperial Oil and then CNRL. The differences in EROI might simply
reflect differences in the reservoirs being tapped into. Richer and easier to access reservoirs will
result in a higher EROI. The differences could also reflect differences in production
management. Sloppy and careless production management will result in lower EROI. Whereas
during the ‘boom years’ of oil sands production, when the oil price was over $100, there were
regular business media reports of inefficient production management, that has pretty much
disappeared as a result of the discipline imposed by low oil prices. A third explanation for the
basic differences in EROI could be technology; some companies have developed and are using
more sophiscated and efficient extraction technologies.
ACCEPTED MANUSCRIPT
21
In contrast with the EROIs, the ROEs of the four oil sands operating companies were
more fluctuating during the latest seven years, especially for Cenovus and Imperial Oil. During
the period 2014-2016,when the oil price dropped dramatically, the ROEs of all four oil sands
companies showed downward trends,while the EROIs of the companies, during the same period,
showed little change. This might be because the financial return ratio such as ROE can be
sensitive to oil price changes while energy return ratio is not much affected by oil price changes
compared with the financial return ratio. Interestingly, during 2014-2016, the EROIs of Cenovus,
Imperial Oil and Suncor were all increasing while the ROEs of the two oil sands operating
companies were actually decreasing during that time period. This can be a further illustration of
the significant effect of oil price flucuation.
This situation described above might be more common among oil sands operating
companies since they may have quite different performances and may find themselves at
different stages of technological development in terms of oil sands technology innovation and
corporate environmental sustainability management. In addition, since the financial return ratio
such as ROE can be sensitive to oil price changes, which are difficult to predict, the ROE trend
of oil sands companies can be quite different from the EROI trend. These are reasons why we
believe that it is important to do and report comprehensive energy andfinancial efficiency
analysis for oil sands operating companies.
ACCEPTED MANUSCRIPT
22
Figure 3. Energy and financial efficiency indicator of oil sands operating companies
Note: In the legend, Suncor, Cenovus, CNRL and Imperial Oil refer to Suncor Energy Inc., Cenovus Energy Inc., Canadian Natural Resources Limited and Imperial Oil Limited respectively.
Figure 3 shows the result of our comprehensive energy and financial efficiency analysis
for the four oil sands operating companies during the latest seven years. Our data show that
during 2010-2014, the energy and financial efficiency indicator of Cenovus Energy Inc. and that
of CNRL were generally increasing while the indicators of Suncor Energy Inc. and Imperial Oil
Limited showed no obvious trend. After 2014, the energy and financial efficiency indicators of
all four oil sands operating companies decreased. The data shows that for Suncor Energy Inc,
though its EROI was increasing and its ROE indicator was decreasing during the latest seven
years, its energy and financial efficiency indicator fluctuated without trend generally. The energy
and financial efficiency indicator may well be, we argue, the most comprehensive reflection of
the oil sands operating efficiency of Suncor Energy Inc. The energy and financial efficiency
indicator of Cenovus Energy Inc. was the highest among the four oil sands operating companies
studied. This might be because Cenovus has consistently focused on technology innovation and
ACCEPTED MANUSCRIPT
23
is now regarded as the leader in in situ oil sands extraction technologies (Cenovus, 2016;
Hussain, 2016; McCarthy, 2013).
3.2 Energy/financial efficiency of shale operating companies
Figure 4. EROI (left) and ROE (right) of shale operating companies
Note: (1) In the legend, Hess, Apache, Marathon Oil refer to Hess Corporation, Apache Corporation, and Marathon Oil Corporation respectively. (2) The EROI data of Apache Corporation for 2016 is lost because of incomplete energy consumption data disclosure.
Results of our calculation show that during the latest seven years, the EROIs of Apache
Corporation and of Hess Corporation showed clear increases, while the EROI of Marathon Oil
Corporation basically kept flat. While Apache Corporation’s and Hess Corporation’s EROI were
increasing significantly, their ROE were in decline during the same time period. EROI and ROE
for these shale operating company clearly provided very different information of the company’s
performance.
ACCEPTED MANUSCRIPT
24
Figure 5. Energy and financial efficiency indicator of shale operating companies
Note: (1) In the legend, Hess, Apache, Marathon Oil refer to Hess Corporation, Apache Corporation, and Marathon Oil Corporation respectively. (2) The energy and financial efficiency indicator of Apache Corporation for 2016 is lost because of lost EROI data.
When we examined our comprehensive energy and financial efficiency indicators of the
three shale operating companies, we saw that during 2010-2014, no obvious trend was detected
for Apache Corporation and that the energy and financial efficiency indicator of Apache
Corporation was the highest among the three shale operating companies. But during 2014-2015,
the energy and financial efficiency indicator of Apache Corporation decreased significantly, to
the lowest level among the three shale operating companies. During the most recent seven years,
the energy and financial efficiency indicator of Hess Corporation showed a slight upward trend,
while the energy and financial efficiency indicator of Marathon Oil Corporation was flat. The
comprehensive energy and financial efficiency indicator reflects both energy return information
and financial return information, thus, we argue, might be a more comprehensive reflection of
the energy and economic efficiency of shale operating companies.
ACCEPTED MANUSCRIPT
25
4. Discussion
4.1 Implications for theory and practice
According to the Brundtland report, sustainable development requires the simultaneous
realization of the economic benefit and the ecological benefit (Aljerf and Choukaife, 2016;
Brundtland, 1987). Biased focus on either the economic side or the ecological side would not
lead to sustainable development (Sardianou, 2008; York et al., 2018). The results of this paper
showed that the energy return ratio and financial return ratio for even the same unconventional
oil and gas operating company could be very different and could even show opposite trends,
while a comprehensive efficiency indicator that combines both the two aspects could be a more
unbiased and fair reflection of the value of unconventional oil and gas extraction operations.
These results would make both theoretical contributions and practical contributions.
In terms of theoretical contributions, first, this study contributes to the sustainability
literature by developing a more accurate and comprehensive measure for the sustainability of
unconventional oil and gas extraction operations (Corley and Gioia, 2011). Reporting of this new
measure will make a difference to the relationships between operation sustainability of
unconventional oil and gas extraction and its antecedents and outcomes, such as investment
decisions on unconventional oil and gas extraction, companies’ strategies to enhance operation
sustainability, etc. Second, this paper extended the EROI literature by applying EROI to firm-
level analysis and by proving that EROI, as an additional indicator to the financial return
indicator, can help us get more accurate information while evaluating different upstream
petroleum companies. In addition, in terms of forecasting the future performance of upstream
unconventional petroleum firms, the EROI indicator provides a better assessment than ROE
(ROE relies heavily on the oil and gas prices, but the future prices are extremely difficult, if not
ACCEPTED MANUSCRIPT
26
impossible, to predict. Therefore, the future performance forecast of upstream unconventional
petroleum firms based on ROE may suffer from insufficient accuracy). What’s more, since the
asset value of unconventional petroleum reserves is always affected more heavily than
conventional petroleum by oil price fluctuation (Wang et al., 2016) and the fluctuating oil price
is more vital to the survival of unconventional companies, EROI is perhaps a more needed metric
when unconventional petroleum is considered.
In terms of practical implications, first, this study is helpful to improve the sustainability-
oriented or sustainability-enhancing behaviors by unconventional oil and gas companies. The
power of formal regulation is recognized but the power of formally required reporting of
company operational statistics (i.e. “what gets measured (and reported) gets done (or
improved)”) is sometimes overlooked (Giovannini, 2004; Martinez et al., 2018; Shaffer, 1995).
With a better and formally required measurement and reporting of operational sustainability,
companies will be more likely to adjust their operational behaviors in the direction of sustainable
development (Daly, 2017). Second, this paper emphasized the importance of the EROI metric to
help policy makers and investors get more accurate information to support their decisions, as it
shows more accurate information about the fundamental worth of unconventional petroleum
extraction. As is noted by Hall (2011), since market price sometimes can give inappropriate
signals due to market psychology rather than asset and operating company fundamentals, EROI,
as an energy return ratio, might be a useful indicator for investors and policy makers/regulators
as it reflects scientifically evidenced objective efficiency information. Murphy and Hall (2010)
noted that an EROI analysis should always be carried out comprehensively for any major policy
or economic decision. We argue here that energy companies should disclose not only financial
data, such as the ROE ratio, but also data of energy output, energy input and the EROI ratio.
ACCEPTED MANUSCRIPT
27
Shareholders and societal stakeholders would then have more objective and comprehensive
information about a company’s operating performance. Furthermore, we argue that the EROI
ratio should also be audited by third-party auditors, analogously to a company’s financial and
reserves metrics. By measuring and reporting in a scientifically sound manner the EROI of
energy companies, this reporting will serve as an incentive to improving performance.
We advocate that in order to better align petroleum company energy return on investment
performance with public policy objectives, companies be required to formally report EROI and
the energy and financial efficiency indicator that we illustrated in this paper. By measuring and
publicly reporting such data, companies have an additional market-based incentive to innovate
and improve energy return on investment through efficiency management, technical innovation
or by not attempting to develop reservoirs providing poor energy return on investment.
There is precedent for adding a major reporting requirement for public companies, and
one that has arguably improved information available to investors and public policy overseers
and improved corporate performance. In 2003 Royal Dutch/Shell found themselves in a
challenging situation having to ‘write down’ the value of their Nigerian oil reserves on their
books after it became apparent that they were overstated (Webb, 2008). That scandal provided
the impetus for the requirement for publicly-listed companies in most jurisdictions being
required to have a board of directors-level reserves committee analogous to the long-standing
board financial audit committee that considers and reports to the board on the company’s
reserves. Audit committees review the assessments and professional opinion reports of third-
party auditors (a public accounting firm) and report to the board where the company’s financial
statements are formally accepted by the board. Reserves committees review the assessments and
professional opinion reports of third-party reserves auditors (a petroleum reserves engineering
ACCEPTED MANUSCRIPT
28
firm) and report to the board where the company’s reserves statements are formally accepted by
the board. Companies’ public market valuations are largely based on these two formal board of
directors issued reports.
A board of directors-level energy efficiency committee could similarly review the
assessment and opinion of professional financial and energy efficiency auditors (possibly an
engineering or public accounting firm employing ecological economists and or engineers) and
have this report formally adopted by the board and communicated to financial markets and
government regulators. Firms with favorable indices would be advantaged in the market place.
What we are arguing essentially is a sophisticated version of the old adage: What gets measured
gets acted upon (Giovannini, 2004). Public companies have demonstrated themselves to be
responsive, in terms of management and technological innovation, to formal financial and
reserves reporting and its consequences. We are suggesting that we do the same with energy
return reporting.
While initiatives such as the Global Reporting Initiative (GRI) are attempting to push the
disclosure of more CSR data including energy efficiency data, their potential impact is limited by
the fact that GRI numbers are diffusely divulged in non-standardized reports separate from those
customarily reported in public company quarterly reports. In addition, GRI allows a discretion
for companies to choose from several different energy efficiency indicators to disclose (GRI,
2016). In order to get the appropriate attention of investors and policy makers/regulators, and to
insure the accuracy and comparability of the energy efficiency information, we argue that the
EROI indicator should be taken as the unified energy efficiency indicator and be disclosed
directly on the companies’ financial reports, instead of on companies’ non-standardized reports.
ACCEPTED MANUSCRIPT
29
EROI is not affected as much as financial ratios such as ROE by energy price fluctuation
and therefore can offer more accurate information about the value of energy development.
Though EROI has advantages compared with ROE, it also has its own limitation. Solely focusing
on EROI, while ignoring financial return is biased. That is to say, EROI, by itself, is not
sufficient to offer comprehensive information to support decision making. Only if both energy
analysis and financial analysis are done, will energy investors and policy makers be able to make
comprehensive and rational decisions.
In order to promote sustainable development of our society, we need the simultaneous
achievement of ecological benefit and economic benefit (Aljerf and Choukaife, 2016; York et al.,
2018). Therefore, energy return analysis, we argue, should always be done together with
financial return analysis. Also, we advocate, the energy and financial efficiency indicator we
discussed in this paper should be required to be disclosed and audited.
The current EROI metric used in this paper is mainly aimed at reflecting energy
efficiency and doesn’t include the environmental cost. As is noted by Murphy et al. (2011),
environmental energy input (energy input in mitigating environmental impact) is included in the
5 different types of energy input of EROI indicator. Attempts to consider this environmental
dimension in the EROI calculation is being made by several researchers currently (Aucott and
Meillo, 2013; Chen et al., 2017; Kong et al., 2015). With more work being done in regard to
including environmental energy cost into the EROI indicator, this indicator may become more
accurately aligned with ecological benefit and the energy and financial efficiency indicator will
become a more comprehensive and important indicator in terms of sustainable economic
development (Atlason and Unnthorsson, 2018).
ACCEPTED MANUSCRIPT
30
4.2 Limitations of this paper
This study also suffers from several limitations. First, due to the data limit, we only chose a small
sample size of unconventional petroleum companies as illustrations in this paper. In addition,
sine the sample companies included in our paper are all among the largest ones, they might be
limited while representing companies of other sizes in the industry. Also, all the companies used
in our analysis have multiple businesses (or multiple operations) and specific data (especially
energy input and financial input data) for upstream unconventional petroleum operations are
usually not given directly. Though we focused on companies where the ‘other business’
component was small and we tried our best to objectively estimate the relevant specific data,
there is a risk that the accuracy of the analysis results might be more or less affected. In cases
where the data separation is unavailable, we used the total number to represent the upstream
unconventional petroleum operations. To reduce the risk of misguidance of our result, for these
cases, we have listed the proportion of upstream unconventional petroleum operations of the
companies. These limitations could affect the specific EROI or ROE values calculated in our
paper. However, we wouldn’t speculate a big effect of the data limitation on the core findings of
this paper, which showed how calculating both the EROI metric and the energy and financial
efficiency indicator can highlight the potential difference between the trends of the energy return
ratio and the financial return ratio. Future research based on clearly separated data of
conventional and unconventional operations is needed to confirm our argument. And, of course,
should corporate governance in future require reporting of this nature, un-estimated accurate
corporate data will be required.
Another concern about the result of this paper is, the increasing EROI of North American
oil sands, shale oil and shale gas operating companies could have been caused by reasons other
ACCEPTED MANUSCRIPT
31
than those that have been mentioned in our analysis, for example, the firms shutting down low
EROI plants. This type of firm behavior will lead to even severe drop of their operation EROI
during high oil price period. Since the sustainable comprehensive return, instead of dramatic
drop, is our expectation, attention should be paid on the potential future drop of EROI
unconventional oil and gas extraction. Besides, the reasons of the different financial and energy
return on investment value of different companies have not been deeply analyzed in this paper.
Future research is expected to do more comprehensive and detailed analysis since the reasons
might be valuable to policy makers to stimulate innovations and thus operating performances of
unconventional oil and gas extraction forms.
The effects of technology uncertainty on the results of our study should also be
considerable question. However, we suspect that though the specific EROI and ROE values
could be sensitive to technology uncertainty, the general trend of the ratios would not be affected
much, since the technology uncertainty would always apply to each sample company and each
time period. Since the main focus of this study is the general trend, instead of the specific value
of EROI, ROE and comprehensive efficiency value in one specific time, the technology
uncertainty issue wouldn’t be a big concern.
The generalizability of this study’s results could also be arguable. It is possible that
different countries will have different data on specific numbers of the indicators discussed in this
study. However, based on our theoretical argument about the inconsistency of the trends of
energy return ratio and financial return ratio caused mainly by the significant effect of oil price,
and also based on similar arguments by other researchers (Hall and Klitgaard, 2012; Murphy et
al., 2011), we speculate that the findings in our study will not be very different among cases of
different countries or different types of unconventional oil and gas resources.
ACCEPTED MANUSCRIPT
32
5. Conclusion
The intention of this paper is to explore the nature of the energy return on (energy) investment
(EROI) and the financial return on equity investment (ROE) relationship at the operating firm
level in the newest commercialized unconventional oil sands and shale oil and shale gas
segments of the hydrocarbon industry. Results of our study show that EROI and ROE sometimes
show different tendencies for North American unconventional petroleum companies. During the
most recent seven years the energy and financial efficiency indicator of Cenovus Energy Inc.
was higher than that of Canadian Natural Resources Limited and Suncor Energy Inc. The energy
and financial efficiency indicator of all four oil sands operating companies show no significant
trend; the energy and financial efficiency indicator of Apache Corporation, highest among the
three sample shale operating companies, shows a downward trend, while the energy and
financial efficiency indicators of Hess Corporation and Marathon Oil Corporation are quite
similar and both of them show no significant trends.
ROE sometimes gives incomplete information since it is, to a large extent, influenced by
commodity prices, which could sometimes give wrong market signals about the value of a
resource extraction operation. As a contrast, EROI is based on objective physical energy data,
which is not affected much by oil price changes, and thus can show more accurate information
about the fundamental worth of unconventional petroleum extraction. In addition, in terms of
forecasting the prospectiveness of a specific type of energy extraction, the EROI indicator
provides a better assessment than ROE. The reason is that energy price is difficult to predict,
while the forecast of ROE relies heavily on the energy price forecast, so the ROE forecast result
may suffer from insufficient accuracy. What’s more, since unconventional petroleum is always
ACCEPTED MANUSCRIPT
33
affected more heavily than conventional petroleum by oil price fluctuation (Wang et al., 2016),
EROI is perhaps a more needed metric when unconventional petroleum is considered.
Given that EROI is an important and objective indicator, which reflects important
additional information to shareholders and stakeholders than financial return ratios by
themselves, we argue that EROI should be disclosed, together with financial data by publicly-
listed energy companies to offer more comprehensive information to shareholders and
stakeholders. We also suggest that the EROI ratio be audited by third-party auditors, like
financial and reserves data are, in order to improve upstream petroleum companies’ innovation
performance.
In addition, the reporting of comprehensive analyses of both energy return and financial
return is needed since that the energy return ratio might show a different, sometimes even
opposite, trend and that the comprehensive analysis consisting of both ROE and EROI can offer
more information to support investment and public policy decisions about energy. We hope with
this paper to stimulate discussion of appropriate metrics for evaluating the new unconventional
petroleum companies’ performance in our current times of technological and business model
innovations and their apparent disconnect from commodity pricing and strictly financial
performance indicators largely driven by these commodity prices.
ACCEPTED MANUSCRIPT
34
Appendix A. Oil sands projects included for each sample oil sands operating company
Suncor Energy Inc. Imperial Oil Limited
Cenovus Energy Inc.
Canadian Natural Resources Limited
Mackay River Cold Lake Christina Lake Primrose, Wolf Lake, and Burnt Lakein situ projects
Firebag Foster Creek
mining project Suncor Energy OSG Imperial Oil Kearl Mine Project
CNRL Horizon Oil Sand Project
Appendix B. Direct energy input and energy output items included in this paper
Mining Oil Sands In Situ Oil Sands
Coke
Process gas - further Processing
Process gas - fuel + plant use
Natural gas consumption
Paraffinic solvent - plant use
Diluent naphtha - fuelElectricity consumption
Diluent naphtha - further Processing
SCO - fuel + plant use
Natural gas purchased
Direct Energy Input
Electricity purchased
Diesel consumption
SCO deliveredEnergy Output
Bitumen deliveredBitumen produced
ACCEPTED MANUSCRIPT
35
Intermediate hydrocarbons delivered
Paraffinic solvent delivered
Diluent naphtha delivered
Electricity exported
Electricity Exported
Appendix C. The proportions of conventional petroleum production in total production of Marathon Oil Corporation and Apache Corporation
2011 2012 2013 2014 2015 2016
Marathon Oil Corporation 71% 57% 34% 24% 19% 13%
Apache Corporation 14% 12% 10% 2% 2% 1%
Acknowledgments:
The authors of this paper would like to thank the Alberta Energy Regulator and Statistics Canada
for their support with providing part of our source data. Also, the authors would like to thank the
National Natural Science Foundation of China (Grant No. 71874202; 71874201) for its generous
support.
References:
Agostinho, F., Ortega, E., 2013. Energetic-environmental assessment of a scenario for Brazilian cellulosic ethanol. J.Clean.Prod. 47, 474-489.
Alexander, S., Anton, S., 2014. Preliminary Calculation of the EROI for the Production of Crude Oil and Light Oil Products in Russia. Sustainability. 6, 5801-5819.
ACCEPTED MANUSCRIPT
36
Aljerf, L., Choukaife, A. E., 2016. Sustainable development in Damascus University: A survey of internal stakeholder Views. Journal of Environmental Studies. 2(2), 1-12.
Anon, 2015. Privacy preserving in DM using min-max normalization and noise addition. International Journal of Advance Engineering and Research Development. 2(10).
Atlason, R. S., Unnthorsson, R., 2018. Societal and Environmental Impact of High Energy Return on Investment (EROI) Energy Access, in García Márquez, F., Karyotakis, A., Papaelias, M. (Eds.), Renewable Energies. Springer, Cham, pp. 127-148.
Aucott, M.L., Meillo, J.M., 2013. A Preliminary Energy return on investment analysis of natural gas from the Marcellus Shale. J. Ind. Ecol. 17, 668–679.
Brandt, A.R., Yeskoo, T., Vafi, K., 2015. Net energy analysis of Bakken crude oil production using a well-level engineering-based model. Energy. 93, 2191-2198.
Brundtland, G., 1987. World Commission on Environment and Development, in: Brundtland,G., Our Common Future. Oxford University Press, Oxford, pp. 27.
Calabrese, A., Costa, R., Levialdi, N., Menichini, T., 2016. A fuzzy Analytic Hierarchy Process method to support materiality assessment in sustainability reporting. J.Clean.Prod. 121, 248-264.
CAPP (Canadian Association of Petroleum Producers), 2017. Basic Statistics. http://www.capp.ca/publications-and-statistics/statistics/basic-statistics (accessed January 7, 2017).
Cavalett, O., Ortega, E., 2010. Integrated environmental assessment of biodiesel production from soybean in Brazil. J.Clean.Prod. 18(1), 55-70.
Cenovus Energy, 2016. Oil Sands. http://www.cenovus.com/operations/oilsands.html (accessed October 10, 2017).
Chen, Y., Feng, L., Wang, J., Höök, M., 2017. Emergy-based energy return on investment method for evaluating energy exploitation. Energy. 128, 540-549.
Cleveland, C. J., 2005. Net energy from the extraction of oil and gas in the United States. Energy. 30(5), 769-782.
Corley, K.G., Gioia, D.A., 2011. Building theory about theory building: what constitutes a theoretical contribution? Academy of management review. 36(1), 12-32.
Daly, H. E., 2017. Toward Some Operational Principles of Sustainable Development 1, in: Pezzey, J. C., Toman, M.A., The Economics of Sustainability. Routledge, Abingdon, pp. 97-102.
Fan, L. W., Pan, S. J., Liu, G. Q., Zhou, P., 2017. Does energy efficiency affect financial performance? Evidence from Chinese energy-intensive firms. J.Clean.Prod.151, 53-59.
ACCEPTED MANUSCRIPT
37
Freise, J., 2011. The EROI of Conventional Canadian Natural Gas Production. Sustainability. 3, 2080–2104.
Gao, C., Su, B., Sun, M., Zhang, Z., 2017. Tracking Multilayer Energy Flows Embodied in China’s Interregional Trade: An Input-Output Network Analysis. Energy Procedia. 143, 367-374.
Giere, R. N., 2004. How models are used to represent reality. Philos.Sci. 71(5), 742-752.
Giovannini, M., 2004. What gets measured gets done: Achieving results through diversity and inclusion. The journal for quality and participation. 27(4), 21.
Global Reporting Initiative, 2016. GRI 302: ENERGY 2016. https://www.globalreporting.org/standards/gri-standards-download-center/ (accessed November 11, 2018).
Grandell, L., Hall, C. A., Höök, M., 2011. Energy return on investment for Norwegian oil and gas from 1991 to 2008. Sustainability. 3(11), 2050-2070.
Guilhoto, J., 2017. Input-Output Models Applied to Environmental Analysis. Oxford Research Encyclopedia of Environmental Science, Oxford.
Gumbus, A., Lussier, R. N., 2006. Entrepreneurs use a balanced scorecard to translate strategy into performance measures. J.Small. Bus. Manage. 44(3), 407-425.
Hall ,C.A.S., 2011. Introduction to special issue on new studies in EROI (Energy Return on Investment). Sustainability. 3(10), 1773-1777.
Hall ,C.A.S., Klitgaard K.A., 2012. Energy and the wealth of nations: understanding the biophysical economy. Springer, New York.
Hall, C. A. S., Cleveland, C. J., Berger, M., 1981. Energy return on investment for United States petroleum, coal and uranium. Energy and Ecological Modeling. 715-724.
Hall, C.A.S., Lambert, J.L. Balogh, S.B., 2014. EROI of different fuels and the implications for society. Energ Policy. 64, 141-152.
Ham, Y., Golparvar-Fard, M., 2013. EPAR: Energy Performance Augmented Reality models for identification of building energy performance deviations between actual measurements and simulation results. Energy and Buildings. 63, 15-28.
Hasan, C., 2013. Central banks and financial markets: the declining power of US monetary policy. Edward Elgar Publishing, Cheltenham.
Hess Corporation, 2012. Annual Report. http://phx.corporate-ir.net/phoenix.zhtml?c=101801&p=irol-reportsAnnual(accessed January 16, 2017).
ACCEPTED MANUSCRIPT
38
Howarth, R. W., Ingraffea, A., Engelder, T., 2011. Natural gas: Should fracking stop? Nature. 477(7364), 271.
Hu, Y., Hall, C.A.S., Wang, J.L., Feng, L.Y., Poisson, A., 2013. Energy Return on Investment (EROI) of China’s conventional fossil fuels: Historical and future trends. Energy. 54, 352-364.
IEA-ETSAP, 2010. Unconventional Oil & Gas Production. https://iea-etsap.org/E-TechDS/PDF/P02-Uncon_oil&gas-GS-gct.pdf(accessed January 6, 2017).
Jain, Anil, Karthik ,N., Arun, R., 2005. Score normalization in multimodal biometric systems. Pattern. Recogn. 38(12), 2270-2285.
King, C. W., Hall, C. AS., 2011. Relating financial and energy return on investment. Sustainability. 3(10), 1810-1832.
Kong, Z., Dong, X., Jiang, Q., 2018. The net energy impact of substituting imported oil with coal-to-liquid in China. J.Clean.Prod. 198, 80-90.
Kong, Z., Dong, X., Liu, G., 2016a. Coal-based synthetic natural gas vs. imported natural gas in China: a net energy perspective. J.Clean.Prod. 131, 690-701.
Kong, Z., Dong, X., Shao, Q., Wan, X., Tang, D., Liu, G., 2016b. The potential of domestic production and imports of oil and gas in China: an energy return on investment perspective. Pet. Sci.13(4), 788-804.
Kong, Z., Dong, X., Xu, B., Li, R., Yin, Q., Song, C., 2015. EROI analysis for direct coal liquefaction without and with CCS: The case of the Shenhua DCL project in China. Energies. 8(2), 786-807.
Leontief, W., 1970. Environmental repercussions and the economic structure: An input-output approach. Rev. Econ. Stat. 52, 262–271.
Liang, H., Ren, J., Gao, Z., Gao, S., Luo, X., Dong, L., Scipioni, A., 2016. Identification of critical success factors for sustainable development of biofuel industry in China based on grey decision-making trial and evaluation laboratory (DEMATEL). J.Clean.Prod.131, 500-508.
Martinez, S., Marchamalo, M., Alvarez, S., 2018. Organization environmental footprint applying a multi-regional input-output analysis: A case study of a wood parquet company in Spain. Science of the Total Environment. 618, 7-14.
Mittal, R. K., Sinha, N., Singh, A., 2008. An analysis of linkage between economic value added and corporate social responsibility. Manage. Decis. 46(9), 1437-1443.
Mulder, K., Hagens, N. J., 2008. Energy return on investment: toward a consistent framework. AMBIO: A Journal of the Human Environment. 37(2), 74-79.
ACCEPTED MANUSCRIPT
39
Murphy, D. J., Hall, C. A., Dale, M., Cleveland, C., 2011. Order from chaos: a preliminary protocol for determining the EROI of fuels. Sustainability. 3(10), 1888-1907.
Murphy, D. J., Hall, C. A., Powers, B., 2011. New perspectives on the energy return on (energy) investment (EROI) of corn ethanol. Environ.Dev.Sustain. 13(1), 179-202.
Murphy, D. J., Hall, H.A.S., 2010. Year in review—EROI or energy return on (energy) invested. Annals of the New York Academy of Sciences. 1185(1), 102-118.
Nogovitsyn, R., Sokolov, A., 2014. Preliminary calculation of the EROI for the production of gas in Russia. Sustainability. 6(10), 6751-6765.
Parmenter, D., 2015. Key performance indicators: developing, implementing, and using winning KPIs. John Wiley & Sons, Hoboken.
Philip,V.D., 2016. These U.S. shale-oil companies are poised to profit when prices rise. http://www.marketwatch.com/story/these-us-shale-oil-companies-are-poised-to-profit-when-prices-rise-2016-03-14 (accessed January 5, 2017).
Poisson, A., Hall, C.A.S., 2013. Time Series EROI for Canadian Oil and Gas. Energies. 6(11), 5940-5959.
Raugei, M., Fullana-i-Palmer, P. ,Fthenakis, V., 2012. The energy return on energy investment (EROI) of photovoltaics: Methodology and comparisons with fossil fuel life cycles. Energ.Policy. 45, 576-582.
Rob, W., 2013.The 14 Best Stocks for Playing The US Shale Boom. http://www.businessinsider.com/the-14-best-stocks-for-playing-the-us-shale-boom-2013-9?op=1 (accessed February 13, 2017).
Rocco, M. V., Colombo, E., 2016. Internalization of human labor in embodied energy analysis: Definition and application of a novel approach based on Environmentally extended Input-Output analysis. Applied Energy. 182, 590-601.
Roman, N., Anton , S., 2014. Preliminary Calculation of the EROI for the Production of Gas in Russia. Sustainability. 6, 6751-6765.
Sardianou, E., 2008. Barriers to industrial energy efficiency investments in Greece. J.Clean.Prod.16(13), 1416-1423.
Satchwell, A.ndrew, Andrew Mills, A.M., Galen B., 2015. Quantifying the financial impacts of net-metered PV on utilities and ratepayers. Energ .Policy. 80, 133-144.
Shaffer, B. , 1995. Firm-level responses to government regulation: Theoretical and research approaches. Journal of Management. 21(3), 495-514.
ACCEPTED MANUSCRIPT
40
Shawn, M., 2013.The oil patch enters a new technological era. http://www.theglobeandmail.com/globe-investor/the-oil-patch-enters-a-new-technological-era/article7375409/(accessed March 11, 2017).
Shen, L. Y., Tam, V. W., Tam, L., Ji, Y. B., 2010. Project feasibility study: the key to successful implementation of sustainable and socially responsible construction management practice. J.Clean.Prod. 18(3), 254-259.
Soliman, M. T., 2008. The use of DuPont analysis by market participants. The Accounting ReviewAR. 83(3), 823-853.
U.S. Energy Information Administration, 2015. World Shale Resource Assessments. https://www.eia.gov/analysis/studies/worldshalegas/ (accessed January 2, 2017).
U.S. Energy Information Administration, Short-Term Energy Outlook, 2018. https://www.eia.gov/outlooks/steo/ (accessed November 20, 2018).
U.S. Environmental Protection Agency, 2016. Hydraulic Fracturing for Oil and Gas and Its Potential Impact on Drinking Water Resources. https://www.epa.gov/hfstudy (accessed November 11, 2018).
Verbruggen, Aviel, Mohamed, A.M., 2010.Views on peak oil and its relation to climate change policy. Energ. Policy. 38(10) , 5572-5581.
Von Blottnitz, H., Curran, M. A., 2007. A review of assessments conducted on bio-ethanol as a transportation fuel from a net energy, greenhouse gas, and environmental life cycle perspective. J.Clean.Prod. 15(7), 607-619.
Wang, K., Feng, L., Wang, J., Xiong, Y. ,Tverberg, G.E., 2016. An oil production forecast for China considering economic limits. Energy. 113, 586-596.
Wang , K., Vredenburg, H., Wang, J.L., Xiong ,Y., Feng, L.Y., 2017. Energy Return on Investment of Canadian Oil Sands Extraction from 2009 to 2015. Energies. 10(5),614.
Webb, T., 2008. Shell to write off half of last year's reserves. https://www.theguardian.com/business/2008/mar/16/royaldutchshell.oil (accessed January 11, 2017).
Won, Gu-. H.,wan, 2007. Electric power industry restructuring and ROE: The case of Korea Electric Power Corporation. Energy Policy. 35(10), 5080-5090.
Wu, Y., Li, L., Xu, R., Chen, K., Hu, Y., Lin, X., 2017. Risk assessment in straw-based power generation public-private partnership projects in China: A fuzzy synthetic evaluation analysis. J.Clean.Prod. 161, 977-990.
Yadullan, H., 2016. Suncor, Cenovus launch $100 million cleantech fund. http://business.financialpost.com/news/energy/embargoed-suncor-cenovus-launch-100m-cleantech-fund?__lsa=fe23-b48d (accessed February 11, 2017).
ACCEPTED MANUSCRIPT
41
York, J.G., Vedula, S., Lenox, M.J., 2018. It’s not easy building green: The impact of public policy, private actors, and regional logics on voluntary standards adoption. Academy of Management Journal. 61(4), 1492-1523.
ACCEPTED MANUSCRIPT
Highlights:
Energy return metric is affected less than financial one by price volatility
Tendencies for energy return ratio and financial return ratio diverge
Combined financial and energy ratio provides more accurate information
Formal audited report of energy and financial efficiency indicators is recommended
Energy and financial efficiency reporting improves fossil fuel company performance
ACCEPTED MANUSCRIPT