Pegging Input Prices to Output Prices in Long-Term Contracts:
CO2 Purchase Agreements in Enhanced Oil Recovery
Klaas van ’t Veld and Owen R. Phillips
Department of Economics & Finance
Enhanced Oil Recovery Institute
University of Wyoming
July 2009
Corresponding author: Klaas van ’t Veld, Department of Economics & Finance, University
of Wyoming, Dept 3985, 1000 E. University Ave., Laramie, Wyoming 82071-3985. E-mail:
[email protected].
Pegging Input Prices to Output Prices in Long-Term Contracts:
CO2 Purchase Agreements in Enhanced Oil Recovery
Abstract
In this paper we investigate the practice, common in CO2 supply contracts for CO2 -enhanced
oil recovery, of pegging the CO2 price to the price of oil. We show, both theoretically and
empirically, the impact of this practice on incremental oil supply from EOR projects and
derived CO2 demand. The empirical analysis uses predicted supply and demand schedules for
Wyoming’s Powder River Basin. The practice is found to reduce the sensitivity of supply and
demand to small oil-price changes by about 25%. For large oil-price changes, the practice’s
effects are much weaker when the oil price increases than when it drops.
Keywords: enhanced oil recovery, contracts, oil supply, CO2 demand
JEL Codes: Q41, L71
1. Introduction
The continued decline of U.S. oil production using conventional recovery methods has drawn
increased attention to the use of “enhanced”oil recovery (EOR) methods, and in particular
to a technique that uses injections of CO2 into depleted reservoirs (CO2 -EOR). The reason is
that conventional methods—typically a primary recovery phase using the reservoir’s natural
pressure, followed by a secondary phase in which pressure is maintained by injecting water
or sometimes natural gas—recover only a limited fraction of the oil originally present in
a reservoir. The primary phase might recover 5-20% of the oil, and the secondary phase
another 10-20%, but this still leaves typically about two thirds of the original oil “stranded.”
A recent Department of Energy study (DOE, 2008) estimates that 400 billion barrels of
established U.S. oil reserves are stranded. This compares to 175 billion barrels that have
been produced to date and just 21 billion barrels of proved reserves that can still be produced
using existing primary and secondary recovery methods. The study also estimates, however,
that CO2 -EOR is technically able to recover another 87.1 billion barrels of the stranded oil.
Since its first commercial-scale application in 1972 at the SACROC unit in the Permian
Basin in West Texas, use of the CO2 -EOR technique has rapidly grown to currently 105
projects spread throughout the country, generating 250,000 barrels per day (bo/d) or about
5% of total U.S. oil production. Of these, fully 24 were started between 2006 and 2008
(Moritis, 2008).1 The technique’s effectiveness derives from the fact that CO2 , if injected
into a reservoir at sufficiently high pressure, will mix with the reservoir oil, thereby reducing
its viscosity and causing the oil to swell. Both processes enable oil that would otherwise
1 A different EOR technique, using injections of mostly steam, is as yet slightly more prevalent in terms of production
volume, generating 293,000 bo/d from currently 45 projects. Its use is almost entirely limited to heavy-oil fields
in California, however, and has steadily declined from a peak of 469,000 bo/d in 1986 (Moritis, 2008).
2
remain trapped in the reservoir by capillary forces to flow towards production wells.2 Most
of the CO2 resurfaces mixed in with the recovered oil, and must therefore be separated.
Once separated, it is then dehydrated, recompressed, and reinjected. In every pass through
the reservoir, however, a fraction of the CO2 remains sequestered underground. In order to
maintain a given CO2 injection rate, operators of CO2 -EOR projects3 therefore need reliable
sources of CO2 over extended periods of time—it is common for an EOR project to take 20
years or longer. As a result, EOR creates a derived demand for relatively pure CO2 gas.4
If indeed EOR is to play a major role in expanding U.S. oil output, large expansions are
required of existing infrastructure supplying CO2 to EOR projects.5 An important input
into planning for these expansions are estimates of how both the supply of incremental oil
and the derived CO2 demand from EOR are likely to vary with the prices of oil and CO2 .
As we have shown in a companion paper (——, 2009), it is in principle quite straightforward
to estimate standard oil supply and CO2 demand curves for mature oil-producing regions.
A complicating factor not addressed in that paper, however, is that historically the prices of
oil and CO2 have not been treated as independent in contracts between CO2 suppliers and
EOR operators; rather, the price of CO2 has generally been pegged to the price of oil.6
2 To avoid fracturing the caprock overlying the reservoir, a small number of CO -EOR projects are operated at
2
3
4
5
6
pressures too low for the CO2 to mix with the oil. These so-called “immiscible CO2 floods” generally recover
significantly less of the stranded oil.
Because our focus in the remainder of the paper is on CO2 -EOR alone, we hereafter drop the qualifier CO2 as
understood.
EOR contracts for CO2 generally call for, and field test for, pressurized CO2 that is 95% pure. The CO2 is
generally transported and injected at pressures where it attains a “supercritical” state, in which it has properties
of both a gas and a liquid.
Current CO2 supply to all EOR projects combined is about 2.5 billion cubic feet (Bcf), of which 2.1 Bcf comes
from four very large, naturally occurring geological deposits in Colorado, New Mexico, and Mississippi. The
remainder comes from a handful of gas processing, fertilizer, and ammonia plants. The DOE study projects that
these existing sources will be able to supply only about one-fifth of CO2 demand over the next 30 years. The
remainder will have to come from new industrial sources such as coal-fired power plants, requiring large new
networks of pipelines to connect these sources to EOR sites.
Interestingly, the Oil & Gas Journal’s 2006 survey of EOR (Moritis, 2006) specifically cites this contractual
practice as one of two factors (together with the currently limited supply CO2 ) that may hamper EOR expansion
in the U.S.
3
Our focus in this paper is on this price-pegging practice and its implications. We first
show, based on a dataset covering a large number of contracts in the Permian Basin of
West Texas (the U.S. region with by far the largest number of active EOR projects) that,
except for short-term agreements, most contracts indeed have clauses that tie the price of
CO2 to the price of oil. Typically, contracts that are longer than a year have semi-annual or
quarterly adjustments to the price of CO2 , and incorporate an agreed price floor combined
with linear escalation of the CO2 price with the oil price above that floor.
We next investigate how in theory the price-pegging practice should affect the aggregate
supply of oil from all potential EOR projects in a basin combined, as well as the derived
CO2 demand. We show that the practice will tend to make both oil supply and CO2 demand
less sensitive to changes in the oil price. This feature is beneficial from the point of view of
planning for future EOR expansion and building the required infrastructure. CO2 and oil
pipeline transporters, for example, can more efficiently plan the size of their lines if sales are
relatively insensitive to price changes of the commodity. Further theoretical results, used to
inform our subsequent empirical analysis, include simple decompositions of the price-pegging
effects, relating them to (i) own- and cross-price elasticities of oil supply and CO2 demand;
(ii) the steepness of the price-pegging relationship, expressed as an elasticity; and (iii) the
share of basin-wide expenditures on CO2 in basin-wide revenues from oil production.
We empirically illustrate the effects of price pegging by applying the observed price relationship in the Permian Basin to an extensive dataset on oil fields in Wyoming’s Powder
River Basin (PRB). This basin, which covers the northeast corner of the state, is a major
oil-producing region in the US, with currently about 500 actively producing fields. To date,
1.9 billion barrels of oil have been extracted from these fields, almost all through primary
4
and secondary recovery. Enhanced oil recovery is just getting underway in the PRB. On
the western edge of the basin, in the Salt Creek Field, one operator has been applying EOR
since 2004. Several other oil-field operators have plans to begin EOR projects in the near
future.
Using the so-called “analog” method described in our companion paper, we are able to
predict which of the remaining oil fields should be able to profitably switch to EOR given any
particular combination of oil and CO2 prices. This then allows us to generate estimates of
aggregate, basin-wide incremental oil supply and CO2 demand curves for the basin, both with
and without price pegging. From these, we estimate both the partial and total elasticities
described above, and thereby the magnitude of the price-pegging effects.
We conclude with a discussion of possible rationales for price pegging, ranging from market power or collusion on the part of CO2 sellers to simple risk-sharing arrangements, or
attempts to influence the timing of EOR investment or shutdown decisions. Lastly, we offer
some speculative remarks about how, depending on the relative importance of these various possible rationales, anticipated regulations of CO2 emissions may end up affecting the
practice in future.
2. Pegging CO2 prices to oil prices
In the West Texas Permian Basin, EOR has been ongoing since 1972, when Chevron started
its CO2 flood at the SACROC unit using CO2 pumped from several gas plants. An important
boost of EOR activity in the basin came when Congress passed the Crude Oil Windfall Profit
Tax Act of 1980, which taxed incremental oil recovered through enhanced recovery methods,
5
including CO2 -EOR, at a reduced rate compared to conventionally recovered oil.7 Currently,
55 EOR projects operate in the basin, producing 67% of all CO2 -EOR output in the U.S.,
and 61% of CO2 -EOR output worldwide.8
Many CO2 sales contracts have been written between sellers and buyers in these EOR
endeavors. We have had the opportunity to review more than 300 contracts written during
a 15-year period beginning in 1983. These contracts can be characterized as either short
term or long term. Short-term contracts have no adjustment clause to the price of CO2
and typically have a duration of one year or less. Long-term contracts adjust the price of
CO2 during the year; often the adjustment is quarterly. Long-term contracts can go up to
fifteen years. Almost all contracts have a take-or-pay clause that assesses a penalty for not
accepting a minimum monthly amount.9
After the first year in a long-term contract, the price of CO2 , denoted pct , is adjusted in
most contracts by a simple formula that can be written as
pct
pc0
= o × pot .
p0
(1)
In the ratio pc0 /po0 on the right-hand side, the numerator pc0 is the original (one-year) agreed
sale price of CO2 , and the denominator po0 is the price of crude oil at the time of agreement.
This ratio is multiplied by pot , which is a posted price, or an average of a collection of posted
prices of crude, calculated at dates established in the contract.10 The expression as a whole
7 The tax on incremental tertiary oil was 30% of the difference between the market price of oil and a statutory
base price; that on conventionally recovered oil was 70% for “majors” and 50% for independent oil companies
(Lazzari, 2006).
8 Based on data in Moritis (2008).
9 Contracts also typically specify a maximum amount that the buyer can take in a given period, leaving the buyer
considerable flexibility. Moreover, a project will typically not rely on a single contract for all of its CO2 demand.
For example, a 15-year contract may be in place to meet the project’s expected minimum injection requirements
for each year over this period, but additional shorter-term contracts may be in place during the project’s early
years, to cover the higher amounts of CO2 it may then require.
6
therefore represents a linear adjustment formula that allows the price of CO2 to adjust
upward or downward with the price of oil. Generally the adjusted price pct cannot go below
pc0 , but sometimes there is an agreed price floor other than pc0 below which CO2 will not be
sold.
Figure 1 shows the monthly average CO2 price, expressed in $/Mcf,11 observed in our
dataset of contracts over the period from January 1984 through November 1993. A clear
structural break is evident in the first quarter of 1986, when the price of West Texas Sour
dropped abruptly from $27.50/barrel in January to $16.00 in March. The predicted series
shown in the figure is based on a simple OLS regression of observed CO2 prices from April
1986 onwards on same-month oil prices. No constant is included in the regression. The
estimated slope coefficient is 0.0224, with a standard error of 0.0003 and an R2 of 0.981.
When we use this estimate to predict the CO2 price out of sample, however, namely before
March 1986, we obtain a clear under-prediction of the observed price.
A regression using only data up to March 1986 yields an estimated slope coefficient of
0.0271, with a standard error of 0.0003 and an R2 of 0.997. Moreover, a Chow test using the
full sample from January 1984 through November 1993 strongly rejects the null hypothesis of
no structural break in the regression relationship between March and April 1986 (p-value "
1%). Overall, the regression analysis therefore confirms that contractual CO2 prices are set
as a constant fraction of the oil price, but also indicates that this fraction itself fell abruptly
after the first quarter of 1986, from about 2.7% to about 2.2%.
10 These contract clauses have appeared through Colorado Department of Revenue mineral audits. A sample con-
tract can be viewed at http://www.techagreements.com/agreement-preview.aspx?num=429293. Article 4.1 reads:
“Delivered Price The price to be paid by Buyer for all volumes purchased shall be calculated on a Monthly basis,
and shall be (**)% of the average of West Texas Intermediate Crude (the average of the first posting of the Month
as posted by ExxonMobil, Chevron, and Conoco Phillips) for such Month.” Note that the sample contract leaves
the percentage unspecified.
11 Mcf is the standard volumetric unit used by U.S. oil field operators for gases. It represents 1, 000 cubic feet of a
gas at standard temperature and pressure conditions.
7
Two events suggest themselves as possible explanations for this structural break around
1986. One is the completion in 1984 of three major pipelines that have since delivered the
bulk of the CO2 used in the Permian Basin from geological deposits in Colorado and New
Mexico. The resulting increase in CO2 supply to the basin may help explain why in Figure 1
CO2 prices start to decline already in 1985. The other event is the sudden collapse of oil
prices in 1986. Because this drop effectively eliminated windfall profits as defined under
the Crude Oil Windfall Profit Tax Act, it thereby also eliminated the above-mentioned tax
advantage of EOR projects relative to projects producing oil using conventional methods.
In our numerical analysis of the next two sections, we use 2.5% as an “average” fraction of
the oil price, and also add a $0.50/Mcf fixed component representing average transportation
costs. Interestingly, a 1984 assessment of the nation’s enhanced oil recovery potential by
the National Petroleum Council (NPC, 1984) used for its simulations a CO2 price of $0.50
+ 2.5% of the oil price for the West Texas, East New Mexico, and Utah region, and the
above-cited DOE (2008) study uses roughly the same escalation formula across its four price
scenarios for the U.S. as a whole.
3. Elasticity Considerations
To examine how this linkage between the prices of oil and CO2 affects oil supply and CO2
demand, we must introduce some notation. Let Qot denote, for a given year t, the aggregate
incremental amount of oil supplied by a region as a result of projects undertaking EOR, i.e.,
the amount over and above that which the region would have supplied otherwise in that
same year. Also, let Qct denote the resulting aggregate demand for CO2 .
8
Both quantities will typically be highly variable over time, even at constant oil and CO2
prices. This is because incremental oil output of any given EOR project tends to rapidly rise
to a peak within the first year or two, and to thereafter gradually decline. As noted earlier,
the project’s demand for CO2 from outside sources declines over time as well; a project can
supply a gradually increasing fraction of its needs by recycling CO2 that is produced with
the oil. For policy purposes, moreover, it is supply and demand over the course of several
decades that is of interest, rather than that in any given year. For both reasons, it will be
useful to focus on the “levelized” quantities
∞
r ! Qot
,
Q ≡
1 + r t=0 (1 + r)t
o
∞
r ! Qct
Q ≡
,
1 + r t=0 (1 + r)t
c
(2)
defined such that, at constant oil and CO2 prices, the present value of constant streams Qo
and Qc forever is equal to that of the anticipated variable streams Qot and Qct .
All else equal, increases in the oil price will increase the number of fields that can profitably
undertake EOR while increases in the CO2 price will decrease that number. We therefore
can write
∂Qo
∂Qo
>
0,
< 0.
∂po
∂pc
Qo = Qo (po , pc ),
The contracts described above fix a relationship between the prices of CO2 and oil that we
can write as pc (po ), with corresponding elasticity
d pc po
ρ = o c.
dp p
9
Let εoo and εco denote respectively the own-price and the cross-price elasticity of oil supply,
holding constant the price of CO2 , i.e., ignoring the relation pc (po ):
εoo =
∂Qo (po , pc )
po
> 0,
∂po
Qo (po , pc )
εco =
∂Qo (po , pc )
pc
< 0.
∂pc
Qo (po , pc )
Also, let ε"oo denote the total elasticity of oil supply with respect to the oil price, taking into
account the relation pc (po ):
ε"oo
#
$
∂Qo (po , pc (po ))) ∂Qo (po , pc (po )) d pc
po
≡
+
∂po
∂pc
d po Qo (po , pc (po ))
=
∂Qo po
d pc po ∂Qo pc
+
·
∂po Qo d po pc ∂pc Qo
= εoo + ρεco ! 0.
(3)
Since the second term in the final expression of (3) is negative, the total elasticity ε"oo must
clearly be less positive than the partial elasticity εoo . That is, the effect of price pegging is
to make oil supply less responsive to the price of oil. In fact, in theory it is possible for the
negative term in (3) to outweigh the positive term. That is, if the cross-price elasticity εoc of
oil supply with respect to the price of CO2 is sufficiently negative, and/or the elasticity ρ of
the CO2 price with respect to the oil price sufficiently positive, then aggregate incremental
oil supply from EOR projects may conceivably decline in the price of oil.
This perverse result is unlikely to arise in practice. To see why, consider the following
expression for the incremental net present value of an EOR project, i.e, its net present value
over and above its value had it not switched to EOR:
npv =
T
!
αpo q o − pc (po )q c − cr q cr − ci
t
t=0
t
(1 +
10
r)t
t t
t
− K.
(4)
In this expression, qto is the projected incremental amount of oil recovered by the project
in period t and sold at constant price po ; α is the share of oil revenues that accrues to the
operator after royalties, severance taxes, and property taxes; qtc is the projected quantity of
CO2 purchased at price pc (po ); qtcr is the projected quantity of CO2 recycled at unit cost crt ;
cit represents any other incremental operating costs over and above costs that would have
been incurred had the project not switched to EOR; K is the up-front investment cost of
switching; r is the internal rate of return required by the operator; and finally T is the
economic lifetime of the project. Importantly, once a project has switched to EOR, its oil
output and CO2 input paths largely fixed by the characteristics of its oil reservoir.12 As a
result, any effects of oil or CO2 price changes on aggregate, basin-wide oil supply or CO2
demand must come from induced changes in the number of positive-npv projects, rather than
from changes in individual projects’ output or input levels. In other words, for a higher oil
price and the associated higher CO2 price to have the above-mentioned perverse effect of
reducing aggregate oil supply, it must turn the npv of one or more projects negative.
Totally differentiating (4) with respect to the oil price, and letting q o and q c (without time
subscripts) denote the project’s levelized streams of oil output and CO2 purchases calculated
in the manner of equation (2), we find13
#
c$
d npv
1+r
o
c dp
=
αq − q
.
d po
r
d po
12 This very fact is central to the analog method of predicting the performance of a proposed EOR project, which
we used to generate the aggregate oil supply and CO2 demand curves for the Powder River Basin discussed in the
next section. As explained in detail in our companion paper, the analog method essentially scales the observed,
historical output and input paths of an existing EOR project (the analog) by two key reservoir characteristics of
the proposed project, namely the rate at which fluids can be injected into it, and the volume of its reservoir rock
originally occupied by oil.
13 Note that, by the envelope theorem, we can ignore the effect of the oil price on the terminal time T , since the
P
P
o
t
operator chooses that time optimally. Also, since qto = 0 after T , we have Tt=0 qto /(1 + r)t = ∞
t=0 qt /(1 + r) ,
c
and similarly for qt .
11
For this expression to be negative, we must have
d pc
αq o
.
>
d po
qc
(5)
On the right-hand side of this inequality, the magnitude of the fraction α varies by county
and state,14 but is generally on the order of 0.6–0.9. Also, rule-of-thumb values cited in the
literature for how much purchased CO2 is needed per barrel of incremental oil recovered
through EOR range anywhere from 2–8 Mcf, implying that q o /q c ranges from 0.125–0.5
bo/Mcf.15 A lower bound on the right-hand side would therefore be on the order of 0.075.
Note that this is still three times greater than the slope dpc /dpo ≈ 0.025 observed in our data
on Permian Basin contracts. This indicates that, unless the CO2 price is set at a considerably
higher fraction of the oil price, price pegging is unlikely to result in a backward-bending oil
supply curve from EOR.
Turning next to derived CO2 demand, Qc (pc , po ), we can derive elasticities εcc , εoc , and ε"oc
analogous to εoc , εoo , and ε"oo above. That is, εcc is the own-price elasticity of CO2 demand
holding constant the price of oil, i.e., ignoring the relationship pc (po ); εoc is the cross-price
elasticity of CO2 demand with respect to the oil price holding constant the price of CO2
and therefore also ignoring the price relationship; and ε"oc is the total cross-price elasticity
of CO2 demand with respect to the oil price, taking into account the price relationship.
Manipulations similar to those yielding the final expression of (3) then yield that
ε"oc = εoc + ρεcc .
(6)
14 See http://mt.gov/revenue/legislativeinformation/taxreform/oilproductiontax.xls for an overview of different
states’ severance and ad-valorem taxes, and GAO (2008) for an overview of royalty rates.
15 The estimates cited in the literature refer to cumulative rather than levelized flows of oil and CO . Since the
2
annual flows qto and qtc tend to decline in tandem, however, either way of summarizing them yields a similar ratio
between the two.
12
Since the second term on the right-hand side is negative, it follows that the total cross-price
elasticity ε"co must be less positive than the partial elasticity εco . As is true for oil supply, the
effect of price pegging is therefore to make CO2 demand less responsive to the price of oil.
%c (pc , Qo ) denote CO2 demand conditional on a given oil supply Qo and
Moreover, letting Q
defining corresponding conditional elasticities
ε%cc
%c (pc , Qo )
pc
∂Q
< 0,
=
%c (pc , Qo )
∂pc
Q
ε%Qc
%c (pc , Qo )
∂Q
Qo
> 0,
=
%c (pc , Qo )
∂Qo
Q
%c (pc , Qo (po , pc )) to derive the
we can make use of the fact that identically Qc (pc , po ) ≡ Q
following identities relating the oil supply and CO2 demand elasticities:
εoc = ε%Qc εoo ,
εcc = ε%cc + ε%Qc εco .
Substituting these back into (6) then yields
ε"co = ρ%
εcc + ε%Qc [εoo + ρεoc ] = ρ%
εcc + ε%Qc ε"oo ! 0.
(7)
Since ρ%
εcc is negative, but ε%Qc positive, it follows that even if—as we argued above is likely
to be the case—"
εoo is positive, so that incremental oil supply still increases in the oil price,
derived CO2 demand may nevertheless perversely decline in the oil price. How likely this
is in practice, and more generally how much ε"co will differ from ε"oo , depends on the degree
of substitutability between CO2 and other inputs (e.g., labor, water, electricity) in the production of oil through EOR. Trivially, in the extreme case of zero substitutability, i.e., a
13
fixed-proportions production function, ε%cc will be zero and ε%Qc unity, implying that ε"co and ε"oo
will coincide.
Further insight into what factors determine the magnitude of the price-pegging effects on
regional oil supply and CO2 demand can be gleaned from treating all potential EOR projects
in a basin as maximizing the incremental net present value of all EOR projects in the region
combined, i.e., the npv sum of all projects.16 Denoting this sum as NPV, we can write
∂NPV
= αQo ,
o
∂p
∂NPV
= −Qc .
c
∂p
and
Moreover, since by Young’s Theorem ∂ 2 NPV/∂po ∂pc = ∂ 2 NPV/∂pc ∂po , we have that
α
∂Qo
∂Qc
=
−
,
∂pc
∂po
or equivalently
αεco
∂Qo pc
pc Qc ∂Qc po
=α c o =− o o ·
= −σεoc ,
o
c
∂p Q
p Q ∂p Q
where σ ≡ (pc Qc )/(po Qo ) is the share of aggregate expenditure on CO2 in aggregate oil
revenue. Substituting the outer expression into (3) then gives
ε"oo = εoo −
ρσ c
ε .
α o
(8)
In the extreme case (which we shall see in the next section is in fact quite close to reality) of
a fixed-proportions production function, we have that εoc = εoo , implying that price-pegging
16 We thank an anonymous referee for suggesting this approach to us.
14
reduces both the own-price elasticity of oil supply and the cross-price elasticity of CO2
demand by the same factor 1 − ρσ/α. It is intuitive that this reduction should be greater,
the steeper is the price relationship, as measured by ρ, and the more “important” is the CO2
input, as measured by the share of CO2 expenditures in after-tax oil revenues, σ/α.
4. Estimating the Impact of Price Pegging
In this section, we turn to estimating empirically how large the impact of price pegging is
likely to be in practice. We also investigate the relative contribution of the various terms in
the decomposition of this impact in equation (8). To do so, we make use of the same dataset
on oil fields in Wyoming’s Powder River Basin (PRB) and the same analog approach to
predicting the EOR performance of those fields as we used in our companion paper. In that
paper, however, we estimated standard oil supply and CO2 demand curves, treating all prices
other than the own price as fixed, and we dealt with supply and demand variability over
time by reporting simple averages over an initial 4-year period. Here, our focus is on supply
and demand curves that incorporate the contractual price relationship pc (po ) estimated in
section 2. Moreover, to parallel the theoretical analysis of section 3, we report “levelized”
supply and demand curves, calculated in the manner of equation (2).
In Figure 2, the curves labeled Qo (po , pc = $1.50) and Qo (po , pc = $4.00) trace out levelized
incremental oil supply for the PRB as a function of the oil price, were the CO2 price held
fixed at respectively $1.50 and $4.00. The estimated increases in supply at higher oil prices
derive from two different sources. One is the projected increase in the economic lifetime
of inframarginal EOR projects, i.e., projects that are already profitable at the original oil
price. From equation (4), the optimal time T to terminate a project is when incremental
15
revenues αpo qTo +1 in the next period no longer cover incremental operating costs pc qTc +1 +
crT +1 qTcr+1 + ciT +1 . Clearly, any increase in the oil price will tend to delay this point to some
later time T + s, thereby increasing basin-wide output by terms qTo +1 , . . . , qTo +s . However,
because these terms tend to be small, typically coming at the end of decades of declining oil
output from the project, and because they are also discounted heavily in the calculation of
levelized output Qo (the benchmark internal rate of return used is 20% per year), their overall
contribution is negligible. The second, far more important source of estimated increases in
supply is that of new, previously extramarginal EOR projects becoming profitable.
Because the Qo (po , pc = $1.50) and Qo (po , pc = $4.00) curves in Figure 2 plot oil supply
against the oil price for given CO2 prices, the elasticity of supply along both curves is the
positive own-price elasticity εoo defined above, while the leftward displacement of the second
curve relative to the first reflects the negative cross-price elasticity εoc . Also shown is a bold
curve labeled Qo (po , $0.50 + 0.025po ). This curve traces out oil supply as a function of the
oil price when the CO2 price is pegged to that price in the manner observed in the Permian
Basin, except that we ignore the price floor and add a $0.50 fixed component representing
average transportation costs. That is, at every point along this curve, the CO2 price is equal
to $0.50 plus a fixed fraction 0.025 of the oil price.17 The elasticity of supply along the curve
is therefore the total elasticity ε"oo .
Although the bold curve is steeper than the two curves for fixed CO2 prices, it is clearly
nowhere close to being backward bending, as predicted in section 3. Figure 3 yields some
17 As noted in section 2, the relationship pc = $0.50 + 0.025po matches the formula used by NPC (1984) for the
West Texas, East New Mexico, and Utah regions, as well as the formula used by DOE (2008) for the U.S. as a
whole. Nothing in our analysis hinges on the exact values of these intercept or slope parameters, however; we
choose them purely for illustrative purposes. It is interesting to note in this respect that a 2001 report on EOR by
the Oil & Gas Journal (Moritis, 2001) cites a major CO2 supplier to the Permian Basin as saying that CO2 was
being sold at about 3-4% of the oil price. Also, the DOE’s National Strategic Unconventional Resource Model
(DOE, 2006) uses a formula pc = $0.50 + 0.013po for West Texas, New Mexico, Colorada, Mississipi, Utah, and
Wyoming, but pc = $0.625 + 0.0163po for Louisiana, and pc = $1.00 + 0.026po for all other regions.
16
additional insight into why this is the case. Each of the lighter curves in the figure represents
the locus of (po , pc ) combinations at which the npv of a particular field in our dataset is zero,
implying that EOR is profitable for that field everywhere to the bottom-right of the locus.
The bold curve in the figure traces out the contractual price relationship pc = $0.50+0.025po ,
so that moving to the right along this curve represents an increase in the oil price with a
contractually pegged corresponding increase in the CO2 price. In order for such an increase
to perversely reduce aggregate oil supply, it would have to cross some npv = 0 locus from
below, thereby taking the corresponding field into negative-npv territory. Note that this
requirement is just the graphical counterpart of of inequality (5) in section 3: the left-hand
side of this inequality, dpc /dpo , is just the slope of the price relationship, while the right-hand
side, αq o /q c , is the slope of the npv = 0 locus for a given field. Clearly, although some outlier
fields have particularly low q o /q c ratios, the price relationship is for most fields not nearly
steep enough. Moreover, the graphical analysis indicates also that the intercept of the price
relationship is of the wrong sign: for the oil supply curve to become backward bending, the
intercept would have to be strongly negative.
Returning to Figure 2, it is also evident from this figure that the effect of price pegging on
equilibrium oil supply is asymmetric with respect to the direction of discrete oil price changes:
for discrete increases in the oil price, the effect is quite small, but for equivalent decreases,
it can be quite large. Starting at the price-pegging equilibrium for an oil price of $40 and
CO2 price of $1.50, for example, an oil price increase to $140 (roughly the increase seen
from July 2004–July 2008) while keeping the CO2 price unchanged would increase levelized
supply from 4 to 9.6 million barrels per year; the same oil-price increase combined with an
upward adjustment of the CO2 price to $4, in accordance with the pegging formula, would
17
yield an only slightly smaller supply increase, to 9.3 million barrels. Conversely, however,
starting at the price-pegging equilibrium for an oil price of $140 and CO2 price of $4, an oil
price drop to $40 (roughly the drop seen from July–Dec 2008) while keeping the CO2 price
unchanged would reduce levelized supply from 9.3 to only 0.7 million barrels, whereas the
same oil-price drop combined with a downward adjustment of the CO2 price to $1.50 would
yield a far smaller supply drop, to 4 million barrels.
This asymmetry is a direct consequence of the fact that the cross-elasticity of oil supply
with respect to the CO2 price, denoted εco above, declines in absolute value (becomes less
negative) at higher oil prices. Graphically, this is reflected in the declining leftward displacement of the Qo (po , pc = $4.00) curve relative to the Qo (po , pc = $1.50) one; it is precisely
this leftward displacement that the price-pegging practice induces for oil-price increases, but
avoids for oil-price decreases. The declining cross elasticity is evident also from Figure 4,
which plots oil supply against the CO2 price, both when oil prices are held fixed at po = $40
and $140, and when the CO2 price varies with the oil price in accordance with the pricepegging relationship. Clearly, supply is far more sensitive to the CO2 price at lower oil prices:
we estimate, based on polynomial smooths of the stepped curves, that εco is about -0.54 at
po = $40 (and pc = $1.50), but only about -0.08 at po = $140 (and pc = $4.00).
Figure 5 shows the estimated effect of price pegging on the derived demand for CO2 .
The figure plots this demand against the oil price, both when CO2 prices are held fixed
at pc = $1.50 and $4.00, and when they are varied in accordance with the price-pegging
relationship. Comparing the curves in Figures 4 and 2 shows them to be remarkably similar
in shape. Underlying this is partly the fact, noted above, that increases in supply at higher
oil prices come overwhelmingly from new, previously extramarginal EOR projects becoming
18
profitable, resulting in a discrete jump of aggregate supply by that project’s levelized output.
Clearly, this will also cause aggregate CO2 demand to jump at the same price. The similarity
goes further, however, in that the magnitude of the jumps is, up to a scaling factor, very
similar as well. This follows because the ratio between aggregate CO2 demand and oil supply
turns out to be fairly constant over much of the price range shown. A plot (not shown) of
this ratio against the oil price, with the CO2 price pegged, shows that it rapidly increases
from a low of 4.3 Mcf/bo at po = $15 to a high of 7 Mcf/bo at po = $40, after which it stays
quite stable, never dropping further than 6.5 Mcf/bo.
An immediate implication is that above po = $40, the cross-price elasticity for CO2 demand, εoc , is almost identical to the own-price elasticity for oil supply, εoo . From equation
(8), this in turn implies that the ratio between the total own-price elasticity of supply, ε"oo ,
and the partial elasticity εoo is equal to 1 − ρσ/α. Note, moreover, that the product of ρ and
σ can be reduced to
d pc po pc Qc
d pc Qc
ρσ = o c · o o = o · o .
dp p p Q
dp Q
It follows that as long as EOR projects’ after-tax share α of oil revenues is independent of
the oil price, constancy of the price-pegging slope dpc /dpo and the Qc /Qo ratio will make
the ratio ε"oo /εoo = 1 − ρσ/α independent of the oil price as well. Consistent with this, we
find that although both εoo and ε"oo drop quite sharply with the oil price, from about 1.45
and 1.15 respectively at po = $40 to about 0.43 and 0.32 respectively at po = $140, the ratio
between them stays roughly constant at about 0.75.18 In other words, over much of the oil
price range shown in the figures, the price-pegging effect makes both oil supply and (given
18 Consistent with this, the price-pegging elasticity ρ increases from 0.025∗40/1.50 ≈ 0.67 to 0.025∗140/4.00 ≈ 0.88,
while the after-tax share of CO2 expenditures σ/α drops from about 0.36 to 0.25. This leaves 1 − ρσ/α roughly
constant.
19
linearity of the Qc /Qo ratio) derived CO2 demand about 25% less responsive to marginal
oil-price changes.
Figure 6, finally, shows CO2 demand as a function of its own price, both when oil prices
are held fixed at po = $40 and $140, and when the CO2 price varies with the oil price
in accordance with the price-pegging relationship. Consistent with Qc /Qo being close to
constant above po = $40, the own-price demand elasticity εcc is found to be similar to the
cross-price supply elasticity εco , and to exhibit the same sharp drop in absolute value with the
oil price. We estimate that εcc is about -0.72 at po = $40, but only about -0.12 at po = $140.
An interesting implication of this falling elasticity is that, if aggregate CO2 demand were
met by either a monopolist supplier or Cournot oligopolist suppliers, the equilibrium markup
of the CO2 price over marginal costs would increase in the oil price. With n identical
suppliers, the Lerner Index is
pc − mc
1
=
,
c
mc
n|εc | − 1
(9)
which decreases in both n and |εcc |. This is illustrated in Figure 6 by the bold dashed curves
labeled n = 1, n = 2, and n = 8. Each of these curves represents our estimate of how
the CO2 price would vary with the oil price under the monopoly or Cournot assumption,
based on the observed change in εcc with the oil price, and assuming that all firms face a
constant marginal cost equal to the $0.50 pipeline tariff. To generate these estimates, we
generated polynomial smooths of the demand curves Qc (pc , po ) at oil prices ranging from $20
to $200. Equation 9 was then applied to calculate the equilibrium monopoly or Cournot price
pcm (po ) and resulting aggregate demand Qcm (po ) at each oil price, after which an exponential
curve with vertical intercept $0.50 was fit to the resulting (Qcm , pcm ) combinations. The
implied relationships between pcm and po (not shown) turn out to be remarkably close to
20
linear, with equation pcm ≈ $0.50 + 0.06po for the case of a monopoly, n = 1, and equation
pcm ≈ $0.50 + 0.025po for the case where n = 8.
5. Possible Rationales for Price Pegging
In this section, we briefly consider a number of possible rationales for the contractual pricepegging practice. Unfortunately, given the limitations of our data, our discussion must
remain largely speculative.
Of the various possible rationales suggested by economic theory, the most straightforward
one is that price pegging is simply cost driven, i.e., a way for CO2 suppliers to pass on higher
marginal production costs induced by higher oil prices. Note that, were this to in fact explain
the practice, the Qc (pc = $0.25 + 0.025po , po ) locus in Figure 6 would simply correspond to
the aggregate CO2 supply curve, and the practice would be fully consistent with efficiency
of the CO2 market. Closer examination of the CO2 supplier’s production technology reveals,
however, that this rationale is highly implausible. Although a major variable production cost
is the fuel cost of cleaning and compressing the CO2 source stream (from either geological
deposits or gas plants), the fuel used is electricity, not oil. Given how little of U.S. electricity
production is in turn fueled by oil (about 1%), the electricity price itself would be a much
more natural basis for a cost-driven price peg.
A more plausible rationale, suggested by the findings reported at the end of the previous
section, is that the practice is driven by market power on the part of CO2 suppliers. As
indicated by the dashed curves in Figure 6, because CO2 demand becomes more inelastic at
higher oil prices, the price-pegging relationship is consistent—qualitatively, at least—with
21
predicted pricing behavior by a monopoly or Cournot industry. It is important, however, to
recognize the limitations of our both our data and our model, and thereby of these findings.
First of all, it is unclear to what extent elasticities estimated for the Powder River Basin
would carry over to the Permian Basin, which is where the price-pegging relationship was
observed. Unfortunately we have no data on fields in the Permian Basin that would allow
us to estimate similar CO2 demand curves there.
Second, also for lack of data, our demand curve estimates make no allowance for possible
substitution by oil-field operators to non-CO2 based methods of enhanced oil recovery, such
as injection of liquid chemicals and gases other than CO2 . To the extent that higher CO2
prices might drive operators to consider such alternatives, actual CO2 demand at any given
oil price will be more elastic, thereby limiting whatever market power CO2 suppliers might
have.
Third, and most importantly, our model treats as static and deterministic and environment
that in reality is very much dynamic and stochastic, with moreover significant irreversibilities
built in. It assumes, for example, counter to historical experience, that the oil price (as well
as the CO2 price, if it is not pegged) will be stable over the multi-decade operating horizon
of EOR projects. In addition, it assumes that at a given oil- and CO2 -price combination all
potentially profitable projects will commence EOR operations at the same time. In reality,
even if prices did in fact remain stable over time, the process of converting all potentially
profitable fields in a basin to EOR would likely take many years and would—given realworld constraints on the supply of CO2 and other EOR inputs (pipelines, drilling rigs, CO2
compression skids, expertise)—require projects to wait in line for such supplies to become
available. Combine this with (i) real-world instability of oil prices, (ii) significant sunk costs
22
associated with EOR conversion, and (iii) significant costs also of restarting an EOR project
once it has been shut down,19 and the price-setting problem of CO2 suppliers becomes very
much more complex than our simple model allows for.
All that said, none of these complications negate the possibility that market power might
drive the price-pegging practice.20 They do, however, point to a number of alternative and
possibly complementary rationales, which our model is unable to capture. The practice
may, for example, facilitate collusion among a number of CO2 sellers in the face of oil-price
instability, allowing the CO2 price to adjust optimally without requiring the colluding parties
to communicate. Alternatively, if EOR operators are more risk averse than CO2 sellers, the
practice may simply be a way of sharing oil-price risk. In return for the lower volatility of
EOR profits and lower risk of shutdown that CO2 -price adjustments provide, operators may
be willing to pay a premium on average.21
Another possible rationale, which may apply even if EOR operators are risk neutral, is
that price pegging may influence the timing of their investment or shutdown decisions in a
manner beneficial to CO2 sellers. As first shown by Brennan and Schwartz (1985), profit
volatility induced by output-price variability may induce a firm to delay investments that
involve significant sunk costs, out of fear that the output price might plummet. Such delay
preserves a valuable option to invest, while allowing the firm to observe how the output price
19 Doing so requires repressurizing the reservoir and possibly incurring large costs of reopening or redrilling shut-in
wells
20 Consistent with this possible explanation for the practice is also the fact that a quite small number of com-
panies have historically dominated CO2 supply to the Permian Basin. For a nice summary of this history, see the July 2006 presentation by Kinder Morgan to the Wyoming Pipeline Authority, available at
http://www.wyopipeline.com/presentations.asp.
21 It is possible that CO sellers, too, have some oil-price risk to mitigate. As noted above, the oil price has a
2
negligible direct impact on marginal CO2 production costs, which are driven largely by the price of electricity.
This is not to say, however, that there may not be an indirect, stochastic link. An active area of research in energy
markets (see, e.g., Bachmeier and Griffin (2006), Mjelde and Bessler (2009), and Mohammadi (2009) for recent
contributions) concerns the degree to which fuel markets are integrated, and shocks to the price of oil eventually
feed into coal, natural gas, uranium, and electricity prices.
23
evolves. In this context, pegging an input price to the output price can, by reducing profit
volatility, make the firm more willing to invest immediately (i.e., make it willing to do so at
a lower threshold output price), which benefits the input supplier. Similar reasoning shows
that if reactivating a project is costly, volatility of profit streams may induce a firm to delay
shutting down, out of hope that output prices will recover. In this case, input-price pegging
may, by reducing the firm’s losses in the meantime, reinforce this willingness to delay, again
benefiting the input seller.22
It is important to note that the risk-sharing and timing-adjustment rationales for price
pegging—both of which enhance the efficiency of the CO2 market—might apply independently of, but also in conjunction with, the market-power or collusion rationales—which in
themselves reduce efficiency. Unfortunately, absent detailed historical data on EOR projects
and CO2 suppliers in West Texas, including cost data that are likely to be treated as proprietary, we have no way of disentangling these possible rationales. Their relative importance
must remain an open question.
6. Concluding Discussion
In this paper, we have investigated—both theoretically and empirically—the implications of
a widespread practice in private CO2 sales contracts for EOR, namely that of pegging the
CO2 price to the price of oil.
Our theoretical analysis shows that price pegging reduces the sensitivity of both incremental oil supply from EOR projects in a region and the derived CO2 demand to changes
22 “May,” because the effect is in this case not unambiguous. If the contract raises the firm’s future input costs
when prices do recover, it will also reduce the firm’s option value of restarting. Depending on parameters, this
second effect may dominate.
24
in the oil price. In theory, both oil supply and CO2 demand could even perversely become
declining in the oil price, although we show that in practice this is unlikely to occur. We
also show that, by treating all potential EOR projects in a basin as maximizing the basinwide net present value of switching to EOR, the cross-price elasticities for oil supply and
CO2 demand can be related to each other. Using this, the magnitude of the price-pegging
effects can in turn be related to the slope of the price-pegging relationship (i.e., the rate of
CO2 -price escalation with the oil price) and the ratio of aggregate CO2 demand to aggregate
oil supply.
Our empirical analysis, using data on oilfields in Wyoming’s Powder River Basin, yields
two main findings. First, the cross-elasticity of aggregate oil supply with respect to the CO2
price is found to decline strongly (in absolute value) as the oil price increases. This implies
that for discrete oil-price changes the price pegging effect is much weaker when the oil price
increases than when it drops. Second, the ratio between aggregate CO2 demand and oil
supply becomes close to constant at oil prices above $40. This implies (in conjunction with
our theoretical results) that for marginal oil-price changes the price pegging effect becomes
roughly constant as well when expressed in percentage terms. We estimate that CO2 -price
escalation at the rate observed in West Texas would in the Powder River Basin make both
oil supply and CO2 demand about 25% less responsive to the oil price.
The two empirical findings combined have the further implication that CO2 demand becomes more own-price inelastic as the oil price increases. This is interesting in that it suggests
a possible market-power explanation for price pegging: the optimal price markup of monopolist, oligopolist, or colluding CO2 suppliers to the basin will increase in the oil price. Not too
much should be made of this particular result, however, because price pegging can benefit
25
CO2 suppliers also in different ways. By reducing the volatility of EOR projects’ profits, the
practice may also enable sellers to extract a risk premium from risk-averse EOR operators.
Moreover, the volatility reduction may increase CO2 demand, by increasing operators’ incentives to invest in EOR projects as well as possibly to keep active EOR projects operating
longer.
Which of these many possible explanations applies, or is relatively more important in
practice, remains an open question. This is unfortunate particularly because, within the
foreseeable future, the U.S. government is likely to adopt some form of regulation of CO2
emissions, whether in the form of a carbon tax or a cap-and-trade program. We leave detailed
analysis of how this might affect the EOR market for future work, but it seems clear that
the effect of such regulations on price pegging will depend very much on what currently
motivates the practice.
The reason is that, whereas current CO2 supply comes overwhelmingly from geological
sources, taxes or caps on CO2 emissions are likely to expand the supply from anthropogenic
sources such as power plants. If so, and if the main rationale for price pegging lies in current
CO2 suppliers’ market power or ability to collude, then increased entry into their market can
be expected to reduce the slope of the price-pegging relationship, possibly to zero. Clearly
this will then also reduce, and possibly eliminate, the practice’s effects on oil supply and
CO2 demand. If, however, the main rationale lies in reducing the volatility of EOR-project
profits, then—since there is no reason to suppose that CO2 regulations will make oil prices
any more stable—this rationale should continue to apply. The main effect of the regulations
may then be to lower the intercept of the price-pegging relationship, possibly making it
26
negative. Since this intercept plays essentially no role in our analysis, however, our main
results should continue to apply, at least qualitatively.
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28
0.9
Observed CO2 price
Predicted CO2 price
0.8
CO2 price ($/Mcf)
0.7
0.6
0.5
0.4
0.3
1984
1985
1986
1987
1988
1989
Year
1990
1991
1992
1993
1994
Figure 1. Observed CO2 prices in West Texas Permian Basin and predicted
CO2 prices based on linear adjustment to oil price.
29
360
340
320
Qo (po , pc = $0.50 + 0.025po )
300
280
260
240
po ($/bo)
220
200
180
160
Qo (po , pc = $1.50)
140
120
100
Qo (po , pc = $4.00)
80
60
40
20
0
0
0.7
2
4
6
8
9.3 9.610
12
Qo (MMbo/yr)
Figure 2. Incremental oil supply at fixed CO2 prices pc = $1.50 and $4.00,
and at varying CO2 prices such that pc = $0.50 + 0.025po (bold curve).
30
9
8
7
pc ($/Mcf)
6
o
5p
5
pc
=
+
.50
$0
2
0.0
4
3
2
1.5
1
0.5
0
0
50
100
150
200
250
300
350
po ($/bo)
Figure 3. Price-pegging relationship (bold curve) and npv = 0 loci for each
of the PRB fields (light curves).
31
9
8
Qo (po = $140, pc )
7
pc ($/Mcf)
6
Qo (po , pc = $0.50 + 0.025po )
5
4
Qo (po = $40, pc )
3
2
1.5
1
0
0
0.7
2
4
6
8
9.3 9.610
12
Qo (MMbo/yr)
Figure 4. Incremental oil supply as a function of the CO2 price, at fixed oil
prices po = $40 and $140, and at varying oil prices such that pc = $0.50 +
0.025po (bold curve).
32
360
340
320
300
Qc (pc = $0.50 + 0.025po , po )
280
260
240
po ($/bo)
220
200
180
160
Qc (pc = $1.50, po )
140
120
100
Qc (pc = $4.00, po )
80
60
40
20
0
3
20
28
40
61 64
80
Qc (Bcf/yr)
Figure 5. CO2 demand as a function of the oil price, at fixed CO2 prices
pc = $1.50 and $4.00, and at varying CO2 prices such that pc = $0.50+0.025po
(bold curve).
33
9
Qc (pc , po = $140)
8
7
n=1
n=2
n=8
pc ($/Mcf)
6
Qc (pc = $0.50 + 0.025po , po )
5
4
Qc (pc , po = $40)
3
2
1.5
1
0.5
0
0 3
20
28
40
61 64
80
Qc (Bcf/yr)
Figure 6. CO2 demand at fixed oil prices po = $40 and $140, and at varying
oil prices such that pc = $0.50 + 0.025po (bold curve).
34