SPE 98511
`
`Accelerating Technology Acceptance: Hypotheses and Remedies for Risk-Averse
`Behavior in Technology Acceptance
`V. Rao, Halliburton Co., and R. Rodriguez, Shell Technology Ventures
`
`
`
`Copyright 2005, Society of Petroleum Engineers
`
`This paper was prepared for presentation at the 2005 SPE Annual Technical Conference and
`Exhibition held in Dallas, Texas, U.S.A., 9–12 October 2005.
`
`
`This paper was selected for presentation by an SPE Program Committee following review of
`information contained in a proposal submitted by the author(s). Contents of the paper, as
`presented, have not been reviewed by the Society of Petroleum Engineers and are subject to
`correction by the author(s). The material, as presented, does not necessarily reflect any
`position of the Society of Petroleum Engineers, its officers, or members. Papers presented at
`SPE meetings are subject to publication review by Editorial Committees of the Society of
`Petroleum Engineers. Electronic reproduction, distribution, or storage of any part of this paper
`for commercial purposes without the written consent of the Society of Petroleum Engineers is
`prohibited. Permission to reproduce in print is restricted to a proposal of not more than 300
`words;
`illustrations may not be copied. The proposal must contain conspicuous
`acknowledgment of where and by whom the paper was presented. Write Librarian, SPE, P.O.
`Box 833836, Richardson, TX 75083-3836, U.S.A., fax 01-972-952-9435.
`
`Abstract
`
`Risk aversion was concluded as being a significant
`factor in the observed slow uptake of technology in the
`Upstream Sector of
`the Oil and Gas business.
`Hypotheses centered on information asymmetry, effect
`of risk volatility on tolerance, and risk profiles of decision
`makers molded by structural or temporal considerations.
`Remedies proposed for debate and action included the
`creation of industry wide independent entities (testing
`agency or insurance company) charged with closing the
`gap created by asymmetries, as well as the creation of
`an industry award for excellence in technology uptake.
`
`
`Background
`to summarize a series of
`This paper attempts
`discussions held by a technical breakout group, as part
`of the larger SPE Applied Technology Workshop on
`Accelerating Technology Acceptance held on March 15-
`16, 2005 at the Del Lago Resort in Montgomery, Texas,
`USA. Approximately one hundred (100) attendees
`participated in the ATW, with six technical breakout
`sessions conducted during the 2-day workshop. Topics
`covered
`included Nucleating and Funding E&P
`Technology,
`Prioritization
`and
`Assessment,
`Incentives/Compensation and Culture, Blurring
`the
`Lines, and Technical Backbone.
`Some of the concepts discussed within the ATW were
`reported in an earlier article published in the May 2005
`issue of the Journal of Petroleum Technology titled
`Annual Drilling Conference Probes Technology
`Development and Lessons Learnedi, which reported on
`discussions held at the SPE/IADC Drilling Conference
`
`and Exhibition in Amsterdam earlier this year. The
`article expanded on the concept that the speed of
`technology uptake is an important problem faced by our
`industry. The SPE was subsequently encouraged by
`readership response to hold an Applied Technology
`Workshop in order to produce a platform for the
`discussion of remedies.
`
`Below we summarize some of the discussions held
`within
`the specific breakout session
`tasked with
`understanding the roles played in technology uptake
`from a risk and reward perspective. While the paper
`represents in large part the findings of the group, further
`influenced by discussion in the larger forum of the ATW
`members, the authors alone are responsible for the
`views expressed below, including the weight placed on
`the different hypotheses and remedies. We therefore
`have written this paper in the form of a normal
`publication, and acknowledge that its content is neither
`an actual accounting of discussions which took place,
`nor is it necessarily faithful to the chronology of events.
`
`Methods
`A breakout group of about
`considered the stated problem:
`
`Problem: Risk aversion is likely an important reason
`for slow technology uptake.
`
`It was generally presumed that the technologies in
`question have demonstrated application suitability with
`early adopters. Upstream technologies comprised the
`single focus of discussions. A presentation of macro
`economic trends having likely influencing behavior was
`given, followed by a moderated discussion. The general
`concepts surrounding risk-taking were also discussed
`and examples were provided. Basic ground rules were
`laid out: Hypotheses for the observed behavior would
`be put forward and discussed, and the group would rank
`the most relevant hypotheses.
`In some
`instances
`hypotheses were combined into logical groupings. The
`breakout group would then advance those specific
`remedies that addressed one or more of the chosen
`hypotheses. These in turn would be ranked for eventual
`
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`presentation and discussion with
`membership.
`
`Results
`
`Hypotheses
`Macroeconomic trends relevant to the discussion are
`presented in Figures 1 and 2. Figure 1 shows the
`progressive decline in collective oil company spending
`on upstream research and development over the last
`two decadesii. While it shows an accompanying
`increase in service company spending, this does not
`appear to significantly offset the overall decline trend.
`
`Figure 1 also shows a correlation between declines in
`R&D spending, and major oil company
`laboratory
`closings. It is surmised that oil company laboratory
`closings inevitably leads to 1) a reduced understanding
`of newer technologies, and, more importantly to this
`discussion, 2) the assessment of risk associated with the
`use of new upstream technologies.
`
`While the service providers are capable of conducting
`new technology development, there are inherent gaps in
`their ability to fully understand the most pressing needs
`of operators. These gaps stem in part from buyer/seller
`relationships and the confidential nature of oil company
`exploration and development strategies.
`
`Figure 2, derived from a commissioned study by Charles
`River Associatesiii and reproduced here by permission,
`shows patents held by the three super majors, as
`compared to patents held by the three largest service
`companies. Ignoring the drop in the year 2000 (an
`artifact of partial year data), it is obvious that patents are
`also proxies for R&D spending.
`
`
`
`The patent portfolio imbalance has contributed to greater
`scrutiny of
`intellectual property considerations
`in
`dealings between oil and service companies. The
`sharing of
`insights
`is often presaged by
`legal
`agreements outlining the rights associated with any
`findings. This inevitably creates a climate of reduced
`interaction, therefore reducing the ability of service
`companies to be responsive to needs of operators.
`
`The net result is that needed technology transfer and
`two-way collaboration between service companies and
`operators is reduced.
`
`Anecdotal information which leads to our first general
`hypothesis includes the following:
`
`1) There is significant variability in research spending
`levels between oil companies; spending may be heavy in
`select areas, and completely eliminated in other areas.
`Nonetheless, the overall spending trend for the industry
`as a whole is hard to dispute.
`
`2) It is obvious that the decline in research spending
`correlates with a related loss of experts, particularly in
`those technical fields essentially ceded to the service
`sector to develop.
`
`This leads us to the first hypothesis:
`
`Hypothesis 1: Current Practices foster Information
`Asymmetry
`
`1) Reduced expertise held by operators (and therefore a
`decreased understanding of the risk associated with new
`technology), and
`
`the
` 2) A decreased understanding of needs by
`technology developer (due
`to reduced cooperative
`interaction),
`
`combine to create Information Asymmetry. Information
`Asymmetry leads to devaluation of the technology by the
`user, and therefore slows average technology uptake.
`
`Information Asymmetry can be illustrated by the simple
`Lemon Discount Analogy posed by Nobel Laureate
`George Akerlofiv:
`
`If I were selling a car to you, and if you had little
`information about the car, you would assume it
`to be lemon, and accordingly discount the value
`to you.
`
`If, on the other hand, you were provided with
`reliable information about the car, the value of
`the car would rise from your perspective.
`
`In essence, information asymmetry causes devaluation.
`In the three decades preceding Akerlof’s awarding of the
`Nobel Prize in 2001, his theory has acquired a great deal
`of currency in economics, and in particular in the field of
`insurance. Akerlof’s paper deals with instances in which
`the existence of many goods of different qualities and
`uncertainty creates interesting problems for the market
`mechanism. In some cases, such a situation which is
`characterized by asymmetric information causes the
`market to break down completely so that there is no
`exchange of goods at all.
`
`
`Hypothesis 2: Risk Profile of the Decision-Maker
`
`The second hypothesis centers around three somewhat
`related issues:
`
`1) During collaborative decision-making, variances
`in
`individual
`risk profiles of decision-makers
`generally result
`in
`lower overall tolerance for
`potential
`failure as
`it pertains
`to using new
`technology on a well. Differences in risk profiles may
`be driven in part by reward systems adopted by different
`departments within a company. It is not uncommon, for
`example, for the drilling department of a company to
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`Scenario 1: A new product failure rate is 1 out of 5 during the testing stage. Scenario 1: A new product failure rate is 1 out of 5 during the testing stage. Scenario 1: A new product failure rate is 1 out of 5 during the testing stage.
`
`
`Installation costs are $600K Cost of Capital is 10%.Installation costs are $600K Cost of Capital is 10%.Installation costs are $600K Cost of Capital is 10%.
`
`
`
`•If successful, it creates $1,000K of value. •If successful, it creates $1,000K of value. •If successful, it creates $1,000K of value.
`
`
`•If it fails, it destroys $250K of value.•If it fails, it destroys $250K of value.•If it fails, it destroys $250K of value.
`
`
`
`r = 10%r = 10%r = 10%r = 10%
`
`
`
`
`
`
`
`
`
`
`
`($ 600K)($ 600K)($ 600K)($ 600K)
`
`
`
`
`
`
`
`4/54/54/54/5
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`
`
`
`
`
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`1/51/51/51/5
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`
`
`$ 1,000K$ 1,000K$ 1,000K$ 1,000K
`
`
`
`
`
`
`
`
`
`
`
`($ 250K)($ 250K)($ 250K)($ 250K)
`
`
`
`Should the operator test the product in Should the operator test the product in Should the operator test the product in
`
`
`his well? his well? his well?
`
`
`Does the operator capture additional Does the operator capture additional Does the operator capture additional
`
`
`benefits?benefits?benefits?
`
`
`
`
`NPV10 = - 600 + (4/5)*1,000/1.1 – (1/5)*250/1.1NPV10 = - 600 + (4/5)*1,000/1.1 – (1/5)*250/1.1NPV10 = - 600 + (4/5)*1,000/1.1 – (1/5)*250/1.1NPV10 = - 600 + (4/5)*1,000/1.1 – (1/5)*250/1.1
`
`
`
`NPV10 = +82KNPV10 = +82KNPV10 = +82KNPV10 = +82K
`
`
`
`
`Scenario 2: Should the operator test the new product if Scenario 2: Should the operator test the new product if
`
`instead:instead:
`
`
`
`•it creates $2,000K in value if successful or •it creates $2,000K in value if successful or
`
`
`
`•destroys $4,250K in value if it fails?•destroys $4,250K in value if it fails?
`
`
`
`
`
`r = 10%r = 10%r = 10%
`
`
`
`
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`($ 600K)($ 600K)($ 600K)
`
`
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`
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`4/54/54/5
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`
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`1/51/51/5
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`
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`$ 2,000K$ 2,000K$ 2,000K
`
`
`
`
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`($ 4,250K)($ 4,250K)($ 4,250K)
`
`
`
`
`
`NPV10 = - 600 + (4/5)*2,000/1.1 – (1/5)*4,250/1.1NPV10 = - 600 + (4/5)*2,000/1.1 – (1/5)*4,250/1.1NPV10 = - 600 + (4/5)*2,000/1.1 – (1/5)*4,250/1.1
`
`
`
`
`
`NPV10 = +82KNPV10 = +82KNPV10 = +82K
`
`
`Note that both of the investment scenarios showed an
`identical, positive NPV of +$82K. From a classically
`trained economist’s perspective, this positive NPV would
`imply the risk therefore is warranted in order to obtain
`the possible outcome.
`
`Following the presentation of scenarios, the presenter
`then asked each audience to “vote”, through a show of
`hands,
`if
`they would personally assume
`the risk
`presented in each of the two scenarios.
`
`When queried on the first scenario, (which showed
`modest value
`if successful, and modest
`loss
`if
`unsuccessful), most audience members indicated they
`would assume the risk. Interestingly, when queried on
`the second scenario, (which showed higher value if
`successful, and correspondingly greater
`loss
`if
`unsuccessful), almost no respondents indicated they
`would assume the risk.
`
`Even though the audience was presented with similar
`curves having the same positive NPV, they reacted less
`willingly to the scenario having greater reward and risk
`(also termed “volatility”).
`
`This informal poll may indicate that when it comes to
`new technology, there is an imbedded negative incentive
`to take on high reward / high risk decisions.
`
`This tendency was also acknowledged by a risk expert
`who presented at a 2005 OTC session on gas
`transportationvi, who reiterated, for the audience’s sake,
`that “novel technology is not inherently riskier”.
`
`
`
`
`than
`
`the production
`
`have a different risk culture
`department.
`
`2) A technology that requires expense outlay in the
`present, for potential gratification in the future, may
`present a dilemma for a decision-maker.
` For
`example, smart wells require initial capital expense
`outlays in order to reap future benefits from optimal fluid
`production and reduced long-term intervention costs.
`This particular example also highlights another inequity:
`
`3) A technology that requires initial CAPEX outlays,
`in order to reap current or future OPEX benefits, may
`present a dilemma for a decision-maker.
`
`
`
`
`Hypothesis 3: Asymmetries in budgets, risks and
`rewards.
`
`The third hypothesis combines yet another set of issues.
`On occasion, limitations of current fiscal year budgets
`can prevent new
`technology
`trials.
` Budgetary
`constraints may be further exacerbated when potential
`value created may have benefit to altogether different
`company functions or regions. It is not atypical for logic
`to dictate that one company department bears the
`expense and risk, while an entirely different department
`recoups the greater value derived from assuming that
`risk. For example, it might make sense to pilot test a
`new subsea technology in shallow waters in the U.S.
`Gulf of Mexico with close proximity to infrastructure,
`although the ultimate “customers” for the new technology
`may be deepwater international operating groups.
`
`Hypothesis 4: Risk Tolerance is reduced when Risk
`Volatility is increased
`
`From the perspective of classic economic assessment of
`risk, reward and probability of outcomes, E&P managers
`are essentially paid to move forward on decisions having
`positive NPV outcomes.
`
`Yet, when making decisions for scenarios which
`have high reward and high risk, even when the
`calculated outcome is a positive NPV, Oil and Gas
`Operators will rationalize a lower tolerance for risk-
`taking when it comes to new technology.
`
`This behavioral tendency was demonstrated during a
`recent series of industry presentationsv. A contributor to
`this paper presented hypothetical investment scenarios
`in several public sessions, one having roughly 50
`Offshore Technology Conference attendees and the
`other comprised of approximately 25 SPE members.
`Each audience was primarily composed of oil and gas
`engineering staff.
`
`The presentation of scenarios was as follows:
`
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`Remedies
`
`Industry Organization for Validating Utility
`
`This concept describes the formation of an independent
`business entity which is charged with assessing key
`technologies and
`the value created by
`those
`technologies,
`and
`testing
`and
`validating
`the
`technologies. The entity would be sponsored, and
`likely owned, by user companies (oil and gas companies
`and service companies). The entity would have the
`appropriate expertise, equipment and facilities to run
`appropriate tests and analysis, and may have access to
`one or more field locations suitable for field testing of
`downhole equipment.
`
`The testing facility would also be charged with assessing
`the
`risk associated with new
`technologies, and
`publishing
`assessments
`of
`technology
`value
`propositions. Comprehensive, independent assessment
`coupled with open communication and full disclosure
`addresses the information asymmetry issue directly.
`One member of the working group quipped that this
`organization would be akin to the “Ministry of Truth”
`(1984 by George Orwell). A more mundane analogy
`would be the United Independent Laboratories (UIL)
`seal, although the entity’s responsibilities would likely be
`broader. Many details would need to be fleshed out,
`including business models, criteria for project selection,
`mechanisms for field testing, etc.
`
`The underlying concepts behind this proposed approach
`have been put into practice by one of the Working
`Group’s members, Bob Hinkle, Chief Executive Officer of
`Enventure Global Technology. Enventure is in the
`business of providing solid expandable tubulars, used in
`well construction to reduce risk associated with a variety
`of adverse drilling situations. Enventure was able to
`bear out the applicability of its solutions through its work
`with Shell’s laboratories in the Netherlands, coupled with
`a variety of tests performed on wells made available in
`South Texas.
`
`Industry Insurance Company
`
`insurance company would be
`The concept of an
`complimentary to the independent test facility described
`above. The insurance company (or variation thereof)
`would possess the expertise to properly evaluate tests
`results presented by the test facility, similar to the role of
`a Lloyd’s of London, for example. It would be judicious
`in determining which offerings were evaluated and
`backed. Based on its assessment of upside and
`associated risk,
`it would
`then selectively offer
`to
`underwrite the costs of failure for the use of certain
`technologies, thus traversing the risk aversion due to
`information asymmetry.
`
`If the insurance company does its job well, the premiums
`paid by users would result in a net profit for the entity.
`
`Various business models could be considered to make
`such an offering attractive to industry participants.
`Assuming the company was owned by its user base,
`profitability could be distributed in the form of equity
`participation to its shareholders. Alternately, premiums
`could be rebated to its users.
`
`in enabling
`lies
`the real value
`In either model,
`participants to put high value technology to work while
`mitigating their risk, even if the user company does not
`have
`the expertise
`to properly evaluate
`risk.
`Interestingly, the concept largely rests on the ability of
`the insurance entity to properly select and evaluate
`technologies such that the actual risk is significantly less
`than the perceived risk.
`
`Industry Award for Technology Uptake
`
`The concept of an Industry Award for Technology
`Uptake addresses some of
`the
`issues raised
`in
`Hypotheses 2 and 3, which relate
`to challenges
`stemming from current practices in corporate policies,
`incentive plans and decision making structures. Well-
`publicized industry recognition for the company having
`the best record for technology uptake in a given year
`might provide an impetus for fostering the desired
`behaviors for technology uptake and risk management.
`Such an award might be presented to the CEO, or the
`executive management team as a whole. Reference
`The Malcolm Baldrige National Quality Award vii, which
`proved to be very effective for a number of years as a
`significant behavior driver.
`
`The strengths and shortcomings of the Baldrige program
`would be studied and used as a guide in the design of
`the Technology Uptake award. The metrics most
`depictive of fast uptake would have to be identified. For
`example, one method might be
`to compare new
`technology based spending to total spending for the
`year. New technology would have to be defined in
`consistent, replicable manner, such as commercial use
`within five years of the vendor’s first revenue.
`
`
`This particular remedy was in fact developed by one of
`the other breakout sessions.
` Participants
`in our
`breakout group also regarded this concept as particularly
`compelling, and one
`that uniquely addressed our
`hypotheses when revealed in the combined session at
`the end of the ATW. It struck a strong chord with the
`entire working group.
`
`
`Conclusions
`
`Risk aversion is concluded as being a significant factor
`in the observed slowness of technology uptake in the
`upstream sector of
`the Oil and Gas business.
`Hypotheses for this behavior include:
`• The existence and continued exacerbation of
`Information Asymmetry, leading to devaluation
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`Figure 1: R&D Investments – Upstream SectorFigure 1: R&D Investments – Upstream Sector
`
`
`
`
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`1,4001,4001,4001,4001,400
`
`
`
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`1,2001,2001,2001,2001,200
`
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`1,0001,0001,0001,0001,000
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`
`
`800800800800800
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`
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`600600600600600
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`400400400400400
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`
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`
`
`
`200200200200200
`
`
`
`
`
`E&P Firms*E&P Firms*E&P Firms*E&P Firms*E&P Firms*
`
`
`
`
`Oilfield Service Firms**Oilfield Service Firms**Oilfield Service Firms**Oilfield Service Firms**Oilfield Service Firms**
`
`
`
`
`Seismic Service Firms***Seismic Service Firms***Seismic Service Firms***Seismic Service Firms***Seismic Service Firms***
`
`
`
`
`Research Center ClosingResearch Center ClosingResearch Center ClosingResearch Center ClosingResearch Center Closing
`
`
`
`20022002200220022002
`
`R&D Investment
`R&D Investment
`R&D Investment
`
`($, millions)
`($, millions)
`($, millions)
`
`of a technology by the user, thus slowing
`uptake;
`• The individual risk profile of the decision maker,
`conditioned by issues such as lack of direct
`realization of rewards (benefit accrues to a
`different group within
`the company) and
`temporal disconnects (spending risk accrued
`today for gratification in later years); and
`• Level of risk volatility (for a typical decision
`maker,
`risk
`tolerance
`is
`reduced when
`(perceived or real) risk volatility is increased.
`
`Proposed remedies suggested
`further action include:
`
`for debate and
`
` •
`
` Formation of an Independent Validation Entity
`(likely owned by a group of operators) charged
`with assessing and validating
`technologies,
`including risk assessment and value creation;
`• Formation of an Industry Insurance Company for
`assessing and underwriting the costs of failure
`associated with selected technologies (where
`the actual risk is significantly less than the
`perceived risk,
`the disparity occasioned by
`information asymmetry); and
`• An Industry Award for Technology Uptake, with
`public recognition for the leadership of the
`company with the swiftest uptake in a given
`year, as defined by set metrics.
`
`
`
`
`i Donnelly, J. (May 2005), “Annual Drilling Conference
`Probes Technology Development and Lessons Learned”,
`Journal of Petroleum Technology.
`ii Cambridge Energy Research Associates (Cambridge,
`Massachusetts USA)
`iii CRA International, Inc. (formerly Charles River Associates
`Incorporated), (Boston, Massachusetts USA)
`iv Ackerlof, G. (1970) “The Market for ‘Lemons’: Quality
`Uncertainty and the Market Mechanism.” The Quarterly
`Journal of Economics, 84 (1970), pp. 488-500.
`v Rodriguez, R. (2005) “Accelerating Technology Acceptance
`(Risk and Return”), 2005 Offshore Technology Conference
`(Houston, Texas USA)
`vi Casada, M & Serratella, C (2005) “Risk-Based Novel
`Concepts Reviews for Offshore Gas Handling and
`Transportation”, 2005 Offshore Technology Conference,
`Deepwater Oil and Associated Gas Technical Session
`(Houston, Texas USA)
`vii Malcolm Baldrige National Quality Award, National
`Institute of Standards and Technology,
`http://www.quality.nist.gov
`
`
`
`
`
`
`
`
`
`
`00000
`19971997199719971997
`19921992199219921992
`19871987198719871987
`19821982198219821982
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
`
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`19771977197719771977
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`*US E&P firms and the US R&D investments of international E&P firms; Department of Energy, EIA, CERA analysis*US E&P firms and the US R&D investments of international E&P firms; Department of Energy, EIA, CERA analysis
`
`**Traditional Oil Field Service companies (Baker Hughes, Halliburton, Schlumberger, Smith, Weatherford) annual Reports, CERA Analysis**Traditional Oil Field Service companies (Baker Hughes, Halliburton, Schlumberger, Smith, Weatherford) annual Reports, CERA Analysis
`
`***Seismic Service companies (CGG, Input/Output, OYO Geospace, PGS, Veritas) annual reports, CERA analysis. Source: Cambridge Energy ***Seismic Service companies (CGG, Input/Output, OYO Geospace, PGS, Veritas) annual reports, CERA analysis. Source: Cambridge Energy
`
`Research Associates.Research Associates.
`
`
`
`
`
`
`
`
`
`
`
`
`
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`Figure 2: Top 3 Super Majors vs. Service Companies Figure 2: Top 3 Super Majors vs. Service Companies
`
`Upstream Patent Awards 1991-2002Upstream Patent Awards 1991-2002
`
`
`500500
`
`450450
`
`400400
`
`450450
`
`300300
`
`250250
`
`200200
`
`150150
`
`100100
`
`5050
`
`00
`
`
`Major Service Major Service
`
`CompaniesCompanies
`
`
`SelectedSelected
`
`Super MajorsSuper Majors
`
`
`
`91 92 93 94 95 96 97 98 99 00 01 02*91 92 93 94 95 96 97 98 99 00 01 02*
`
`
`*Year to date 2002; Source: Derwent WPI, Global patent search on Upstream code*Year to date 2002; Source: Derwent WPI, Global patent search on Upstream code
`
`H01) published patents (1991-2002) ; Source: Charles River AssociatesH01) published patents (1991-2002) ; Source: Charles River Associates
`
`
`
`Higher Volatility DistributionHigher Volatility Distribution
`
`
`
`Area 1’Area 1’
`
`
`
`Area 1Area 1
`
`
`
`Area 1- Area 1’ = Area 2 – Area 2’Area 1- Area 1’ = Area 2 – Area 2’
`
`
`
`Area 2’Area 2’
`
`
`
`Area 2Area 2
`
`
`
`Risk NPVRisk NPV
`
`
`
`00
`
`
`
`Reward NPVReward NPV
`
`
`
`
`
`Value
`Value
`
`5 of 5
`
`Ex. 2093
`IPR2016-01517
`
`