Production rates and availability of oil and natural gas: From field to macro-level

Transcription

1 Production rates and availability of oil and natural gas: From field to macro-level Resources workshop Deutsches Institut für Wirtschaftsforschung, Berlin 22 March 2012 Kristofer Jakobsson Ph.D. in Engineering Science Dept. of Earth Sciences Uppsala University Kristofer Jakobsson 1

2 Availability a flow issue The economy needs a continuous flow of energy Availability : production rate (barrels per day) at a given price Resources in-ground are relevant insofar as they result in flows How is the amount of resources related to flows? Kristofer Jakobsson 2

3 Many analysts only focus on the amount of resources [T]he oil resource base is adequately large and growing, with little prospect that its depletion could cause a supply crisis in any foreseeable future. (Radetzki, 2010) The world s already proven reserves of oil and the process whereby they evolve thus totally eliminate any significant up-side restraint on the development of production for the first quarter of the 21st century (Odell, 2004) Is it really that simple? Kristofer Jakobsson 3

4 U.S. reserves and production 4.5 Production (Gb/ year) Proved reserves (10 s of Gb) proved reserves production Source: EIA Kristofer Jakobsson 4

5 Implications of U.S. example Relation between reserves and production does not conform to simple intuition Questions that need answers: Why are reserves not suitable as predictors? Why do regions, such as the U.S., peak and decline when a lot of oil/gas remains? Kristofer Jakobsson 5

6 What is actually meant by reserves? Definitions: Resources: total endowment of oil/gas Reserves: fraction of resources that is known and profitable to recover under present circumstances (usually low, medium and high estimates) Ultimate recoverable resource (URR): best current estimate of past production + present reserves + future additions to reserves Kristofer Jakobsson 6

7 What is actually meant by reserves? Reserve figures are not meant to enable aggregate production forecasts Purpose of reserve estimation is to: Account for a company s physical assets Guide the development of the field where the reserve is situated Indicates that a field perspective is more relevant than aggregate perspective Kristofer Jakobsson 7

8 Why do regions peak early? Norwegian North Sea gives a clue Large fields are discovered early and producing early Statfjord Discovery 1974 Production 1979 Source: NPD Kristofer Jakobsson 8

9 Why do fields plateau and decline? Maximum production rate is only a few percent of URR Decline rate is typically 10-20% Production (share of initial reserves per year) Production (share of initial reserves per year) 7% 6% 5% 4% 3% 2% 1% 0% 10% 8% 6% 4% 2% 0% Statfjord Oseberg Kristofer Jakobsson 9

10 Another question: Why produce at different costs at the same time? Statoil are producing in the North Sea and Canadian oil sands IEA, World Energy Outlook 2009 Kristofer Jakobsson 10

11 Production economics of non-renewable resources Two analytical traditions: Hotelling (1931) Intertemporal market eqilibrium Strong assumptions on producers access to information Gray (1913, 1914) Only supply side Producer uses rules of thumb, e.g. assumes constant market price Kristofer Jakobsson 11

12 Explaining plateau production: capacity investment Parameters: Resource size: 10 Unit capacity cost: $1 Discount rate: 10% Oil price: $2 12 In a nutshell: The producer must weigh a rapid realization of profits against a low investment cost Production rate NPV = $8.2 NPV = $13.3 Immediate Optimal (price = $2) Optimal (price = $1) Optimal production: MC = price (by definition) AC = 2.5/10 = $ Year AC = 1.67/10 = $0.167 Marginal cost differs from average cost Kristofer Jakobsson 12

13 Explaining plateau production: capacity investment Insights: Maximizing profit is not the same thing as maximizing the rate of production Marginal cost (= the price) is not equal to average cost Average cost varies with production rate Marginal cost cannot be directly observed (involves opportunity costs) Kristofer Jakobsson 13

14 Explaining gradual decline: declining productivity in reservoir Structure of a petroleum reservoir Kristofer Jakobsson 14

15 Oil and gas fill the pores of porous and permeable rock Source; C.Gen Kristofer Jakobsson 15

16 The flow rate The flow rate is determined by: Flow area (the number of wellbores) Pressure difference (reservoir vs. wellbore) Viscosity of fluid (i.e. its resistance to flow) Permeability of reservoir rock Source: MDM Energy Kristofer Jakobsson 16

17 Consequence: Declining reservoir productivity Pressure decline Increasing fraction of unwanted fluids Kristofer Jakobsson 17

18 Thinking of reserves with the right metaphor Bucket: When do we run out? Sponge: How hard can we squeeze? Kristofer Jakobsson 18

19 A simple production model Producer chooses the optimal platform capacity, drilling schedule and decommissioning time, subject to: Oil price Capacity cost Drilling cost Fixed operating cost Reservoir model (no spatial variation) with depletion drive Kristofer Jakobsson 19

20 Optimal production profiles: different cost scenarios Production (% of initial recoverable reserve) Parameters: Oil price = $100 Discount rate = 10% CAPEX = $100K Drilling cost = $10M Fixed OPEX = $10K Jakobsson et al. (2012) Both plateau level and decline rate are chosen to maximize NPV Base case Double drilling cost Double capacity cost Double fixed operating cost Year Kristofer Jakobsson 20

21 Optimal production rate Explaining simultaneous production at different costs Two producers with different unit costs produce at the same time, but at different rates unit CAPEX = 1 unit CAPEX = Year MC = price = $2 AC = 2.5*1/10 = $0.25 AC = 1.1*4/10 = $0.44 Same marginal cost, different average costs Kristofer Jakobsson 21

22 Explaining why large fields are discovered and produce early Few large fields, many small ones The large fields still stand for a major share of the resource Lognormal distribution Kristofer Jakobsson 22

23 Simulation of discovery process Assumed: Exploration is random Probability of discovery is proportional to field size Compare to throwing darts blindfolded at a board with areas of varying size Kristofer Jakobsson 23

24 Implication: Declining discovery size Kristofer Jakobsson 24

25 Implication: Declining productivity of exploration Kristofer Jakobsson 25

26 Exploration and discovery scenarios Exploration rate scenarios (number of exploration wells per year) Resulting discovery scenarios (barrels of new reserves per year) Kristofer Jakobsson 26

27 Aggregate production result Combine discovery scenarios with the previous field production model Availability declines when only 24-30% of total recoverable resource is produced Kristofer Jakobsson 27

28 Applications of field-by-field modeling Increasingly used for scenarios, e.g. IEA s World Energy Outlook IEA, World Energy Outlook 2011 Kristofer Jakobsson 28

29 Ambition to replicate investment decisions 0-5 years: announced projects (problems: incomplete list; delays) beyond 5 years: NPV evaluation Requires assumptions regarding: Production profiles Oil price Costs Future discoveries Kristofer Jakobsson 29

30 Many possible production profiles Implications for the timing of revenues Kristofer Jakobsson 30

31 The future oil price Possible to simply assume an exogenous price scenario IEA uses a market equilibrium model What do we know about the demand function (asymmetric responses to price changes, etc.)? What about the effects of price volatility? Kristofer Jakobsson 31

32 Costs What costs to include? Finding CAPEX Fixed and variable OPEX Fiscal (royalties, etc.) Decommissioning Cost drivers? Situation on-/offshore Size of reserves Reservoir depth Kristofer Jakobsson 32

33 Difficult to forecast cost trends Depletion causes increasing cost Technological development causes decreasing cost Cyclical fluctuations due to temporary shortages of equipment Kristofer Jakobsson 33

34 Recent cost inflation IEA, World Energy Outlook 2011 Kristofer Jakobsson 34

35 Uncertainty about future rate of discoveries CumDisc URR(1 e b CumExpl ) Kristofer Jakobsson 35

36 Example of field-by-field modeling: gas suppliers of EU-27 Bcm per year EU s increasing import dependence consumption production Imports are expected to grow by more than 50% in 20 years (IEA, 2011) Norway and Russia supply 60% of present imports Kristofer Jakobsson 36

37 Norway a mature gas producer 10 giant fields (URR > 84 bcm) contain 80% of the initial reserves No new giant discoveries in 14 years All giant fields are producing All giant fields have reached their planned plateau production Kristofer Jakobsson

38 Scenario methodology 24 fields modeled individually Contingent and undiscovered resources included (modeled as aggregates within each region) Two scenarios of total URR: Low: 5327 bcm High: 5989 bcm (NPD 2009 estimate) NPD reduced URR estimate to 5540 bcm in 2011 Kristofer Jakobsson 38

39 Norway reference scenario Söderbergh et al. (2009) Kristofer Jakobsson

40 Limited and temporary increase Söderbergh et al. (2009) Conclusions: Production will start to decline by Pipeline exports in 2030 less than or similar as present. Kristofer Jakobsson

41 Reduced official scenarios We agree that gas production will begin to decline some time after 2020, but we do not know how rapidly. - Jan Bygdevoll, Norwegian Petroleum Directorate, in Aftenposten Kristofer Jakobsson

42 Nadym Pur Taz (Western Siberia) is the energy heart of Europe NPT Region Source: Gazprom Source: Gazprom Kristofer Jakobsson

43 Remote areas are left Shtokman, arctic offshore. Yamal peninsula Eastern Siberia Source: Google Earth Sakhalin Source: Gazprom

44 Russian gas giants were discovered decades ago Western Siberia, Urengoy (1966) Yamburg (1969) Zapolyarnoye (1965) Söderbergh et al. (2010) Yamal Peninsula, Bovanenko (1971) URR Barents Sea, Shtokman (1988) Kristofer Jakobsson 44

45 Scenario methodology 83 giant fields modeled individually Planned plateau level used when available Plateau and decline rate estimated from historical data according to reserve size class Kristofer Jakobsson 45

46 Plateau levels Söderbergh et al. (2010) Kristofer Jakobsson 46

47 Decline rates Söderbergh et al. (2010) Kristofer Jakobsson 47

48 Western Siberia needs replacement Söderbergh et al. (2010) Kristofer Jakobsson

49 Yamal peninsula is critical Söderbergh et al. (2010) Kristofer Jakobsson 49

50 Scenario production and consumption Russian domestic gas demand Söderbergh et al. (2010) Kristofer Jakobsson

51 Exports to Europe and CIS Söderbergh et al. (2010) Yamal development delayed five years. Kristofer Jakobsson

52 The usefulness of field-by-field modeling Enables interpretable scenarios Inclusion of economics promotes an understanding of dynamics But does it also reduce uncertainty? A detailed model does not compensate for lack of data Kristofer Jakobsson 52

53 Final conclusions Availability is about flow rates Understanding the relation between reserves and flow rates requires a field level perspective Availability may decline early (because of gradually declining productivity in production and exploration) Should we be concerned about exhaustion? No. Should we be concerned about availability? Yes! Kristofer Jakobsson 53

54 Final conclusions Marginal cost of oil and gas production is unobservable, because of opportunity costs Cost structure (CAPEX, variable OPEX, fixed OPEX, etc.) is therefore crucial Average cost gives a picture of profitability, but does not say anything about the reasonable market price of oil and gas Kristofer Jakobsson 54

55 Thank you! Acknowledgement: The research presented here has received financial support from the Swedish Energy Agency +46(0) Kristofer Jakobsson 55

56 References Energy Information Administration. Petroleum Navigator ( International Energy Agency. World Energy Outlook (various issues). OECD, Paris. Jakobsson, K., Bentley, R., Söderbergh, B., Aleklett, K., The end of cheap oil: Bottomup economic and geologic modeling of aggregate oil production curves. Energy Policy 41, Jakobsson, K., Petroleum Production and Exploration: Approaching the End of Cheap Oil with Bottom-Up Modeling. Doctoral thesis, Uppsala University. Norwegian Petroleum Directorate. Fact Pages ( Odell, P.R., Why Carbon Fuels Will Dominate the 21st Century s Global Energy Economy. Multi-Science Publishing, Brentwood. Radetzki, M., Peak Oil and other threatening peaks - Chimeras without substance. Energy Policy 38, Söderbergh, B., Jakobsson, K., Aleklett, K., European energy security: The future of Norwegian natural gas production, Energy Policy 37, Söderbergh, B., Jakobsson, K., Aleklett, K., European energy security: An analysis of future Russian natural gas production and exports. Energy Policy 38, Kristofer Jakobsson 56