1 Financing E&P Companies and Projects on NCS The SPE Oslo Annual Seminar - hosted by PwC and Oslo Børs Upstream Project Value, Farm-in, Farm-out, Data Room Upstream IPRISK Management Methodology Olav Øvreberg, Senior Reservoir Consultant Xodus Group Arvid Elvsborg, Managing Director IPRES Norway
2 Decision Support Analysis Methodology Example: Data Room / Farm-in Value of projects with both uncertainties and probability (risk) for success or failure > Basis for the bidding strategy and financing
3 Asset value Farm-in Project Questions: > What is the value of the Asset? Downside Risk Upside Potential Total Uncertainty > Future Asset Value? Options > How much to bid? Net Present Value with uncertainty Farm-in Project (1) Producing Field (2) Prospect > Financing?
4 Asset value Farm-in Example Asset Description 1. Producing Field Future Development Options: 1. Capacity Increase 2. Infill Wells 3. Oil Prospect Asset value options a. As Is b. de-bottleneck capacity? c. Drill infill wells? d. Develop prospect? e. Timing of subprojects? 3) Infill wells (2) Prospect (1) Producing field Economic Value? How to combine the options?
5 Decision Support Analysis Methodology Upstream Projects Type of Projects > Feasibility studies Concept selection Optimize development Development modification Development wells > Exploration, Prospect > Area planning Producing fields Discoveries/Prospects > Discovery evaluation Appraisal strategy Value of new information > IOR (Improved Oil Recovery) Infill drilling EOR > Data Room Farm-in / Farm-Out Farm-in Example Covers: > Feasibility studies Concept selection Optimize development Development modification Production/Injection wells > Exploration, Prospects > Area planning Producing fields Discoveries / Prospects > Discovery evaluation Appraisal strategy Value of new information > IOR (Improved Oil Recovery) Infill drilling EOR > Data room Farm-in / Farm-Out 5
6 IPRISK - Upstream uncertainties Prospect Discovery Field Dev. plan CAPEX OPEX Economics Risks Uncertainties Scenarios Project A producing Drilling rig? Production Efficiency Seismic interpretation? Depth conversion? Deposition? Porosity? GOC? WOC? Reserves? Development CAPEX? Include Processing OPEX? capacity increase? # production wells? Communication between layers? Include Infill drilling? Production rate per well? Injection wells? Fault location? Pipeline cost? Cost per well? Oil price? Schedule Pipeline capacity? Include pospect B? Exploration Appraisalwell(s)? Cost per template? Drill exploration well? # templates?
7 Asset Valuation Methodology Define sub-surface and Surface data with Uncertainty and utilize those Uncertainties throughout the evaluation to define: 1) an Overall Development Strategy 2) the Development Concept 3) in One Economic Model Traditionally the uncertainties are lost on the road or added as sensitivity afterwards (One uncertainty at a time, which give no probability for the outcome) ü ü Recognise that The Most Likely Input Data doesn t give The Most Likely Result Need of a Methodology for combining all disciplines uncertainties and economic
8 Integrated Upstream Development Assessment Rock Volume Parameters Rock & Fluid Characteristics Oil and Gas Reserves / Resources Recovery Factor PROBABILITY RESERVES Capacity Constraints Facilities & Wells, Schedule Production Profiles CAPEX/Sched OPEX Revenue Tariff PRODUCTION Prod.start TIME Value / Cash flow Cash Flow Cut off P&A Abandonment Fiscal Regime Results Probability Plots Time Plots Decision Trees Tornado Plots Summary Tables NPV etc.
9 Asset Valuation Methodology IPRISK Input from all disciplines including Uncertainties and Risk. One Probabilistic Model for all Uncertainties and Economic.
10 Modeling Logic STOOIP Reserves Rc # of Wells Reserves per Well Drilling Start Date(s) Rig Costs Drilling Durations P&A Transp./Tariffs/Logis./Insu. Time MonteCarlo Simulation Drilling Cost Profiles CAPEX Profiles OPEX Profiles Production Profiles CAPEX (FEED +Dev. Concept) Phasing of CAPEX CAPEX per Wet well head Annual OPEX Price Assumptions Fiscal Model Internal S IMULATION Prese range outcom Abandonment 3rd. Party Economics Capacity Constraints Well Prod. Profiles Field Prod. Profiles P90 Mean P10 Key fac contrib overall NPV Tornado
11 Asset value Example Asset Description 1. Producing Field Future Options: 1. Capacity Increase 2. Infill Wells 3. Oil Prospect 3) Infill wells (2) Prospect (1) Producing field Asset value options Q L e. Timing a. As Is b. De-bottleneck capacity? c. Drill infill wells? d. Develop prospect? e. Timing subprojects? Liquid capacity a. Today b. c. d.
12 Traditional Project Valuation Data room information Sub-projects Values NPV Mil. USD NPV Mill. USD Proven Reserves Existing productio n Capacity Increase P: 80% P: 35% Infill Wells Prospect - - some upside potential BaseTraditional approach valuates project to 759 MUSD with 136 * * Asset Value Potentials Reserves Scenario Low Case Excisting Productio n Capacity increase Infill drilling Prospect Sum NPV Base Case Medium / High Case * High Case *.8 62*0.35 (Proven)
13 Asset value Decision making under Uncertainty Asset Uncertainties: Oil in Place Recovery Producing field Infill drilling Discovery Risk Discovery risk Infill drilling risk Drilling Duration & Cost CAPEX Capacity increase Prospect development OPEX Production Tariffs Timing Oil price P. 3) Infill wells Probability for Success = 80% (2) Prospect Probability for discovery = 35% (1) Producing field Uncertainties In Reserves & Cost etc.
14 Development Strategy: Farm-in Project Modification Capacity Increase Drill Prospect As Is
15 Development Strategy: Farm-in Project Modification Capacity Increase Drill Prospect As Is
16 Asset Value Development strategy NPV with full uncertainty As Is 0
17 Asset Value Probabilistic calculation of Decision Tree NPV with full uncertainty Mean P: 35% Probabilistic As Is As Is 893
18 Asset Value Options and Optimal path PROBABILITY Each Case and Decision Tree, Optimal Path NPV (10^6 USD) USD IPRISK Model results for each case and full decision tree result (Optimal path)
19 Asset Value Options and Optimal path TRUE UPSIDE (1397) PROBABILITY Expected Traditional BASE CASE (759) EXPECTED CASE OPTIMUM PATH (1046) Optimum path (stochastic): Valuates same project almost 40% higher!
20 Asset Value Comparison Traditional and Stochastic Methodology UPSIDE (862) TRUE UPSIDE (1397) PROBABILITY Traditional Expected LOW CASE (636) BASE CASE (759) EXPECTED CASE OPTIMUM PATH (1046) Optimum path (stochastic): Valuates same project almost 40% higher! 90% chance that real outcome is higher than traditional base case.
21 Traditional Asset Valuation Why different Base case estimate is Most Likely Data from each discipline Most Likely value (Mode) = equal to the Mode value in a histogram Base case is based on the Most Likely values only Traditional Most Likely 1.0 Parameter uncertainty Final Economic valuation is based base case values And some sensitivity to reflect uncertainty (Reserves, cost and oil price)
22 Stochastic summation versus deterministic summmation of Most Likely value Most Likely 1.0 Most Likely value (Mode) = 1 Deterministic: Summation of 10 Most likely values are 1*10 =10 Stochastic: Summation of 10 distribution: Most likely (Mode) = 14 Parameter uncertainty Stochastic sum Cumulative plot Stochastic Sum 10. Most Likely 14 Arithmetic sum of most likely is not equal stochastic most likely 10 Most likely * 10 has a probability of 1%
23 Stochastic versus Deterministic Stochastic: Full range of possible outcomes True expected outcome True P10 and P90 Quick update of models with new data Informed decisions Deterministic: Three discrete outcomes or N sensitivities Base Case Expected High/low cases extremely unlikely to occur Time-consuming to update sensitivities Risk-averse decisions based on low case? OTHER MODELING PRACTICES
24 Conclusion Asset value including uncertainty Methodology Advantages > Utilize all Sub-surface and Surface uncertainties throughout the evaluation > Systemize and compare all economic options > Evaluate the optimal path > Gives the total Uncertainty band for the Net Present Value (NPV) > Gives Complete Economics for DECISIONS How much to bid? Basis for Financing? That is the next question
25 Asset Value Methodology Thank you I have no theory for Bidding or Financing END
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