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IADCHernandez2001

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IADCHernandez2001

  1. 1. Production Geology Approach as a tool to accelerate the implementation of advanced drilling technologies: Intelligent Well Evaluation Methodology Ana Maria Hernandez IADC World Drilling conference, Madrid, June, 2002
  2. 2. Production Geology Approach Knowledge Gaps: Time & Money Knowledge Management Geology Production Advanced Drilling & Completion Technologies
  3. 3. Intelligent Well Evaluation Methodology  Technological Background  Initial screening criteria: production geology scenarios  Intelligent Well Systems: Geological Constraints  Down hole Sensors  Isolated Control flow Zones  Surface Systems  Intelligent well technologies and new trends in Economics  Production Geology Approach: Case Study Multilateral technology
  4. 4. Why Intelligent Wells? Measurement - Control - Monitoring Applications:  To monitor gas water coning problems in oil rims  To measure, control and monitor injection & production fluids in complex reservoirs  Reservoir drainage improvement  Remote control and monitoring in hostile environments  To avoid well interventions >>>>> Isolate Control Zones Down hole Sensors Surface Systems Telemetry Well
  5. 5. Where to apply Intelligent well technology? Initial screening criteria: reservoir candidates Oil rims in heterogeneous reservoirs IOR projects in complex reservoirs Improvement of drainage strategies in reservoirs with technology maturity Offshore projects with economic potential Areas under environmental regulations
  6. 6. Intelligent Well technology vs. Reservoir types Critical zones: partially connected sands in the middle part of the reservoir ME-J1U/L ME-S2,3 ME-M2 ME-T4,5< ME-L ME-M1 ME-S1 ME-JIU ME-C ME-J1U ME-C ME-S1 Type 1:Structural/faulted reservoirs with high lateral & vertical heterogeneity Type 2: Heterogeneous reservoir associated with salt domes Type 3: Stratigraphic traps with internal compartmentalization Type 4: Bypassed oil zones in stratigraphic reservoirs
  7. 7. Reservoir scale Oil rims and complex IOR in mature heterogeneous reservoirs GOC WOC Irregular GOC & WOC Water coning Water / Gas Coning Gas Coning Bypassed Oil Lower reservoir Change in petrophysical properties Change in reservoir architecture Upper reservoir Critical Zone: partially connected sands in the middle part of the reservoir More control and monitoring is needed to avoid production problems Critical zone Km m
  8. 8. Borehole seismic::  Range ~ 2-100 m  High resolution  Geometry limitation 4C/4D seismic: •3D geometry •Reservoir coverage •Limited resolution Resistivity sensors: •Range 0-10 m •Permanent monitoring Data Gap vs. Technology
  9. 9. Source: The leading edge (april, may 1999) Borehole seismic systems More borehole seismic configurations are needed to improve well to well visualization
  10. 10. Km-m +/- 2-200 m 0-10 m The dimensional Problem Illustration by BP
  11. 11. Project Economics Flow Cash, NPV Valves Chokes Control Zones Sensors Identification of variables that produce economical impact Variable 1 Variable 2 Variable n Search of the probability distribution to model each variable Determination of variables with high impact Sensitivity analysis of each variable Run the Simulation Analysis of results How to determine the impact of geological variables at inter-well scale Decision support tool for technology assessment NPV 1141.17 45 5.6 11.57 100.00 40.5 11.23 6.16 1895.83 16 14.0 8.52 150.00 43.5 9.55 13.84 -200.00 0.00 200.00 400.00 600.00 STOIIP Wells to drill Plateau rate Discount factor Facility size Recovery Well cost Well rate
  12. 12. Geological variables at inter- well scale Target Forecast: Reservoir variability Reservoir continuity (km-m) .44 Vertical connectivity (m) .50 Kv/kh ratio .49 Flow units (m) .75 -1 -0.5 0 0.5 1 Measured by Rank Correlation Sensitivity Chart Flow unit is the geological variable with more impact related with Intelligent well technology Reservoir architecture vs. well architecture
  13. 13. +200 150 100 50 25 15 5 mReservoir Candidates North Sea Gulf of Mexico Indonesia West Africa Venezuela Reservoir flow units dimensions The design of isolated control zones should take into account the dimensions of the reservoir flow units to optimize production and avoid production problems
  14. 14. Sand production proneScale prone Optimal Completion window 200-20 m Production flow units: Rock types + rock wetability + rock strength Drainage points Horizontal well Isolated control zones at perforation scale Bigger completion windows: high lateral and vertical heterogeneity but more homogeneous rock types (quartz arenites)
  15. 15. Isolated control zones 200-20 m Isolated control zones +/- 200 m A.- Horizontal well B.- Multi branch well Isolated control zones: best geological options in reservoirs with bigger completion windows
  16. 16. PRODUCTION BEHAVIOR HIGH ANGLE vs. CONVENTIONAL WELLS 0 500 1000 1500 2000 2500 3000 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000 OIL RATE (BOPD) WELLHEADPRESSURE(PSI) FUL-63 FUL-68 FUL-70 FUL-75 FUL-56 FUL-59 FUL-61 FUL-651/2" 1" 3/4" 1 1/2" 1 1/4" C.- High angle wells perforated following the completion windows Example El Furrial Field - VenezuelaEl Furrial Field - Venezuela High Angle Wells production Typical wells SPE 56430 Proposed Isolated control zones
  17. 17. Isolated control zones: North Sea Case Sensitive Scale intervals Sensitive Sand Production intervals Scale prone Completion window Sand production prone 20-5 m Horizontal well • Red intervals will produce sand/scale since the beginning if they are perforated • If yellow intervals are perforated any change in the flow regime will activate the production problems Reservoirs with high lateral & vertical heterogeneity and high internal heterogeneity (rock type: litarenites)
  18. 18. A.- Low/high angle wells Isolated control zones + 200 m Proposed Isolated control zones: North Sea Case B.- Optimal completion windows in small-channel zones: perforation optimization Horizontal well Completion window
  19. 19. ow to determine the impact of geological variables at perforation scal Producer Surprise handling Injector Water Breakout Decision variables Assumptions Variability Uncertainty Forecast Injector Injection points Valves/chokes Zonal flow sensors Producer Drainage point Valves/chokes producer Permanent resistivity sensors Interwell data Distance between wells Completed interval Perforation rock types rock wettability rock strenght pore pressure barriers layers Surprise handling Water Breakout Monte Carlo Simulation Target Forecast: Surprise handling rock strength .54 rock types .52 rock wet ability .49 layers .05 internal barriers .01 -1 -0.5 0 0.5 1 Measured by Rank Correlation Sensitivity Chart Drainage points Injection points
  20. 20. Proposed Rock type Analysis Reservoir Pressure Bottom Hole Pressure Rock type window ? Oriented rock type perforation Rock Type Rock Strength Rock type vs. Rock Strength Rock type window
  21. 21. IW project Brainstorming Identify Technical Issues related with IW Identify Economical Issues related with IW Identify IW Potential Scenarios Initial Options Screening IW production Optimization Solutions Prospective IW economic scenarios Identify Critical Decision Issues New trends in petroleum economics Discounted Cash Flow Analysis IW Case history selection IW Reservoir Modeling Intelligent well projects: screening criteria
  22. 22. - 6 - 4 - 2 0 2 4 6 1 2 3 4 5 6 TIME [MONTHS]CASHFLOW[MM$] Production Initial Investment Workover Costs NPV | BASE CASE CONVENTIONAL WELL MULTILATERAL WELL NPV |MLT< Cash flow analysis Life cycle cost analysis(2) Intelligent wells goal is to capture everyday events in the reservoir. Can we analyze them using conventional petroleum economics? Forecasting & risk analysis (1) Economic threshold: Decision Tree (3) (1) SPE 37932,63528; (2)SPE 35315;(3)63201
  23. 23. Advanced decision- making technical/economical tools to justify new technology Technology A Technology B Technology C High Risk 0 5 10 15 2 0 2 5 3 0 3 5 4 0 scena. 1 scena. 2 scena. 3 v a r . 1 v a r . 2 v a r . 3 Technical / Economical ranking matrix Reservoir Scenario 3 Scenario 2 Scenario 1 Variables that impact economically the reservoir Multi-objective Decision Analysis (3) Dynamic Complexity Dynamic Complexity (1) Multi-prospects Evaluation (2) (1) SPE 52954;(2) SPE 69614; (3)SPE 68579
  24. 24. Activity Level Mutual Help Coalescence Individual Effort Potential • Multidisciplinary Team • Compilation of Information Information Analysis • Business Plan • Reservoir Review • Technology Maturity • Opportunity identification Unification of Efforts Maturity 3 Technical Forum • Drilling/completion • Geomechanics • Case Studies • Potential proposals Results Actions Dispersion Year 2000 Domestic development • Technical Proposals • Operational know-how Technology Knowledge How to accelerate the implementation of advance drilling technologies? Knowledge management. Example MTL Technology; PDVSA, Venezuela
  25. 25. Production Geology Approach Production Geology “ THE FRAME” Combination of: • Structural Styles • Reservoir Types • Rock types • Flow Units •.... a techno-economic challenge Technology- a solution The key: Right Technology in the right frame using the optimal oil recovery process  Acceleration of technology implementation  Reduction of cost/ increase of value  Multidisciplinary approach: identification of best practices  Uncertainties reduction, production optimisation MTL Failure MTL success MTLFailure MTL success Multi laterals 1995-1998 Multi laterals 2000 + 1998 MTL technology Abandoned 1999 MTL Corporative Effort Evolution of the Multilateral Technology in Venezuela; PDVSA, Venezuela 5 Wells 20 Wells

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