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Marginal Field Development

Marginal Field Development. Advances in 3D Geological Modeling: How it can help?. Economic Drivers. How much oil or gas is there? How much is recoverable? How fast it can be recovered? How much capital expenditure required? What will be return on investment?

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Marginal Field Development

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  1. Marginal Field Development Advances in 3D Geological Modeling: How it can help?

  2. Economic Drivers How much oil or gas is there? How much is recoverable? How fast it can be recovered? How much capital expenditure required? What will be return on investment? Economics is constrained & guided by technical complexities & challenges…..how well we understand the field

  3. Thrust Areas: New Technology Data Acquisition & Processing Seismic Interpretation Formation Evaluation, Well Stimulation & Well Control Reservoir Modeling & Simulation Drilling & Related Services Facilities & logistics Information Technology Marginal fields have constraints on heavy data acquisition program - Field understanding is based on limited data - Dealing with Risk when limited data pose high uncertainty The real challenge with marginal field is probably not in selecting the best technology but in the way these technologies will be managed.

  4. Technological Drivers New algorithms New Workflows Powerful computing capabilities Improved integration of various type of data Improvement in existing algorithms Improved workflows Efforts are directed towards development of technologies that are faster, automated, scalable, reproducible and provide realistic representations

  5. Technological Innovations 3D Geological Modeling Seismic Technology Formation Evaluation Strategy Drilling Technology Extended Well Tests (EWT) Early Production Systems (EPS) Intelligent Completions Aim of technological innovation is to reduce economic & project risk

  6. 3D Geological Modeling Challenges Reservoir pose challenge –structure & stratigraphy Challenge is to realistically represent reservoirs Data explosion Reservoir quality & Volumetric Challenges are related to- scale, technology, & skill Understanding the reservoir and the associated uncertainty/ risk is key….even in marginal fields

  7. Make Horizons Zones & Layering 3D Grid Construction Structural Framework 3D Grid Construction Structural Gridding Surfaces and Data edit Stratigraphic Modeling Interface Intro to Petrel Workflow Editor Pillar Gridding 3D Geological Modeling Workflow Introduction 3D Grid Construction: Structural Modeling Studio Fault Modeling Make contacts & Volume Calculation Property Modeling Facies & Petrophysical Modeling Well Log Upscale

  8. New Algorithms- Structural Modeling

  9. New Algorithm- Model Update

  10. New Algorithm-Model Update Facies New well shows low NTG compared to 3D model Facies updated in region around new well Porosity Petrophysics updated in region around new well Updated model Original model

  11. Improved Algorithm-Integration with Seismic Seismic Technology can identify Geobodies Geobodiescan be incorporated in reservoir models for better charchaterization Move from stochastic to semi-deterministic

  12. Improved Algorithms- Integration of Various Data • Initial Model Built from geological data, geophysical and petrophysical data • Well Testing provides additional information • Models can be calibrated to handle additional information Distance conditioning No Distance conditioning

  13. New Algorithms- Capturing Reality • 15 biggest geobodies extracted • Well match Conditioned Simulation (Hard Data)

  14. Dealing with Uncertainty Uncertainty spectrum is very important for marginal fields Evaluation of scenario uncertainty is more important than generating multiple realizations for marginal fields

  15. Scenario 1: Petrel geo model 1 Scenario 2: Petrel geo model 2 Scenario 3: Petrel geo model 3 3_2 3_1 2_N 2_1 3_N 1_2 1_1 3_3 2_2 1_N Handling Different Scenarios and Realizations in Petrel • Use nested approach: For each scenario, run multiple realizations. • The Cases pane is used to organize the results. Realizations: . . . . . . . . . Volume distributions:

  16. Technical Advantages Fast Model Building Better integration with various data Rapid model updates Easy and Simple Workflow Faster & Better Decision Making

  17. Conclusion New geological concepts development New Data Acquisitions Technology (Logs, Seismic) New & Improved Interpretation techniques Integrated Solutions & Multidisciplinary studies Project Management

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