A presentation done by Neelendra Nath in 2009 at MIT, Pune on techno-managerial approach to reservoir management using computer based algorithm.

1. PetroFirst
Raising Reservoirs : A Techno-Managerial Approach
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2. Content
 Introduction
 Reservoir Management – Team & Process
 A Technological Approach
 Self Learning Reservoir Management
 MPC & NPV Optimization
 Case Study
 Conclusion
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3. Did you know…?
“ About 70% of crude oil production on the global scale comes from matured
fields more than 30 years old and recovery from these fields are only 30-40%.
Further, Reserve depletion from producing assets have always outpaced the
reserve accretion from new fields. ”
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4. Reservoir Management
Data
• Geological
• Geophysical
• Engineering Tools
• Financial
• Seismic Interpretation
Technology • Tomography
• Data Acquisition
• Seismic • Logging/Coring
• Geologic • Completion & Facilities
Integration •
• Geostatistics Geologic Modeling
• Engineering • Pressure Transient
• Drilling & Completion • Fracturing
• Enhanced Oil Recovery • Reservoir Simulation
• Computer • Enhanced Oil Recovery
People • Computer Software &
Hardware
• Management
• Geoscientists
• Engineers
• Land/Legal
• Field
• Financial
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5. Reservoir Management
Objectives
Decreasing Risk
Increasing Production
Maximizing Recovery
Minimize Capital Expenditure
Minimizing Operating Cost
Maximize Profitability
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6. Management Team
Management Geology &
Legal Geophysics
Reservoir
Land Engineering
Economics
Environment
Reservoir
Management
Team Drilling
Engineering
Services
Design & Construction
Engineering
Research &
Development
Production & Operation
Engineering
Gas & Chemical
Engineering
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7. Management Team
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8. Management Process
Setting Strategy
Developing Plan
Implementing
Revising
Monitoring
Evaluating
Completing
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9. Management Process
Revising
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10. A Technical Approach
Why is it
required ? How it
works?
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11. Self Learning Reservoir Management
 [ qok qwk qgk ] = [ 1 p-k pwfk (pwfk)2] Matrix3x3 [ a, b, c]
 [(p^)k] = [ d0 d1 d2 d3 d4 d5 ][ 1 ṕk-1 q0k-1 qwk-1 qgk-1 qwik-1 ]T
Parametric
Fluid Flow
Modeling
NPV
Optimization
Model
Predictive
Control
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12. Model Predictive Control
Process model for Online
Computation of
Class of Computer online prediction optimization of a
appropriate control
Control Algorithm of future plant cost objective over
action
behaviour a future horizon
ỹqk+t|k = ∑(i=1 to nU)∑(j=1 to p)(hijq)( uik-j+t) + dqk|k
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13. NPV Optimization
 Linear Programming optimization routine is use to find optimum solution.
Assumption : Future reservoir behavior is described by current
model(Certainty Equivalent Principle)
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14. Conclusion
1. A team approach based on integration of geosciences and engineering
personnel, tools, technology and data is essential for sound reservoir
management practice.
2. A better understanding of integrated approach and technology can be
beneficial to geoscientists, engineers, field operations staff and
managers.
3. Technological advances and computer power are providing the tools to
manage reservoir better to maximize economic hydrocarbon recovery.
4. A multi-level self adaptive reservoir management strategy work
wonders in term of increasing recovery factor and optimizing
economics.
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15. Reference & Further Reading
• Thakur, G.C.: “Reservoir Management- A Synergistic Approach.” paper SPE
20138 presented at the 1990 SPE Permian Basin Oil and Gas Recovery
Conference, Midland, March 8-9
• Wiggins, M.L.: A Manual of Petroleum Reservoir Management, Crisman
Institute for Petroleum Management, Dept. Of Petroleum Engineering, Texas
A& M U.(May 1989)
• Satter, A.: “ Reservoir Management Training- An Integrated Approach.” paper
SPE 20752 presented at the 1990 SPE ATCE, New Orleans, Sept. 23-26
• Thakur, G.C.: “Implementation of Reservoir Management Programme.” paper
SPE 20748 presented at the 1990 SPE ATCE, New Orleans, Sept. 23-26
• Satter, A. et al.: “ Integrated Reservoir management,” paper SPE 22350
presented at the 1992 SPE International Meeting on Petroleum Engineering,
Beijing, China, March 24-27
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