Full-Field Production Optimization Training Course

Full-Field Production Optimization Training Course

Introduction

Full-Field Production Optimization Training Course is designed to equip oil and gas professionals with the advanced technical knowledge, analytical capabilities, and strategic decision-making skills required to maximize hydrocarbon production across entire oil and gas fields. This course explores the critical principles of production engineering, reservoir performance optimization, well productivity enhancement, artificial lift optimization, flow assurance, surface facility management, and integrated asset modelling. Participants will learn how to identify production bottlenecks, diagnose declining well performance, manage reservoir uncertainties, and develop data-driven strategies that improve production efficiency throughout the field lifecycle.

The programme emphasizes the integration of subsurface engineering, well operations, surface production systems, and digital technologies to achieve sustainable production growth. Participants will explore production allocation, well testing, nodal analysis, production forecasting, water and gas management, artificial lift performance, constraint-based optimization, and economic evaluation of production improvement opportunities. By the end of the training, delegates will be better prepared to develop integrated field optimization plans, prioritize high-value interventions, enhance operational reliability, reduce unplanned downtime, and deliver measurable improvements in oil and gas production, asset profitability, recovery efficiency, and long-term field performance.

Course Duration

5 days

Course Objectives

By the end of this course, participants will be able to:

1. Explain the principles of full-field production optimization and their application to integrated oil and gas asset management.
2. Evaluate reservoir performance using advanced reservoir surveillance, production data analytics, and decline curve analysis.
3. Identify production bottlenecks through well performance diagnostics, nodal analysis, and system-wide constraint analysis.
4. Optimize well productivity using advanced production engineering techniques and inflow performance analysis.
5. Improve artificial lift performance through ESP optimization, gas lift optimization, and intelligent well monitoring.
6. Apply integrated asset modelling (IAM) to coordinate reservoir, well, gathering network, and processing facility performance.
7. Utilize digital oilfield technologies, real-time monitoring, and predictive analytics to improve operational decisions.
8. Develop effective strategies for water production management, gas handling, and unwanted fluid production control.
9. Evaluate flow assurance risks, including scale deposition, corrosion, wax formation, hydrates, and pipeline pressure losses.
10. Optimize production facilities by identifying processing constraints, equipment limitations, and capacity utilization opportunities.
11. Apply production forecasting, scenario modelling, and uncertainty analysis to support field development and optimization decisions.
12. Conduct economic evaluation, production opportunity ranking, and value-based intervention planning to maximize asset returns.
13. Develop an integrated continuous improvement and production optimization roadmap incorporating operational excellence, digital transformation, and sustainable production practices.

Target Audience

1. Petroleum and Production Engineers.
2. Reservoir Engineers and Reservoir Management Specialists.
3. Well Intervention and Well Services Engineers.
4. Artificial Lift and Completion Engineers.
5. Field Operations and Production Supervisors.
6. Asset Managers and Integrated Asset Planning Teams.
7. Process, Facilities, and Flow Assurance Engineers.
8. Oil and Gas Consultants, Technical Specialists, and Production Optimization Managers.

Course Modules

Module 1: Fundamentals of Full-Field Production Optimization

• Principles, objectives, and value drivers of full-field production optimization.
• Integration of reservoir, well, gathering network, and surface facilities.
• Production system hierarchy and identification of field-wide constraints.
• Key performance indicators (KPIs): production efficiency, uptime, recovery, and operating costs.
• Case Study: Evaluating an ageing oilfield to identify production losses and prioritize high-impact optimization opportunities.

Module 2: Reservoir Surveillance and Production Performance Analysis

• Reservoir pressure monitoring and production trend interpretation.
• Decline curve analysis and production forecasting techniques.
• Material balance concepts and reservoir performance assessment.
• Water cut, gas-oil ratio (GOR), and fluid production trend analysis.
• Case Study: Diagnosing declining production in a mature field using well histories, pressure data, and reservoir surveillance indicators.

Module 3: Well Performance Diagnostics and Productivity Enhancement

• Inflow performance relationships and outflow performance analysis.
• Nodal analysis for well and production system optimization.
• Identification of skin damage, pressure losses, and productivity limitations.
• Well testing, production logging, and diagnostic data interpretation.
• Case Study: Restoring production from underperforming wells by identifying near-wellbore damage and tubing-related restrictions.

Module 4: Artificial Lift Optimization and Well Intervention Planning

• Selection and optimization of electric submersible pumps (ESPs).
• Gas lift design, injection gas allocation, and performance tuning.
• Rod pump optimization and operating parameter analysis.
• Intelligent well monitoring and artificial lift failure diagnostics.
• Case Study: Optimizing artificial lift operations across a multiwell field to improve production while reducing energy consumption and equipment failures.

Module 5: Integrated Asset Modelling and Production Network Optimization

• Fundamentals of integrated asset modelling (IAM).
• Production gathering systems, pipeline hydraulics, and network simulation.
• Pressure and flow distribution across wells, manifolds, and processing facilities.
• Constraint-based optimization and production allocation strategies.
• Case Study: Using integrated production modelling to redistribute flow and remove network bottlenecks across a field with constrained processing capacity.

Module 6: Flow Assurance and Surface Facility Optimization

• Identification and mitigation of wax, scale, hydrate, and corrosion risks.
• Separator performance, gas handling, and processing capacity optimization.
• Pipeline pressure-drop analysis and multiphase flow behaviour.
• Produced water treatment, reinjection, and fluid handling optimization.
• Case Study: Resolving recurring flow restrictions and separator capacity limitations to improve production stability and reduce unplanned shutdowns.

Module 7: Digital Oilfields, AI, and Advanced Production Analytics

• Digital oilfield architecture and real-time production surveillance.
• Application of artificial intelligence and machine learning in production optimization.
• Predictive maintenance and anomaly detection for production equipment.
• Automated production allocation, dashboards, and decision-support systems.
• Case Study: Developing a data-driven surveillance workflow to detect abnormal well behaviour and prioritize interventions before major production losses occur.

Module 8: Production Forecasting, Economics, and Continuous Optimization

• Production forecasting under operating and reservoir uncertainties.
• Opportunity identification, screening, and value-based prioritization.
• Economic evaluation using incremental production, intervention costs, and net present value (NPV).
• Development of integrated field optimization plans and performance monitoring frameworks.
• Case Study: Preparing a full-field optimization plan that compares workovers, artificial lift upgrades, facility debottlenecking, and digital surveillance initiatives based on expected production gains and economic returns.

Training Methodology

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.