Production Engineering

1. Course Description

This course provides students with the knowledge and integrated analytical methods required to evaluate, diagnose, and optimize the production performance of oil wells, gas wells, and integrated reservoir–well–surface systems. The course covers oil- and gas-well deliverability; construction and analysis of inflow performance relationship (IPR) and vertical lift performance (VLP) curves; nodal analysis; evaluation of formation damage and skin factor; production decline analysis and forecasting; production monitoring and diagnosis of causes of productivity deterioration; evaluation of artificial-lift performance; selection and assessment of production-improvement measures, including adjustment of operating conditions, acid stimulation, and hydraulic fracturing; and integrated production optimization considering technical, safety, environmental, and economic constraints.

Major topics include:

  • Oil- and gas-well deliverability.

  • Inflow performance relationship (IPR), vertical lift performance (VLP), and nodal analysis.

  • Formation damage, skin factor, and diagnosis of productivity deterioration.

  • Production decline analysis and forecasting.

  • Production monitoring and artificial-lift performance evaluation.

  • Evaluation of production-improvement alternatives, including the selection and performance assessment of well-stimulation options.

  • Integrated production optimization and technical, economic, and environmental evaluation.

  • Application of digital tools and appropriately validated artificial intelligence (AI) tools in engineering analysis.

2. Course Objectives

The course aims to enable students to apply engineering, scientific, and mathematical knowledge to analyze well production performance; diagnose factors that limit production; forecast production trends; and select and evaluate alternatives for production improvement and optimization. The course also develops students’ ability to make data-driven engineering decisions while considering safety, environmental, and economic constraints; communicate technical information effectively; and responsibly use information sources, digital tools, and artificial intelligence in solving production engineering problems.