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Decline Curve Analysis and Reserves Estimation for Production Engineers

02 – 06 Feb. 2026, Abu Dhabi06 – 10 July 2026, Abu Dhabi

COURSE OVERVIEW:

Decline Curve Analysis (DCA) and Reserves Estimation for Production Engineers is a fundamental technical course designed to quantify the future potential of oil and gas assets. As a well or field matures, the rate of production inevitably declines; understanding the nature of this decline is critical for financial forecasting, operational planning, and investment decision-making. This course provides production engineers with the empirical and analytical tools necessary to project future performance based on historical data.

 

The scope of this program focuses on the Arps decline models exponential, hyperbolic, and harmonic—and their application in various reservoir types. Participants will learn how to clean and normalize production data to remove the "noise" caused by operational downtime or changes in artificial lift, ensuring that the resulting decline curves represent the true reservoir potential. The curriculum emphasizes the link between DCA and the broader classification of reserves (Proved, Probable, and Possible) as defined by the Petroleum Resources Management System (PRMS).

 

Coverage also includes the use of diagnostic plots, such as the Fetkovich and Blasingame types, which allow engineers to differentiate between reservoir depletion and wellbore issues. Attendees will learn how to estimate the Remaining Useful Life (RUL) of an asset and determine the Estimated Ultimate Recovery (EUR). By mastering these techniques, production engineers will be able to provide accurate forecasts that inform workover candidates, facility sizing, and long-term asset strategy.

 

COURSE OBJECTIVES:

After completion of this course, the participants will be able to:

  • Explain the theoretical basis of Arps Decline Curve Analysis.
  • Distinguish between Exponential, Hyperbolic, and Harmonic decline models.
  • Identify the correct decline exponent (b-value) for different drive mechanisms.
  • Perform data normalization and "grooming" to prepare production history for analysis.
  • Estimate the Remaining Recoverable Reserves (RRR) and Estimated Ultimate Recovery (EUR).
  • Apply the Petroleum Resources Management System (PRMS) definitions to reserves.
  • Use diagnostic plots to identify changes in drainage area or well performance.
  • Integrate Decline Curve Analysis with Material Balance for improved accuracy.
  • Predict the economic limit of a well based on operating costs and oil price.
  • Evaluate the impact of workovers and stimulations on the decline profile.
  • Perform probabilistic reserves estimation using Monte Carlo simulation basics.
  • Utilize software tools to generate automated production forecasts.
  • Document and report reserves estimates for regulatory and corporate audits.

 

TARGET AUDIENCE:

Production Engineers, Reservoir Engineers, Asset Evaluators, and Technical Managers involved in production forecasting and reserves reporting.

 

TRAINING COURSE METHODOLOGY:

A highly interactive combination of lectures, discussion sessions, and case studies will be employed to maximise the transfer of information, knowledge, and experience. The course will be intensive, practical, and highly interactive. The sessions will start by raising the most relevant questions and motivating everybody to find the right answers. The attendants will also be encouraged to raise more of their questions and to share in developing the right answers using their analysis and experience. There will also be some indoor experiential activities to enhance the learning experience. Course material will be provided in PowerPoint, with necessary animations, learning videos, and general discussions.

 

The course participants shall be evaluated before, during, and at the end of the course.

 

COURSE CERTIFICATE:

National Consultant Centre for Training LLC (NCC) will issue an Attendance Certificate to all participants completing a minimum of 80% of the total attendance time requirement.

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