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Production Forecasting For Low Permeability Reservoirs

W. John Lee, PhD
INSTRUCTOR: W. John Lee, PhD
DISCIPLINE: Engineering, Unconventional Reservoirs
COURSE LENGTH: 2 Days (Classroom) / 4 Half-Day Sessions (Live Online)
CEUS: 1.6
AVAILABILITY: In-House & Live Online
ATTEND AN UPCOMING CLASS:
Check back in periodically for updated Public and Live Online course dates! To schedule an In-House course, contact SCA’s Training Department at training@scacompanies.com.
SAMPLE TOPIC FROM THE CLASS: “Identifying Flow Regimes: A Big Assist for Production Forecasting”

WHO SHOULD ATTEND: Engineers, geologists, financial analysts, investors, bankers, or anyone who needs to understand traditional and recent methods to forecast production for low-permeability oil and gas reservoirs.

COURSE DESCRIPTION: This course summarizes decline curve analysis (DCA), including Arps’ decline models, linear flow models, and other recent decline analysis approaches. We provide background information on basic fluid flow theory, which enhances understanding of strengths and limitations of both traditional and recent decline analysis methods. Numerous short class exercises illustrating principles will be included.

LEARNING OUTCOMES:

  • State assumptions and limitations of Arps and other decline models
  • Analyze production histories and forecast production using Arps and other decline models for low-permeability reservoirs
  • Analyze production histories and forecast production using the Fetkovich type curve
  • Outline systematic forecasting procedures combining rate-transient analysis (RTA), decline curve analysis, numerical and analytical reservoir models

COURSE CONTENT:

  • Basic fluid flow fundamentals underlying DCA and RTA
  • Flow regime identification
  • Arps decline model
  • Fetkovich and other type curves
  • Alternative decline models: stretched exponential, power law, long-duration linear flow, Duong model
  • Comparison of decline models
  • Systematic procedure for DCA
  • Overview of RTA, including systematic work flow for applications

Required materials: Laptop computer equipped with Microsoft Excel (for class problem solution)

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