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Predicting Organic Shale Well Performance
Robert 'Bob' Barba

INSTRUCTOR: Robert “Bob” Barba
DISCIPLINE: Engineering, Unconventional Reservoirs
CEUS: 1.6
AVAILABILITY: Public, In-House, & Live Online

Check back in periodically for updated Public and Live Online course dates! To schedule an In-House course, contact SCA’s Training Department at

SAMPLE TOPICS FROM THE CLASS: "Using Logs and Production Data to Predict Organic Shale EURs" "Organic Shale Refracs - Can They Be Economically Done at Current Prices?"

WHO SHOULD ATTEND: Engineers, geoscientists, asset managers who want to develop techniques for predicting well performance in organic shale reservoirs by integrating petrophysical analysis with rock properties, production data.

COURSE DESCRIPTION: Petrophysical analysis of organic shale reservoirs is more complicated than analysis of conventional reservoirs.  The presence of kerogen in organic shale reservoirs introduces a level of complexity into petrophysical analysis process for estimating hydrocarbons in place. Traditional TOC based models are complicated by presence of mobile oil with kerogen that makes volume of kerogen in rock difficult to estimate.  Even with an accurate kerogen volume, physical properties are not well characterized.  Most organic shale reservoirs have complex minerals that complicate a straight volumetric approach. Rock mechanics and proppant transport issues introduce complexity.  The petrophysical analysis process uses Powerlog Synthetic Curve Generator which ties log/core data to estimate hydrocarbons in place. An estimate is made of producing height and a comparison is made to production data with height above proppant bank a function of rock brittleness.  Operators can “forward model” landing zone performance prior to drilling a lateral.  Recovery factors are a function of the frac treatment intensity and forecasts can be made for previously fracced areas with larger fracs.  The flexibility of Powerlog program allows for robust models for simple “triple combo” log suites following calibration of the model to core and/or specialty log data.  Participants are encouraged to provide local case studies to develop models specific to wells in the course.



  • Develop a calibrated petrophysical model to estimate hydrocarbons in place
  • Learn techniques to integrate OIP/GIP data with rock properties and production data to estimate recovery factors as a function of frac vintage
  • Develop well performance models specific to reservoirs and export equations for application in reservoirs


  • Basic log analysis techniques
  • Log quality control, normalization
  • Calibration of Vclay, porosity, Sw to core, production data
  • Net pay cutoff estimation
  • Recovery factor model data requirements
  • Rock properties model development
  • Production decline curve analysis
  • Log analysis exercises
  • Case studies with calculation of OIP and comparisons to EUR
  • “Best Practices” incorporating OIP and rock properties data