Forecasting Well Production Data in Unconventional Resources
This 1-day course provides a comprehensive methodology for the diagnosis, analysis, and forecasting of well production data in unconventional resources. An extensive evaluation of the diagnostic tools for assessing data viability, checking data correlation along with flow regime identification is presented. The principal focus of the course is to diagnose the characteristic flow regimes associated with well production and to apply methodologies to estimate performance parameters and forecast production. These methodologies include simple analytical tools, decline curves, and more complex techniques such as non-linear numerical simulation. Examples from tight gas sands, gas shales, and liquids-rich shale systems will illustrate the theoretical considerations and practical aspects of the analysis and forecast techniques. A course notebook will be provided with copies of PowerPoint slides and a list of reference materials.
- Learn how to collect, analyze, and interpret critical data for well performance analysis
- Identify well performance characteristics and flow regimes using diagnostic plots
- Estimate key reservoir and completion parameters using model-based production analysis
- Forecast future performance of single/multiple well(s) for various production/completion and field development scenarios
- Establish the optimal workflow to help quantify well performance uncertainty and non-uniqueness
Who Should Attend
This course is suitable for technologists, engineers, and engineering managers involved in the evaluation of well performance (time-rate-pressure) data for optimizing production, understanding completion efficiency, and estimating reserves and ultimate recoveries.
Why You Should Attend
Production analysis and forecasting in unconventional resources are challenging tasks due to the high degree of uncertainty and non-uniqueness associated with evaluating well completion and understanding reservoir properties. This course provides guidelines on the interpretation of data behavior and a consistent approach to analyzing and forecasting production in unconventional resources.
0.8 CEUs (Continuing Education Units) will be awarded for this 1-day course.
To receive a full refund, all cancellations must be received in writing no later than 14 days prior to the course start date. Cancellations made after the 14-day window will not be refunded. Send cancellation requests by email to firstname.lastname@example.org; by fax to +1.866.460.3032 (US) or +1.972.852.9292 (outside US); or mail to SPE Registration, PO Box 833836, Richardson, TX 75083.
For more details, please contact us at email@example.com.
Dilhan Ilk is a reservoir engineer at DeGolyer and MacNaughton in Dallas, Texas. He holds BSc degree from Istanbul Technical University, MSc and PhD degrees from Texas A&M University—all in petroleum engineering.
Ilk's interests include analysis of well test and production data, reservoir engineering, and inverse problems. In particular, he focuses on well performance analysis in unconventional reservoirs and has extensive field experience in well performance assessment of unconventional reservoirs. He has made several contributions to petroleum engineering literature, and to date, has prepared more than 30 articles in well test analysis, analysis/interpretation of production data, and general reservoir engineering.