Westside: Comparison of Numerical vs Analytical Models for EUR Calculation and Optimization in Unconventional Reservoirs

Speaker Jim Erdle, Vice President, Computer Modelling Group
Jim is currently Vice President for software marketing and support for the USA and Latin America. He has over 40 years of industry experience, primarily in reservoir and production engineering-related positions within the service and software segments of E&P. He graduated from Penn State with BS and PhD degrees in ...

Jim is currently Vice President for software marketing and support for the USA and Latin America. He has over 40 years of industry experience, primarily in reservoir and production engineering-related positions within the service and software segments of E&P. He graduated from Penn State with BS and PhD degrees in petroleum engineering. He has coauthored a number of SPE papers on the subject of modelling unconventional wells, and is the author of Chapter 8 (“Application of Numerical Models”) in the 2016 SPEE Monograph #4 (Estimating Ultimate Recovery of Developed Wells in Low-Permeability Reservoirs).


 

Full Description

Analytical models available in Rate-Transient-Analysis (RTA) packages are widely used as fast tools for history matching and forecasting in unconventional resources. Recently, there has been an increasing interest in numerical simulation of unconventional reservoirs. In this presentation, both methods will be used to history-match fractured unconventional wells, followed by the application of forecast calculations. A single-phase shale oil reservoir will be used as a base case, but dry gas and gas condensate shale reservoirs will also be examined. In all cases, historical data and reference EUR’s are derived from fine-grid simulations.

The data presented will demonstrate an excellent match between the two methods for the base case, but when real-world deviations from RTA assumptions are applied, the analytical model requires key reservoir and fracture parameters to be drastically modified in order to match the historical production data. Results will also show that these history-matched models may not be predictive for future production, providing highly pessimistic EUR’s in most real-world scenarios. For the cases presented, analytical models under-predict EUR’s by 10-20% despite good history matches of two-year production. For all cases presented, an efficient simulation workflow for probabilistic forecasting of brown fields was applied. This workflow provided multiple history-matched models that were constrained by historical production data.

 

Organizer Bharath Rajappa

Telephone:  (832) 486-3122          Email: bharath.rajappa@conocophillips.com

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When?

Wed, Nov. 15, 2017
11:30 a.m. - 1 p.m. America/Chicago

How Much?

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Where?

Norris Westchase Center
9990 Richmond Ave., Suite 102
Houston, TX 77042

Parking for the Norris Conference Center is on the roof level of the garage. Enter the parking garage through the Richmond entrance.

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