Title of article :
A new methodology for the identification of best practices in the oil and gas industry, using intelligent systems
Author/Authors :
Mohaghegh، نويسنده , , Shahab D.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2005
Pages :
22
From page :
239
To page :
260
Abstract :
In this paper the theory and methodology of “Intelligent Best Practices Analysis” is presented. The methodology is then applied to a database of stimulation practices in the Golden Trend fields of Oklahoma to demonstrate its use and benefits. Golden Trend fields of Oklahoma, like many other oil fields, the outcome of stimulation jobs have not been the same for all wells. The effectiveness of the stimulation is a function of several factors including reservoir quality, completion and stimulation practices. Completion and stimulation practices can be further itemized as completion type such as open hole versus cased hole with perforations and the type and amount of fluids and proppants that is used during the stimulation and the rate at which they are pumped into the formation. stimulation data from more than 230 wells in the Golden Trend operated by three independent operators were collected and analyzed using this methodology. The study was performed both for gas and oil bearing formations. The Best Practices Analysis pointed out that in the carbonate formations of the Golden Trend that are primarily gas producing, acid fracs are much more effective than acid jobs (where no proppant is pumped into the formation). For the clastic formations in the Golden Trend, from which both oil and gas are produced, the Best Practices Analysis showed that most effective fluids were those with a diesel oil base. Furthermore the analysis concluded that the formations in the Golden Trend respond best to frac jobs with proppant concentration of 1 lb/mgal/ft or higher that are injected at rates up to 1 gal/min/ft.
Keywords :
best practices , Intelligent systems , Golden trend
Journal title :
Journal of Petroleum Science and Engineering
Serial Year :
2005
Journal title :
Journal of Petroleum Science and Engineering
Record number :
2218638
Link To Document :
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