CIVILICA We Respect the Science
(ناشر تخصصی کنفرانسهای کشور / شماره مجوز انتشارات از وزارت فرهنگ و ارشاد اسلامی: ۸۹۷۱)

Correction of Drill-off Test Error Using Artificial Neural Network andMechanical Specific Energy

عنوان مقاله: Correction of Drill-off Test Error Using Artificial Neural Network andMechanical Specific Energy
شناسه ملی مقاله: NPGC02_053
منتشر شده در دومین کنفرانس ملی ژئومکانیک نفت در سال 1395
مشخصات نویسندگان مقاله:

Hossein Yavari - M.Sc Student at Amirkabir Universityof Technology, Drilling Engineering
Mohammad Fazaelizadeh - Faculty Member of Amirkabir University of Technology
Rasool Khosravanian - Faculty Member of Amirkabir University of Technology
Vahab Hassani - Head of Bit Operation & Drilling Optimization, Dana Energy

خلاصه مقاله:
Drill-off test is used to determine the optimum WOB and RPM during drilling. In this test the WOB that gives the highest ROP is considered as the optimal value. In 1991, Bourgoyne et.al introduced the maximum rate of penetration point as a non-optimal point because at this point available hydraulic cant clean underneath the bit and the bit crushes cuttings from previous step for another time, causing over wearing of the bit, bit balling and vibrations. The point that has the minimum MSE and maximum mechanical efficiency is the optimal point. This point is called founder point.

کلمات کلیدی:
Mechanical Specific Energy, Rate of Penetration, Artificial Neural Network, Mechanical Efficiency, Weight on Bit, CCS

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/611521/