• شماره ركورد كنفرانس
    2953
  • عنوان مقاله

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

  • عنوان به زبان ديگر
    Correction of Drill-off Test Error Using Artificial Neural Network and Mechanical Specific Energy
  • پديدآورندگان

    Yavari Hossein نويسنده , Fazaelizadeh Mohammad نويسنده , Khosravanian Rasool نويسنده , Hassani Vahab نويسنده

  • تعداد صفحه
    1
  • كليدواژه
    Rate of Penetration , Artificial neural network , CCS , Weight on Bit , mechanical efficiency , Mechanical Specific Energy
  • سال انتشار
    1395
  • عنوان كنفرانس
    دومين كنفرانس ملي ژئومكانيك نفت : كاهش مخاطرات اكتشاف و توليد
  • زبان مدرك
    فارسی
  • چكيده لاتين
    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
  • شماره مدرك كنفرانس
    4411868
  • سال انتشار
    1395
  • از صفحه
    1
  • تا صفحه
    1
  • سال انتشار
    1395