Tezislər / Theses

THE 3
rd
 INTERNATIONAL SCIENTIFIC CONFERENCES OF STUDENTS AND YOUNG RESEARCHERS 
dedicated to the 99
th
anniversary of the National Leader of Azerbaijan Heydar Aliyev
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other machine, formation or human related factors can also affect quality of 
simulation and subsequently optimization process. Actions that are needed 
to be done will be stated in appropriate section of this paper. Apart from 
simulation or optimization, proper drill bit selection should be done and 
design and material of the selected bit should also be taken into 
consideration as resistance of the drill bit to the well conditions can be 
satisfied by appropriate selection of bit and its material and proper designing. 
It has to be stated that determination of UCS from sonic log results is not 
significantly effective as log results can be affected by extra properties and 
factors. As (George A. Cooper, 2003) it was stated, the rock strength, which 
governs the rate of penetration of the drill bit, and the abrasive, which 
controls the rate of wear, are the fundamental rock parameters required as 
inputs for a drilling simulator., and the rock type or mineralogy, which has an 
important secondary effect on both the rate of penetration and wear. George 
A. Cooper and Peter Hatherly had tried to calculate these properties from 
wireline logging results. It should be admitted that by using ARS data from 
nearby drilled wells, perfectly matched simulation of new well cannot be 
gotten as there are several affecting factors that can be inevitable to become 
avoided. Issues can vary from an insufficient description of the geometry of 
the bit that was or will be utilized to ambiguity about the nature of the rock 
being penetrated and/or its level of pressurization. These sorts of issues can 
be avoided by using a method in which the simulator is "tuned" to mimic the 
drilling behavior under a known set of parameters that are as close to those 
of the well under investigation as feasible. Thus, if the rate of penetration of 
a specific type and style of drill bit is known at a depth and in rock types 
similar to those for which some future behavior is intended, tuning the 
simulator to match the known historical record allows to avoid having to 
predict the drilling behavior from first principles. (George A. Cooper, 2003) It 
can also be added that due to significant improvements in AI (Artificial 
Intelligence), neural networks has been used for several purposes including 
identifying UCS. F. Meulenkamp, M. Alvarez Grima (F. Meulenkamp, 1999) 
used back-propagation supervised neural network and predicted values for 
UCS are close to actual values of them. In addition to mentioned methods 
above application of AI and GEP can be regarded as the most attractive 
methods for determination of UCS among non-destructive methods. Once 
UCS has been defined, adequate simulation of ROP can be done though 
special software after which optimization of drilling process can be achieved. 
By means of appropriate drilling process simulation, relevant optimization of 
some parameters for efficient drilling can be operated. Specific Energy 
Method has been used for appropriate bit selection and R. K. Abbas 
analyzed several wells drilled and drill bits used for conducting appropriate 
bit selection by using Specific Energy Method (Abbas, 2007). In addition to 

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