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Document Type : Latin Dissertation
Language of Document : English
Record Number : 151130
Doc. No : ET22922
Main Entry : Abdulrahman F. AL-Rashidi
Title Proper : Designing Neural Networks for the Prediction of the Drilling Parameters for Kuwait Oil and Gas Fields.
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : In this study a new methodology was developed to predict the drilling parametersusing the Artificial Neural Network. Three models were developed to predict bit type,rate of penetration (ROP), and cost-per-foot (cost/ ft), respectively.The prediction of bit type and other drilling parameters from the current availabledata is an important criterion in selecting the most cost efficient bit. History of bit runsplays an important factor in bit selection and bit design. Based on field data, the selectionof bit type can be accomplished by the use of a neural network as an alternative bitselection method.Three drilling parameters were modeled with data from different fields located inKuwait. Results show that the drilling parameters of the new well can be predicted withthe neural network models developed from the previous wells, a cost efficient alternative...,....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL46150.pdf
Title and statement of responsibility and : Designing Neural Networks for the Prediction of the Drilling Parameters for Kuwait Oil and Gas Fields. [Thesis]
 
 
 
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