About Academy  |  About IRBAS  |    Contact Us                                                                                                                                  ISSN (Online) : 2308-7056

International Review of Basic
and Applied Sciences (IRBAS)

Home     Editorial Board     Current Issue     Archive     Indexing      Call for papers     Authors Guideline      Manuscript Submission      Contact

News & Events

Thursday, September 10, 2020
IRBAS Volume 8 Issue 4 will publish in October 2020.
Thursday, September 10, 2020
IRBAS Volume 8, Issue 3 has been published.
Thursday, September 10, 2020
IRBAS Published on Quarterly basis from Volume 8.
Tuesday, January 17, 2017
Recruitment of Reviewers. Reviewers name and affiliation will be listed on the IRBAS journals webpage.

IRBAS Citation Report

  All Since 2020
 Citation  118 17
 h-index 06 01
 i10-index 03 01

Hit Counter

Total 476371
Today's 172
Yesterday's 118

 Country Wise Counter

Academy Publication Ethics

Academy of IRMBR Volume  6, September, 2018
Move your mouse curser on the title to view the abstract of the paper
S.No. Title Authors Pages Download
Risk Analysis in Drilling of Oil and Gas Wells in Libya and How to Overcome These Problems
Drilling of oil field is always accompanied with risk factors in regard of safety and investments. A branch of science called as Enhanced Drilling Reach (EDR) is dealing with the steps and procedures to be taken for prevention of risks and enhancement of drilling quality for optimizing the oil projects worthiness i.e. efficiency. EDR is usually involves methods to evaluate the maximum depth of oil well, however, the most proposed methodologies in the related literate can be using the Artificial Neural Network logic to predict the drilling parameters whereas drilling efficiency is maximized. In this article, we proposed a novel approach that proactively analyze the risks of drilling oil wells. The performance of the said approach is tested with various situations and the same is reported a noticeable safety and economical efficiencies. The study that based on Artificial Neural Network is applied on EE123 petrol field in south Libya is aimed to predict the safety of drilling the said well i.e. EE123 before actually it been drilled; the result of this study shows that only 54% is the safety level if this well world been drilled. Keywords: Libyan Economy, Oil, Gas, Layers, Field, Assessment, Neural Network, Pre-processing.

Copyright © www.academyirmbr.com : 2012-21. All Rights Reserved.