期刊名称:Current Journal of Applied Science and Technology
印刷版ISSN:2457-1024
出版年度:2018
卷号:28
期号:5
页码:1-10
语种:English
出版社:Sciencedomain International
摘要:Over the past decades, various methods have been proposed to evaluate drilling depth and complexity because of the large number of factors and events that affect drilling performance, which makes it difficult to construct predictive models. Quantifying drilling oil well depth and complexity is challenging due to restrictions on data collection and availability, constraints associated with modeling or combinations of these factors. Drill rates are often not documented and constrained by factors that the driller does not control. In large investments, the requirements to drill for oil and gas are made primary by oil companies. Many specialized talents are required to drill an oil well safely and economically. Estimation of the depth of oil well is one of the major concerns of oil companies today. The aim of this paper is to study and analyze the associated depth drilling parameters, and to run a comparative analysis of simulated events and regression model software values by adopting mathematical model of multiple regression that transform into programming technique for predicting total depth of drilling oil well. Visual Basic Net programming language (front-end) and Microsoft Access Database relational database management (back-end) were used in the research work for the experimental study. The implemented software has a performance accuracy of 93.94%. The data series explained that higher the drill depth more is the total cost.
关键词:Impact;drilling;parameter;oil well depth;predictive model