Multi Regression Analysis to Suggest Optimum Drilling Weight On Bit and Penetration Rate for Optimum Rate of Penetration Propose Well
Abstract
R is a system for analyzing statistical data included in open source software group or also called freeware. R software less popular when compared with other paid statistical software such as SPSS, MINITAB, SAS or Eviews. Limited references and support especially in Indonesian, is one of the reasons statistical users prefer commercial statistical packages over free R software and provide results that are no less powerful and interesting graphics systems. Among many statistical techniques that R software can accomplish, one of the most popular is multiple regression analysis. In this article, we will discuss about multiple regression analysis modeling using R software as an alternative software for determining Weight on Bits (WOB) and optimal Rate of Penetration (RPM) in oil and gas drilling. Multi-regression analysis aims to get maximum drilling rate at drilling process, which is reduce drilling time and drilling cost. Bourgoyne and Young ROP models have been chosen to observe effects of several parameters during drilling operations such as drilling depth, pore pressure, equivalent circulation density, bit weight, rotating speed, bit tooth wear and jet collision force were extracted from the final drilling report. Results of the analysis are used to determine the optimum value of the weight of the bit which provides optimal drilling operations and optimized WOB has been calculated for several data points. the results show that R software can be used for multi regression analysis, and and produce a multi-regression equation that can be used to predict the optimum WOB and RPM for further drilling in equivalent rock formations.
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DOI: https://doi.org/10.31315/jpgt.v3i1.6888
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