The Experts below are selected from a list of 109719 Experts worldwide ranked by ideXlab platform
Mordechai Shacham - One of the best experts on this subject based on the ideXlab platform.
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statistical analysis of linear and nonlinear Correlation of the arrhenius equation constants
Chemical Engineering and Processing, 1997Co-Authors: Neima Brauner, Mordechai ShachamAbstract:Abstract Engineers must often use Correlations that were developed before statistical analysis and verification of the Correlation became a routine procedure. In this paper, we use modern statistical techniques to compare the traditional linear regression technique with the modern nonlinear regression as applied to the Arrhenius equation. The objective of the comparison is to determine whether there are basic flaws with the technique used in the past and whether these flaws may render the constants Published in the literature untrustworthy. It is concluded that linear regression, when applied to the Arrhenius expression, is in principle not inferior to nonlinear regression and if the relative error in the data is distributed normally, it can even be superior. Nevertheless, if insufficient data were used for calculation of the constants and/or the experimental data were interpolated or smoothed, the accuracy of the Published Correlation is unpredictable.
E. Shirif - One of the best experts on this subject based on the ideXlab platform.
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The Prediction of Bubble-point Pressure and Bubble-point Oil Formation Volume Factor in the Absence of PVT Analysis
Petroleum Science and Technology, 2014Co-Authors: S. Elmabrouk, Abdulrazzag Y. Zekri, E. ShirifAbstract:Up to now, there has not been one specific Correlation Published to directly estimate the bubble-point pressure in the absence of pressure-volume-temperature (PVT) analysis. Presently, there is just one Published Correlation available to estimate the bubble-point oil formation volume factor (FVF) directly in the absence of PVT analysis. Multiple regression analysis technique is applied to develop two novel Correlations to estimate the bubble-point pressure and the bubble-point oil FVF. The developed Correlations can be applied in a straightforward manner by using direct field measurement data. Separator gas oil ratio, separator pressure, stock-tank oil gravity, and reservoir temperature are the only key parameters required to predict bubble-point pressure and bubble-point oil FVF.
Mohd Haziq Farhan - One of the best experts on this subject based on the ideXlab platform.
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Prediction of Bubble-point Pressure (Pb) and Formation Volume Factor (Bo) Using Group Method of Data Handling (GMDH) approach and the effect of reducing correlating parameters; a comparative study
2013Co-Authors: Mohd Zaki, Mohd Haziq FarhanAbstract:year Petroleum Engineering undergraduate students at Universiti Teknologi PETRONAS (UTP) are required to complete a Final Year Project (FYP), as part of the graduating requirement. In this course, students are given opportunity to use their knowledge as well as problem-solving tools and methods that they have acquired throughout their study to independently carry out research or design work. The project supervision and evaluations are mainly done by lecturers although practicing engineers from the industries are invited to participate. The author’s FYP title is “The Prediction of Bubble Point Pressure and Oil Formation Volume Factor using Group Method of Data Handling (GMDH) and the effect of reducing correlating parameters; a comparative study”. A precise description of the reservoir fluid properties, hold importance essence in finding solution and solving petroleum reservoir engineering related problems. It is important for engineers to get ahold of the physical reservoir fluid properties, because they help in designing the best approach and strategies for the development of any oilfields. A broad literature review was done to assist the author to apprehend and establish the parameter, boundary, limitations of the existing Correlation as well as the method he’s going to apply for his study. This paper will be evaluating Published Correlations aimed to predict bubble point pressure and oil formation volume factor, the author’s propose Correlation which is his ambition to improve the current Correlation’s accuracy used by the industry in predicting the reservoir’s bubble point pressure and oil formation volume factor through the method known as GMDH. Statistical analysis will be conducted to evaluate the model’s performance. This paper aims to generate two Correlation models; bubble point pressure Pb, and Oil formation volume factor Bo, with high accuracy and less number of parameters. On the other hand, this paper will also discuss the effect of reducing parameters used in previously Published Correlation that took into account while developing them.
K Salam - One of the best experts on this subject based on the ideXlab platform.
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fuzzy sequential forward search for oil formation volume factor predictive tool factor for niger delta crude oil
British Journal of Applied Science and Technology, 2013Co-Authors: K SalamAbstract:Accurateprediction of fl uid properties is essentials for all reservoir engineering calculations such as estimation of reserves, well testing analysis and in numerical reservoir simulation. Oil formation volume factor is one of the properties that can either be gotten from empiric al or experimental method. This work focuses on the use of fuzzy sequential forward techniques to develop a oil formation volume factor model using 1,316 data obtained from 45 different oil fields in the Niger Delta, Nigeria. The data set was randomly divi ded into two parts with 750 used for training and 566 for testing. The model developed has the lowest Root Mean Square Error (RMSE) of 0.0784 when compared with Published Correlation used for prediction. The accuracy of the developed model was tested with cross plotand statistical analysis. The model developed outperformed the existing Correlations when subjected to further statistical analysis . Research Article
Neima Brauner - One of the best experts on this subject based on the ideXlab platform.
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statistical analysis of linear and nonlinear Correlation of the arrhenius equation constants
Chemical Engineering and Processing, 1997Co-Authors: Neima Brauner, Mordechai ShachamAbstract:Abstract Engineers must often use Correlations that were developed before statistical analysis and verification of the Correlation became a routine procedure. In this paper, we use modern statistical techniques to compare the traditional linear regression technique with the modern nonlinear regression as applied to the Arrhenius equation. The objective of the comparison is to determine whether there are basic flaws with the technique used in the past and whether these flaws may render the constants Published in the literature untrustworthy. It is concluded that linear regression, when applied to the Arrhenius expression, is in principle not inferior to nonlinear regression and if the relative error in the data is distributed normally, it can even be superior. Nevertheless, if insufficient data were used for calculation of the constants and/or the experimental data were interpolated or smoothed, the accuracy of the Published Correlation is unpredictable.
