ArticleHeliyon2024
Optimizing oil salt analysis in southern Iran: A comprehensive statistical model for ASTM D3230 electrochemical cell device utilizing advanced analytical approaches.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The ASTM D3230 electrochemical cell plays a pivotal role in measuring oil salt content in the southern Iranian oil fields, employing a solvent blend of 63 % butanol and 37 % methanol. However, the growing application of this method raises concerns about the substantial daily requirement of 40 L of solvents as well as the device's significant power consumption within a laboratory setting. This study analyzes a year-long dataset comprising 103 filtered samples and leverages data mining techniques to investigate interactions among descriptive statistical parameters within crude oil compositions, thereby enhancing the efficiency, operational stability, and performance monitoring of the D3230 device. Key statistical attributes, including the structure and population characteristics of the data, are thoroughly analyzed. Various statistical tests, including ANOVA, are employed to develop significant regression models that offer an evolutionary and augmented reality perspective on the statistical and experimental data from the D3230 electrochemical cell, Petrotest device, and the IP 77/79 method. This approach facilitates a better understanding of the optimal performance of salt measurement devices and the identification of comprehensive optimization functions for salt measurement methodologies. The findings indicate a remarkable accuracy in the structure and properties of the statistical data population, illustrated by a correlation coefficient of R
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