Prediction Model between Emulsified Water Fractions and Physicochemical Properties of Crude Oil Based on the Exergy Loss Rate

Abstract Due to the high pour point of the oil products transported in the long-distance high wax crude oil pipeline, in order to ensure the operation safety, it is necessary to adopt heating transmission technology, so as to ensure that the oil temperature along the pipeline is 3–5 °C higher than the pour point, that is to say, the oil temperature is the most important operation parameter of the long-distance hot oil pipeline, and the accurate prediction and control of the oil temperature is the premise of the pipeline safety optimization. Aiming at the problems of large prediction error and poor applicability of the previous theoretical formula, this paper studies the establishment of oil temperature prediction model by using data mining algorithms such as Back Propagation (BP) neural network, and improves the prediction efficiency and accuracy of the model by using Genetic Algorithm (GA) optimization. The correlation coefficient formula is used to calculate the influence coefficient of oil temperature, ground temperature, pipeline transportation and other parameters on the inlet oil temperature of the downstream station, so as to obtain the input parameters of the model. The actual production data training model is downloaded through SCADA system, and the prediction accuracy of the control model is ±0.5 °C. Compared with BP model and other theoretical formulas, the accuracy and efficiency of GA-BP oil temperature prediction model are greatly improved, and the adaptability is better. The GA-BP oil temperature prediction model trained according to the actual production data can be effectively applied to the future pipeline big data platform, which lays a theoretical foundation for the intelligent control of the pipeline.

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Physicochemical Properties and Fatty Acid Profiles of Crude Oil Extracts from Three Vegetable Seeds

Pakistan Journal of Nutrition ◽

10.3923/pjn.2013.647.650 ◽

2013 ◽

Vol 12 (7) ◽

pp. 647-650 ◽

Cited By ~ 6

Author(s):

Amos- Tautua ◽

Bamidele Martin W. ◽

Onigbinde, Adebayo O.

Keyword(s):

Fatty Acid ◽

Physicochemical Properties ◽

Crude Oil ◽

Fatty Acid Profiles

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Changes in soil microbial respiration and physicochemical properties following bonny light crude oil contamination of sandy loam soil

Ife Journal of Science ◽

10.4314/ijs.v22i1.15 ◽

2020 ◽

Vol 22 (1) ◽

pp. 153-163

Author(s):

C.N. Eze ◽

P.I. Orjiakor ◽

U.J. Ebeifenadi

Keyword(s):

Physicochemical Properties ◽

Crude Oil ◽

Microbial Respiration ◽

Sandy Loam ◽

Sandy Loam Soil ◽

Oil Contamination ◽

Light Crude Oil ◽

Soil Microbial ◽

Crude Oil Contamination ◽

Loam Soil

This study was undertaken to investigate the effects of Bonny light crude oil contamination of sandy loam soil on aspects of microbial metabolism and physicochemical properties of the soil. Bonny light crude oil (specific gravity = 0.81) was used at eight different levels (0.5%, 1.0%, 2.0%, 2.5%, 5.0%, 10.0%, 15.0% or 20.0% v/w of soil) for the controlled pollution of pristine soil samples, each weighing 1 kg. The experiment lasted for eightweeks. Results of the effects of crude oil on the physicochemical properties of the soil showed that high levels of the oil significantly (p< 0.05) increased soil organic matter but had no significant effect on the pH and moisture content. With the exception of organic carbon, the levels of bioavailable nitrogen, sodium, potassium, calcium, magnesium, sulphur and phosphorus in the test samples with higher levels of crude oil (5.0%, 10.0%, 15.0% and 20.0%) were significantly reduced when compared to their levels in the controls. Similarly, higher levels of the oil significantly (p<0.05) reduced soil microbial phospholipid synthesis and CO emission. 2 Correlation analysis using the Pearson's correlation model showed a positive correlation between soil CO and 2 phospholipid (r = 0.74). Keywords: Contamination, Crude oil, Microbial respiration, Physicochemical properties.

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