Properties of Emulsions Formed <i>In Situ</i> In a Heavy‐Oil Reservoir during Water Flooding: Effects of Salinity and pH

Pu, Wanfen; Shen, Chao; Pang, Shishi; Tang, Xingjian; Tian, Qingtao; Song, Yufei

doi:10.1002/jsde.12188

Cited by 12 publications

(11 citation statements)

References 15 publications

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“…One other compound type that is expected according to the FT-IR results is nitrogen-containing aromatic bases. ESI-FT-ICR-MS studies on crude oil suggest that the dominant aromatic nitrogen bases contain typically only one nitrogen atom. ,, According to the nitrogen rule, organic compounds containing exclusively hydrogen, carbon, nitrogen, oxygen, silicon, phosphorus, sulfur, and halogens have an odd nominal mass that indicates that an odd number of nitrogen atoms is present. According to the ESI-FT-ICR-MS studies, three nitrogen atoms in the bases in question are insignificant, so it is realistic to expect to find aromatic bases containing only one nitrogen atom.…”

Section: Resultsmentioning

confidence: 99%

“…However, another interesting group of emulsifiers or stabilizers of emulsions are the naturally occurring ones in crude oil. These include asphaltenes, resins, organic acids, and organic bases. − These are typically high-molecular-weight polar molecules that exhibit surfactant-like behavior and will form stabilizing films around the water droplets. Particles are another group of emulsifiers acting as mechanical stabilizers, which can be added or be naturally present.…”

Section: Introductionmentioning

confidence: 99%

“…The highly complex nature of crude oil makes it challenging to speculate on what compounds or compound types are responsible for the emulsion behavior, so the obvious approach has been to take the crude oil apart (i.e., isolate the compound classes) via extraction or chromatographic methods and then analyze the isolated parts using chemical analytical methods. This has been done by many workers for various purposes. − ,− Two isolation methods have typically been used for this: (i) liquid/liquid extraction with aqueous solutions at various pH values and (ii) solid/liquid extraction via some kind of liquid chromatography (LC). The isolated material has typically been analyzed using chemical analysis methods such as Fourier transform infrared (FT-IR) spectroscopy, ,,, nuclear magnetic resonance (NMR), , and various types of mass spectrometry (MS). ,,,− …”

Section: Introductionmentioning

confidence: 99%

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Isolation and Characterization of Surface-Active Components in Crude Oil—Toward Their Application as Demulsifiers

et al. 2020

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Surface-active components in the form of intrinsic emulsifiers have been studied, and their possible role as demulsifiers has been assessed. Polar components were extracted from crude oil via three isolation methods involving liquid/liquid extraction at pH 14, liquid/liquid extraction at pH 1, and column chromatography. All three isolates were found to improve separation within hours independent of their concentration. The material isolated from acidic extraction was found to be the most efficient. An expanded chemical analysis of the isolates involving Fourier transform infrared spectroscopy, UV−vis spectroscopy, liquid chromatography–mass spectrometry, and liquid chromatography–tandem mass spectrometry analysis was employed to identify the polar compounds in the three isolates. The most polar components were found to be naphthenic acids and saturated and nonsaturated noncyclic carboxylic acids. The least polar compounds were found to be nitrogen-containing aromatic bases such as pyridines, quinolines, pyrroles, indoles, indolines, and carbazoles. A mixture of compounds with polarities between the acids and bases were identified as phenols, pyrans, benzopyrans, naphthopyrans, benzonaphtholpyrans, dibenzopyrans, dinaphthopyrans, and compounds containing both nitrogen and oxygen atoms. The fact that so many compounds are found in each extract makes it difficult to speculate on exactly what types of molecules are significantly contributing positively to the emulsion breaking and separation process. The suggested polar molecules from this work have been sufficiently precise for a follow-up study to be realistic and promising, where the dominating polar molecules in each category are synthesized and subjected to separation experiments. Finally, interesting observations were made that relate to oil maturity and origin.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Isolation and Characterization of Surface-Active Components in Crude Oil—Toward Their Application as Demulsifiers

et al. 2020

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“…Figure 21 shows that increasing the salinity concentration increases the efficiency of oil removal. The reason is that there is lower stability of the emulsion at higher levels of salinity; furthermore, the IFT value also increased [41]. The salts screen charge on the surface of the oil droplets and reduce the stability of the emulsions, which reduces the time needed to separate the oil and water [42].…”

Section: Comparison Of Rsm and Anfismentioning

confidence: 99%

Predicting the Efficiency of the Oil Removal From Surfactant and Polymer Produced Water by Using Liquid–Liquid Hydrocyclone: Comparison of Prediction Abilities Between Response Surface Methodology and Adaptive Neuro-Fuzzy Inference System

Ishak

Ayoub

2019

IEEE Access

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The present study developed, evaluated and compared the prediction and simulating efficiency of both, the response surface methodology (RSM) and adaptive neuro-fuzzy inference system (ANFIS) approaches for oil removal using a liquid-liquid hydrocyclone (LLHC) from surfactant and polymer (SP) produced water. Six parameters were involved in the process: the surfactant concentration, polymer concentration, salinity, initial oil concentration, feed flowrate and split ratio. For RSM, D-optimal design was used, while the ANFIS model was developed in term of this process with the Gaussian membership function. All models were compared statistically based on the training and testing data set by the coefficient of determination (R 2 ), root-mean-square error (RMSE), average absolute percentage error (AAPE), standard deviation (STD), minimum error, and maximum error. The R 2 for RSM and the ANFIS model for the testing set were of 0.972 and 0.999, respectively. Both models made good predictions. Trend analysis has been done to confirm the applicability of the models. From the results, it shows that the ANFIS model was more precise compared to the RSM model, which proves that the ANFIS is a powerful tool for modelling and optimizing the efficiency of the oil removal from the LLHC in the presence of SP.

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“…The figure shows that increasing the salinity from 14,000 to 28,000 ppm has increased the efficiency of oil removal. The reason is because of the decrease in stability of the emulsion based on the increase in IFT values and salinity (Pu et al, 2018). The salts screen charge on the surface of oil droplets and reduce the stability of the emulsions.…”

Section: 6mentioning

confidence: 99%

Performance of liquid–liquid hydrocyclone (LLHC) for treating produced water from surfactant flooding produced water

Ishak

Ayoub

2019

WJE

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Purpose The purpose of this study is to investigate the performance of the fabricated liquid–liquid hydrocyclone (LLHC) with dimensions similar to those of one of the Malaysian oilfields with the presence of an anionic surfactant, S672. The effect of salinity and initial oil concentration were also investigated following the actual range concentration. Design/methodology/approach The current control system’s pressure drop ratio (PDR) does not necessarily lead to an efficient LLHC. Therefore, rather than using the PDR, the efficiency of the LLHC was analyzed by comparing the concentration of oil in the effluents with the concentration of oil at the feed of the LLHC. An LLHC test rig was developed at Centre of Enhanced Oil Recovery, Universiti Teknologi PETRONAS. Emulsions were prepared by mixing the brines, S672 and oil by using Ultra Turrax ultrasonic mixer. The emulsion was pumped into the LLHC at different feed flowrate and split ratio. The brines concentration, initial oil concentration and S672 concentration were also varied in this study. Samples were taken at the underflow of the LLHC and the oil in water concentration analysis was done for the samples using TD-500D equipment. Findings It was found that the efficiency of oil removal decreased with an increase in S672 concentration but increased with the increase in salinity and initial oil concentration. Originality/value The optimum feed flowrate for the LLHC of 45 mm diameter and length of 1,125 mm with the presence of S672 surfactant was found to be 40 L/min with a split ratio of 14%. This study can be used as a guidance for future optimization of the LLHC in the presence of the surfactant.

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Properties of Emulsions Formed In Situ In a Heavy‐Oil Reservoir during Water Flooding: Effects of Salinity and pH

Cited by 12 publications

References 15 publications

Isolation and Characterization of Surface-Active Components in Crude Oil—Toward Their Application as Demulsifiers

Isolation and Characterization of Surface-Active Components in Crude Oil—Toward Their Application as Demulsifiers

Predicting the Efficiency of the Oil Removal From Surfactant and Polymer Produced Water by Using Liquid–Liquid Hydrocyclone: Comparison of Prediction Abilities Between Response Surface Methodology and Adaptive Neuro-Fuzzy Inference System

Performance of liquid–liquid hydrocyclone (LLHC) for treating produced water from surfactant flooding produced water

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