Application of Continuous Polydisperse Molecular Thermodynamics for Modeling Asphaltene Precipitation in Crude Oil Systems

Manshad, Abbas Khaksar; Edalat, M.

doi:10.1021/ef7006529

Cited by 17 publications

(14 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Asphaltene deposition in the reservoir can be a bothersome phenomenon or an opportunity to leave behind obnoxious components that can lead to multiple problems in the refinery and decrease the value of crude oils. It is well-known that changes in the temperature, pressure, and composition can induce asphaltene precipitation . As the asphaltene deposit builds up, permeability decreases, causing a reduction in oil production rates .…”

Section: Introductionmentioning

confidence: 99%

Ultrahigh-Resolution Magnetic Resonance Mass Spectrometry Characterization of Crude Oil Fractions Obtained Using n-Pentane

2020

View full text Add to dashboard Cite

In this work, crude oil fractions obtained using n-pentane were analyzed using atmospheric pressure photoionization coupled to ultrahigh-resolution magnetic resonance mass spectrometry. The crude oil was supported on Ottawa sand and transferred to a glass column. n-Pentane was added to the column, and the fractions drained at the bottom were collected. Results indicate that the fractions obtained are highly deficient in hydrogen and become more aromatic as the amount of n-pentane going through the column increases. The analysis of the fraction retained in the sand after the experiment indicates that this fraction is enriched in oxygen species and more aromatic than pentane-extracted asphaltenes from the same crude oil. It was also found that the material dissolved in n-pentane after the initial washing is more aromatic than the material remaining in the sand, suggesting that the sand plays a significant role in the strong adsorption of molecules containing more polar moieties but that are less aromatic. Also, molecules left in the sand are smaller (lower C carbons) than those eluted in the fractions; therefore, small molecules are retained preferentially. This study provides evidence that the presence of sand and likely of other inorganic substrates leads to asphaltenes that occupy a different compositional space from those obtained using standard procedures in the laboratory.

show abstract

Section: Introductionmentioning

confidence: 99%

Ultrahigh-Resolution Magnetic Resonance Mass Spectrometry Characterization of Crude Oil Fractions Obtained Using n-Pentane

2020

View full text Add to dashboard Cite

show abstract

“…They expanded the Flory-Huggins theory by applying a mixture of polymers of different lengths [40]. Later, based on this theory, other authors proposed their own thermodynamic models [41,42].…”

Section: Scott Makat Theorymentioning

confidence: 99%

Analysis of the Modern State of Researches on Deposition of Asphalt-Resin Substances, Paraffin and Modeling Methods Review Part I: Precipitation of Asphaltenes

Manafov¹,

Келбалиев²

2020

AChJ

View full text Add to dashboard Cite

Asphaltenes are the heaviest crude oil fraction and tend to self-associate and precipitate. The precipitation and deposition of asphaltenes during the production, refining, transportation of oil is the main for the oil industry, the precipitation of asphaltenes and their subsequent deposition can cause problems at all stages of production. Asphaltenes have different structures and molecular composition, they are a mixture of poorly defined components, they are self-associated even at very low concentrations, what makes them one of the most difficult components of crude oil. Since the deposition mechanism of paraffin wax differs from the deposition mechanism of asphaltenes, mathematical modeling of crystallization of paraffin will be considered separately in another work. Creating accurate asphaltene models that can predict the behavior of asphaltenes in various scenarios should help reduce asphaltene problems. This review is specifically devoted to advances in mathematical modeling of asphaltenes. Several different models have been proposed in the literature for predicting the initial conditions and precipitation of asphaltenes. Existing modeling approaches can be broadly classified into colloidal and thermodynamic models. It should be noted intelligent models, such as a vector machine, an artificial neural network, in recent years are increasingly used for modeling various parameters and properties in the oil and chemical industries. However, these models are a black box and cannot provide a clear link between the output and input parameters of the model. In the past few years, models based on the Cubic Plus EoS Association (CPA EoS) and Statistical associating fluid theory (SAFT) have been recognized as promising one for studying asphaltene sediments. However, in the literature, there exist different opinions. Therefore, a systematic study is important for modeling the deposition of asphaltenes. Over the past decades, several different models have been proposed to predict the onset of asphaltenes and the amount of asphaltenes deposited. This paper examines various models that have been proposed to predict asphaltenes deposition under changing thermobaric conditions. A brief summary of various research approaches is presented.The main focus is on the description of the basic assumptions underlying various models, as well as on the ability of the model to correspond to experimental data. The presented models are compared and current modeling trends for forecasting precipitation are shown. This work will help improve understanding of asphaltenes and provide recommendations for the proper study and modeling of asphaltenes in future research.

show abstract

“…In particular, a number of authors [104][105][106][115][116][117][118][119] have developed thermodynamic models based on the Scott-Magat polymer theory [120,121], where the heterogeneous structure and polydispersity in the asphaltene molecular weight is taken into account in the model. Although there is recent practical evidence from sulphur analysis and speciation of reservoir crude oils that there are circumstances where polydispersity can be ignored at the molecular [73] and nanoaggregate/cluster [72] levels, polydisperse models have been developed to account for size and molecular weight distributions of aggregates due to asphaltene self-aggregation [115,119,122,123].…”

Section: Lattice Fluid Theoriesmentioning

confidence: 99%

“…Although gamma distribution functions have been a common choice [105,106,115,124], Schultz-Zimm distribution functions [104] and fractal distribution functions [119,123] have also been suggested. A comparison between these different distribution functions is made in the study of Manshad and Edalat [117], where the use of a fractal distribution function leads to best agreement with experimental data. A typical element in these studies is to model asphaltenes as the only self-associating fraction.…”

Section: Lattice Fluid Theoriesmentioning

confidence: 99%

Thermodynamic modelling of asphaltene precipitation and related phenomena

Forte

Taylor

2015

Advances in Colloid and Interface Science

View full text Add to dashboard Cite

Application of Continuous Polydisperse Molecular Thermodynamics for Modeling Asphaltene Precipitation in Crude Oil Systems

Cited by 17 publications

References 35 publications

Ultrahigh-Resolution Magnetic Resonance Mass Spectrometry Characterization of Crude Oil Fractions Obtained Using n-Pentane

Ultrahigh-Resolution Magnetic Resonance Mass Spectrometry Characterization of Crude Oil Fractions Obtained Using n-Pentane

Analysis of the Modern State of Researches on Deposition of Asphalt-Resin Substances, Paraffin and Modeling Methods Review Part I: Precipitation of Asphaltenes

Thermodynamic modelling of asphaltene precipitation and related phenomena

Contact Info

Product

Resources

About