Explore chapters and articles related to this topic
Origin and Composition
Published in Mark J. Kaiser, Arno de Klerk, James H. Gary, Glenn E. Hwerk, Petroleum Refining, 2019
Mark J. Kaiser, Arno de Klerk, James H. Gary, Glenn E. Hwerk
The three main types of hydrocarbons found in crude oil are paraffins, naphthenes, and aromatics. Paraffins occur in both branched-chain (iso) and straight-chain (normal) structures. Naphthenes have five or six carbon atoms in a ring structure and are found in single (monocyclic) and multiple (polycyclic) combinations. Aromatics are also ring structures but have less hydrogen per carbon atom than paraffins or naphthenes due to double bonding. Accumulations of condensed polynuclear aromatic layers linked by saturated chains are known as asphaltenes. Asphaltenes are very large molecules with molecular weights ranging from 1000 to 100,000, and all crude oils contain some amount of asphaltenes.
Physical Separation
Published in Cesar Ovalles, Subsurface Upgrading of Heavy Crude Oils and Bitumen, 2019
Benson and Ovalles patented a process for producing upgraded heavy oil during SAGD operations by flowing a liquid phase additive into a near wellbore region of the steam chamber to control asphaltenes mobility [Benson and Ovalles 2017]. The additive was formulated to mobilize the asphaltenes within this region preventing blockage and formation damage. In this order of ideas, Yakubov et al. performed several experiments using C3, C4, C5, and C6 hydrocarbons with bitumen to evaluate the efficiency of several asphaltene inhibitors during solvent injection processes. The authors reported that the addition of asphaltene inhibitors is a way to prevent asphaltene precipitation and deposition in a reservoir [Yakubov et al. 2014].
Basics of Crude Oil Refining
Published in Soni O. Oyekan, Catalytic Naphtha Reforming Process, 2018
Asphaltenes are high-molecular-weight hydrocarbons that are found in crude oil and present mostly in the heavy fractions of crude oils. The compounds consist of carbon, hydrogen, nitrogen, oxygen, and sulfur, as well as trace amounts of nickel and vanadium. They usually do not have a chemical molecular formula as is the case for alkanes, alkenes, alkynes, and naphthenes. They are hydrogen-deficient compounds, as their carbon-to-hydrogen stoichiometric ratio is about 1:1.2 for some asphaltenes, and that is also dependent on the source of the asphaltenes. It should be noted that the 1:1.2 ratio is close to the 1:1 that is typically used to represent the high hydrogen deficiency of catalytic coke. Asphaltenes are complex compounds with a number of aromatic rings, pyridine, thiophenes, and alkyl chains embedded in their structure, as shown in Figure 2.9.(9,10)
Asphaltenes of crude oils and bitumens: The similarities and differences
Published in Petroleum Science and Technology, 2022
Yulia Ganeeva, Ekaterina Barskaya, Ekaterina Okhotnikova, Tatiana Yusupova, Vladimir Morozov, Gennady Romanov
Special attention is paid to the study of the asphaltenes, since they are crucial to all aspects of oil utilization including reservoir characterization, production, and transportation and refining (Speight 2004). Interest in the study of oil asphaltenes is also enhanced by the “mystery” of their origin. There are several hypotheses about the origin of asphaltenes in oils. The most common, based on the great similarity of the composition and structure of oil asphaltenes with bitumen asphaltenes and kerogen, is that oil asphaltenes are small soluble fragments of kerogen (Tissot and Welte 1978). At the same time, there is a perception that asphaltenes are an intermediate step in the conversion of organic matter to kerogen (Borisova 2017, 2019). Nevertheless, Borisova admits that some of the asphaltenes can be a product of the destruction of kerogen.
Effect of pressure and CO2 content on the asphaltene precipitation in the light crude oil
Published in Petroleum Science and Technology, 2020
Jianguang Wei, Jiangtao Li, Xiaofeng Zhou, Xin Zhang
Because asphaltene is a complex organic matter with high carbon atoms, the study of its chemical structure is difficult. Although a large number of researches have been carried out by using a variety of detection methods since the 20th century, the molecular structure of asphaltene is still difficult to determine and most of the results are speculative. Now the widely accepted physical model of asphaltene is a type of stable micellar aggregate formed by adsorption of colloid. Long-term studies have shown that asphaltene has the following characteristics (Dunn, Gutama, and Noid 2019; Aminzadeh, Nikazar, and Dabir 2019): (1) positive charge; (2) asphaltene surrounded by colloid; (3) an electric current generated during the flow of asphaltene to cause the asphaltene flocculation; (4) asphaltene micelle dispersed in crude oil, which can be described by the average molecular weight; (5) a tendency to aggregate with each other.
Applying of LSSVM approach as a novel tool for accurate prediction of asphaltene inhibition efficiency
Published in Petroleum Science and Technology, 2018
Mostafa Sedaghatzadeh, Pouya Bakhtiari Manesh, Khalil Shahbazi
Asphaltene is known as solid and high molecular weight fraction of crude oil which is soluble in aromatics and insoluble in paraffins. The asphaltene precipitation is known as critical problem in petroleum industry such as blockage of reservoir during gas injection or pipeline blockage so inhibition of asphaltene precipitation and effect of different parameters on precipitation become essential issues for research (Madhi et al. 2017; Bemani, Ashoori, and Bahrami 2017; Speight, Long, andFigure 1, Figure 2, Figure 3Trowbridge 1984; Ghahfarokhi et al. 2017; Kor and Kharrat 2016; Lashkari, Kharrat, and Khaz'ali 2017). Zarei used MLP-ANN algorithm to estimate amount of asphaltene precipitated in terms of dilution ratio, carbon number of precipitant and temperature (Zarei and Baghban 2017). Baghban applied LSSVM approach to estimate asphaltene precipitation a function of operational conditions (Baghban and Khoshkharam 2016). Taherpour et al. estimate asphaltene precipitation based on Fuzzy c-means algorithm (Taherpour et al. 2017). Zanbouri and coworker used Grid partitioning based Fuzzy inference system for asphaltene precipitation estimation (Zanbouri et al. 2018).