The physicochemical characteristics of Bonga crude oil.
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Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
\n\nThis achievement solidifies IntechOpen’s place as a pioneer in Open Access publishing and the home to some of the most relevant scientific research available through Open Access.
\n\nWe are so proud to have worked with so many bright minds throughout the years who have helped us spread knowledge through the power of Open Access and we look forward to continuing to support some of the greatest thinkers of our day.
\n\nThank you for making IntechOpen your place of learning, sharing, and discovery, and here’s to 150 million more!
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Efforts of people in related fields are contained in this book. 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Application of Design for Manufacturing and Assembly: Development of a Multifeedstock Biodiesel Processor",doi:null,correctionPDFUrl:"https://cdn.intechopen.com/pdfs/68990.pdf",downloadPdfUrl:"/chapter/pdf-download/68990",previewPdfUrl:"/chapter/pdf-preview/68990",totalDownloads:null,totalCrossrefCites:null,bibtexUrl:"/chapter/bibtex/68990",risUrl:"/chapter/ris/68990",chapter:{id:"63204",slug:"application-of-design-for-manufacturing-and-assembly-development-of-a-multifeedstock-biodiesel-proce",signatures:"Ilesanmi Afolabi Daniyan and Khumbulani Mpofu",dateSubmitted:"March 15th 2018",dateReviewed:"July 9th 2018",datePrePublished:"November 5th 2018",datePublished:"January 3rd 2019",book:{id:"7460",title:"Applications of Design for Manufacturing and Assembly",subtitle:null,fullTitle:"Applications of Design for Manufacturing and Assembly",slug:"applications-of-design-for-manufacturing-and-assembly",publishedDate:"January 3rd 2019",bookSignature:"Ancuţa Păcurar",coverURL:"https://cdn.intechopen.com/books/images_new/7460.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"184794",title:"Dr.",name:"Ancuta Carmen",middleName:null,surname:"Păcurar",slug:"ancuta-carmen-pacurar",fullName:"Ancuta Carmen Păcurar"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"11921",title:"Prof.",name:"Khumbulani",middleName:null,surname:"Mpofu",fullName:"Khumbulani Mpofu",slug:"khumbulani-mpofu",email:"mpofuk@tut.ac.za",position:null,institution:{name:"Tshwane University of Technology",institutionURL:null,country:{name:"South Africa"}}},{id:"260269",title:"Dr.",name:"Ilesanmi Afolabi",middleName:null,surname:"Daniyan",fullName:"Ilesanmi Afolabi Daniyan",slug:"ilesanmi-afolabi-daniyan",email:"afolabiilesanmi@yahoo.com",position:null,institution:null}]}},chapter:{id:"63204",slug:"application-of-design-for-manufacturing-and-assembly-development-of-a-multifeedstock-biodiesel-proce",signatures:"Ilesanmi Afolabi Daniyan and Khumbulani Mpofu",dateSubmitted:"March 15th 2018",dateReviewed:"July 9th 2018",datePrePublished:"November 5th 2018",datePublished:"January 3rd 2019",book:{id:"7460",title:"Applications of Design for Manufacturing and Assembly",subtitle:null,fullTitle:"Applications of Design for Manufacturing and Assembly",slug:"applications-of-design-for-manufacturing-and-assembly",publishedDate:"January 3rd 2019",bookSignature:"Ancuţa Păcurar",coverURL:"https://cdn.intechopen.com/books/images_new/7460.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"184794",title:"Dr.",name:"Ancuta Carmen",middleName:null,surname:"Păcurar",slug:"ancuta-carmen-pacurar",fullName:"Ancuta Carmen Păcurar"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"11921",title:"Prof.",name:"Khumbulani",middleName:null,surname:"Mpofu",fullName:"Khumbulani Mpofu",slug:"khumbulani-mpofu",email:"mpofuk@tut.ac.za",position:null,institution:{name:"Tshwane University of Technology",institutionURL:null,country:{name:"South Africa"}}},{id:"260269",title:"Dr.",name:"Ilesanmi Afolabi",middleName:null,surname:"Daniyan",fullName:"Ilesanmi Afolabi Daniyan",slug:"ilesanmi-afolabi-daniyan",email:"afolabiilesanmi@yahoo.com",position:null,institution:null}]},book:{id:"7460",title:"Applications of Design for Manufacturing and Assembly",subtitle:null,fullTitle:"Applications of Design for Manufacturing and Assembly",slug:"applications-of-design-for-manufacturing-and-assembly",publishedDate:"January 3rd 2019",bookSignature:"Ancuţa Păcurar",coverURL:"https://cdn.intechopen.com/books/images_new/7460.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"184794",title:"Dr.",name:"Ancuta Carmen",middleName:null,surname:"Păcurar",slug:"ancuta-carmen-pacurar",fullName:"Ancuta Carmen Păcurar"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}}},ofsBook:{item:{type:"book",id:"10366",leadTitle:null,title:"Acute-Phase Protein",subtitle:null,reviewType:"peer-reviewed",abstract:"
\r\n\tAcute-phase proteins (APP) have been used as biomarkers of diseases for decades in human medicine, but have been relatively under-utilized in veterinary medicine. Over recent, years, significant progress has been made in studies on acute phase response in farm animal medicine and small animals, including the detection, measurement and application APP as biomarkers of diseases. APP is blood and milk proteins primarily synthesized by hepatocytes and mammary gland tissue cells as a part of the acute-phase response. The acute phase response is a complex systemic early-defense system activated by impaired homeostasis, trauma, tissue injury, infection, inflammation, stress or neoplasia. Acute-phase proteins play an important role in the monitoring of the health status of live animals.
\r\n\r\n\tOn the other hand serves as a non-specific diagnostic marker of some health disorders, which occur around parturition of all animals. Between APP exist some specificity bind to organs (e.g. milk amyloid A specific type of sérum amyloid A, which is a form in mammary gland a serves as an indicator of the early state of inflammation on the level of this organ). To exist some differences in the dominant importance of different APP between the animals (Cattle: haptoglobin- Hp, serum amyloid A - SAA, alpha1-acid glycoprotein- AGP and specific milk amyloid A - M-SAA3; Horse: serum amyloid A, haptoglobin; Pig: C-reactive protein - CRP, pig- major acute-phase protein - pig-MAP, sérum amyloid A, haptoglobin; Dog: C-reactive protein, serum amyloid A, haptoglobin, alpha1-acid glycoprotein; Cat: serum amyloid A, alpha1- acid glycoprotein, haptoglobin.
",isbn:null,printIsbn:"979-953-307-X-X",pdfIsbn:null,doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"736936e72af137d618b0b16b2087bd50",bookSignature:"Prof. Gabriel Kovac",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10366.jpg",keywords:"History, APP, Animals, Animal Medicine, Transition Period, Metainformation, Mammary Gland, Marker, Sheep and Goats, Piglets, Horses, Sows",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"June 15th 2020",dateEndSecondStepPublish:"July 6th 2020",dateEndThirdStepPublish:"September 4th 2020",dateEndFourthStepPublish:"November 23rd 2020",dateEndFifthStepPublish:"January 22nd 2021",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"2 years",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:'Till now, Dr. Kovac is a member of several editorial boards of scientific journals: „Biofarm", „Veterinarní medicína", „Folia Veterinaria", „Orbis Medicinae", etc.',coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"39585",title:"Prof.",name:"Gabriel",middleName:null,surname:"Kovac",slug:"gabriel-kovac",fullName:"Gabriel Kovac",profilePictureURL:"https://mts.intechopen.com/storage/users/39585/images/system/39585.jpg",biography:"Prof. Kováč was born on 8 November 1947 in Trnava in a workfolk family. Having finished the central agricultural technical school in Trnava (branch grower – breeder) in 1966 – 1972, he studied at the University of Veterinary Medicine in Košice.\nIn 1971, during academic study, he got married and brought up three children with his wife Maria – son Martin and daughters Gabriela and Adriana.With the diploma of a veterinary surgeon he succeeded to the department of Internal Diseases of Ruminants and Swine as a research assistant. In 1972 – 1973 he completed basic military service attendance at the military Veterinary Research Institute in Prague, where, inter alia, he broadened knowledge of scientific-research work, and published his first publications. After returning to the UVM in Košice, he continued with the activities he had started before the military service. Later, he worked as a pedagogic lecturer (1974). Since 1975, he started add-on post-graduate study and in 1978 he defended dissertation thesis („Serum concentrations of vitamin E in cattle and sheep in relation to age, season, pregnancy, breed, and application of its preparations'). In the framework of contemporary regulations in 1982 he was named associated professor and after 8 years of active pedagogic and science-research activities he defended his doctor dissertation thesis („Clinical picture and biochemical indices after application of VX substance in cattle, sheep, and swine'). After habilitation and inauguration hearings („Periods of low vitamin E concentrations in the blood serum of pigs, diagnosis and prevention) he was designated professor for internal diseases of animals and pharmacology by decree of the Slovak President in 1997. In 1989 – 1991, he was the head of the university department and vice-rector for scientific-research activities and foreign relations. In 1997 – 2002, he performed superintendence of the Department of Internal Diseases of Ruminants and Swine at UVM Košice. In the subsequent period 2003 – 2007, he was the chief of II. Clinical Department for Internal Diseases, and since September 2007 chief of the Department for Diseases of Ruminants at the UVM Košice. Already during study he was interested in the subject he later chose, as he worked as a demonstrator and scientific jumper on the Department of Histology and Embryology led by Prof. Hrudka and subsequently at the Department of Internal Diseases of Ruminants and Swine headed by Prof. Vrzgula. As a student, he was involved in the students' scientific and professional activities, in which he stayed as an assistant for 10 years as a scientific secretary. Later he completed several educational stays on the Veterinary faculty in Utrecht, Helsinki, and short-term educational and lecturing stays within European and worldwide scientific and professional events, particularly organized by buiatrics societies in Sophia, Budapest, Moscow, Olsztyn, Lublin, Havana, London, Aberdeen, Belfast, Cambridge, Lyon, Alford, Toulouse, Vienna, St. Paul, Bologna, Edinburgh, Sydney, Balatonfured, Punta del Este, Hannover, Lovran, Quebec, Hajduszoboszlo, Krakow, Nice, Radenci, Kodan, Lisboan, Bury, Gura Humurolui, Leipzig, Siofok, etc. Numerous foreign stays enriched his scientific-pedagogic profile and contributed to his appointment to prominent specialized and scientific commissions and scientific boards, not only at UVM in Košice, but also on Veterinary faculty VaFU Brno and Medical faculty UPJS Košice. Moreover, he was the chairman of the branch of veterinary medicine of the Slovak Academy of Agriculture Sciences, now he is its vice-president, he was the vice-president of Slovak Commission for Dispense of Scientific Ranks, member of presidency of Slovak Academy of Agriculture Sciences, Scientific College of Slovak Academy of Science for Agricultural, Forestry, and Veterinary Sciences, Slovak Association of Veterinary Surgeons and president of its Subsection of Diseases and Rearing of Cattle, contact person for World Buiatric Society and member of its board extension, co-founder and member of executive boards for organization of Middle-European Buiatrics Congresses, member of British VET Association for Cattle Diseases, member of the scientific board of advisers of the American Biographic Institute.\nProf. Kováč is a commissioner of VEGA (scientific grant agency) MS SR and SAV for Agricultural, Forestry, and Veterinary Sciences (for 5-times, last from r. 2005); vice president of Committee for Agriculture Sciences of Agency Supporting Research and Development; member of working parties of Accreditation Commission of SR related to veterinary sciences; member of Technical Board of SNAS (Slovak National Accreditation Service) for accreditation of certifications boards for risk management. Till now, he is a member of several editorial boards of scientific journals: „Biofarm', „Veterinarní medicína', „Folia Veterinaria', „Orbis Medicinae', etc. \nWithin his scientific and research activities he performed important functions as the president of the Common Special Committee for Defence of Dissertation Thesis (PhD.) in the field of study 'Internal Diseases of Animals', member of special committees for defence of dissertation thesis (PhD.) in the fields of study: 'Immunology', 'Nutrition and Dietetics', 'Toxicology', 'Pharmacology'. He is the chairman of Committee for Defence of Doctor Dissertation Thesis (DrSc.) at science branch 'Internal Diseases of Animals', member of special committees at science branches: 'Veterinary Morphology', 'Nutrition and Dietetics', 'Parasitology', 'Other Related Branches of Veterinary Sciences'.Prof. Kováč is engaged in advisory and expertise activities aimed at helping agricultural practice, he closely cooperates with various enterprises in proposing and verifying of new remedies and aids for agricultural and veterinary practice. \nHis present activities classified Prof. Kováč among head representatives of Slovak veterinary medicine, particularly in the field of internal diseases. This is proofed primarily by working out of aetiopathogenesis, diagnosis, therapy and prevention of the most important metabolic disorders in livestock and wild animals. Scientific and research activities of Prof. Kováč are presented at home, as well as abroad. Till now, he is a co-author of 22 Slovak scientific monographies, 11 foreign scientific monographies, author and co-author of three academic textbooks, 7 scripts, 91 scientific works in the Current Contents journals (88 foreign and three Slovak), 239 scientific and special papers in other journals (62 foreign and 177 Slovak), 141 scientific contributions in reviewed proceedings of foreign conferences, 371 scientific works in reviewed proceedings of Slovak conferences.\nProf. Kováč, as the principal investigator and co-investigator, participated in 23 defended final reports of state research tasks, 6 department research tasks, 2 international grant projects, and 6 grant projects within SR; 11 continuous research reports, 9 research and special works based on economic activities. He worked out 23 reviews of issued works, 42 opponent reviews of qualifying works, 3 special translations, 36 scientific-popular and informative contributions, he took part in the elaboration of subject words in four dictionaries and encyclopaedias, and other 96 published works (to prominent jubilee colleagues, information on important scientific and special events at home and abroad). At the present, he is the principal investigator of VEGA and APVV grant projects, and co-investigator of several other projects. Among the published works of Prof. Kováč, the most important is knowledge of periods of low vitamin E concentrations in the blood serum of cattle, sheep and swine in relation to stage of pregnancy, age, season, and response to various ways of administration of remedies based on vitamin E and selenium; clarifying of aetiopathogenesis, diagnosis, therapy, and prevention of nutritional muscular dystrophy in young cattle; hypovitaminoses of B-complex; interactions of natural antioxidants and poly-unsaturated fatty acids; the use of natural sorbents; knowledge of clinical picture and metabolic indices in livestock and wild animals in areas exposed to industrial and chemical contaminations. In close relation to educational stays abroad, Prof. Kováč paid also considerable attention to the clarification of aetiopathogenesis, diagnosis, therapy, and prevention of several organ entities, and methodical procedures. In the recent period, Prof. Kováč orientates his collective, particularly research activities of his PhD students, to use components of genomics, proteomics, nutrigenomics, metabolomics, for real selection of animals by health signs, which lags behind the selection of food animals based on production traits only. Prof. Kováč participated meaningly in under-graduate education within students' research and special works (21 students), diploma thesis (12 the students), young scientific-pedagogic workers for needs of UVM (5 PhD.), practice (2 PhD.), and foreign countries (2 PhD.); three associated professors, two regular professors; building up of former Department of Internal Diseases of Ruminants and Swine, later 2nd Clinical Department, and presently the Clinical Department for Ruminants at UVM Košice, as an up-to-date academic place of work within the University of veterinary medicine in Košice, as well as in European space (through acquirement of financial resources within developing projects).",institutionString:"University of Veterinary Medicine in Košice",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Veterinary Medicine in Košice",institutionURL:null,country:{name:"Slovakia"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"6",title:"Biochemistry, Genetics and Molecular Biology",slug:"biochemistry-genetics-and-molecular-biology"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"247865",firstName:"Jasna",lastName:"Bozic",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/247865/images/7225_n.jpg",email:"jasna.b@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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Oil also contains the gaseous phase as methane, ethane, and liquid phase. Gas typically dissolves in the liquid, whereas in the balance’s case remains strong. It is noticed with the experience that natural gas fields are close to oil fields [2]. In general, there are four or three oil: aromatic, paraffin, naphthenic. But there is also a mixed type [1]. The classification of crude oil is carried out for various reasons. The criteria for classifying crude oil refer more or less to its quality [3]. For a better understanding of classificatory at the quality (quality/price), the Petroleum world has adopted a benchmark called stallion as Brent Blend produced in the North Sea, West Texas Intermediate (WTI) from the USA, Dubai Crude from Dubai... However, there are other possibilities to classify oil by density, sulfur content, and viscosity. Crude oil supplied to refineries must meet requirements [4]. The pre-treatment of oil from harmful impurities occupies an important place among the main processes associated with the production, collection, and transportation of oil to refineries or export [5]. The harmful impurities of oil can be divided into two groups: hydrophilic (lipophobic) and hydrophobic (lipophilic). The hydrophobic impurities are soluble in oil. These hydrophobic impurities are organometallic compounds (metalloporphyrin complexes), organic acids, among which the most undesirable organochlorine compounds. The Hydrophilic impurities include impurities that are inherently insoluble in oil, these impurities are water and inorganic salts dissolved in it, as well as solid salts, mechanical impurities (sand, clay), hydrogen sulphide, etc. These hydrophilic impurities are in another phase (water), which are dispersed in the oil in the form of drops of water [6, 7]. Therefore, the degree of pre-treatment oil in production areas is an imperative and significantly affects the efficiency and reliability of transportation by pipeline, tanker, rail, and even road transportation [2]. These requirements should facilitate the transportation and future processing of Petroleum. The requirements are summarized as follows: water content, the content of mechanical impurities, saturated steam pressure, the content of chloride salts, and organochlorine compounds [5]. Usually, the degree of pre-treatment of oil for transportation does not consider the content of chloride salts and the content of organochlorine compounds [8], literally because all salts are large in water and not in oil [9], in connection with the decision of the Russian Federation to join the world trade organization (WTO), the requirements for oil are unified following the requirements for prepared oil according to ASTM D1250-97 [4] and EN 224 [3]. However, countries such as Russia use the GOST R 51858-2002 standard for oil, established by oil and gas companies for transportation by oil pipeline [5] for delivery to oil refining plants in the Russian Federation and export. In Russia, the pipeline transport takes into account the above-mentioned points [3, 10]: salt content (100–900 mg/l), water content from 0.5 to 1.0% of mass, impurity content (not over 0.05% of mass).
The crude distillation unit is the first phase of oil refining. That’s what we usually hear. However, if we are very careful, we can notice that oil refining began at the level of oil wells with its pre-treatment; the first pre-treatment of crude oil. However, additional pre-treatment is essential before the first separation (fractions our cups) are obtained. This additional pre-treatment and the manufacturing of these first fractions are carried out at the crude distillation unit as shown in Figure 1. As well, in our humble opinion for a better understanding of this unit, before getting into the thick of the topic, it is important to make the list of the main devices that make up it: The desalination plant, furnaces, distillation columns (atmospheric and under vacuum). Furthermore, in this process, there are also auxiliary equipment that is also very important, such as pumps, valves, heat exchangers, coolers, automatic process control systems, etc. The Russian Federation, as a major participant in the world oil industry alongside the United States of America, Saudi Arabia, Canada, Argentina, and other countries, has developed its own standards incorporating international standards. In a similar approach, ordinarily, in Russia, they appoint the distillation unit: Atmospheric-vacuum distillation unit (AVDU). AVDU is itself subdivided into two other units which are: Atmospheric distillations unit (ADU) and vacuum distillation unit (VDU). As a result, in this chapter, we tried to explain the operation of the atmospheric distillation crude, to model it, and to compare the usual model of the crude distillation unit with the model of the Russian Federation.
P& ID diagram flow process of crude distillation unit without vacuum distillation. We would like to emphasize that reboilers were used in this scheme in this way, just for esthetics. Less flow to the reboilers is done differently.
An emulsion is a suspension of small droplets of a liquid (water) in a second liquid (oil crude) [11]. The liquids, in a stable emulsion, can only be separated by a treatment process which calls the desalting process [10]. The electrical conductivity of oil emulsions in the literature note that it has an ionic nature. A detailed theory of ionic conductivity of liquid dielectrics. Despite the low dielectric constant, the polar components of crude oil dissociate into ions and create a fairly significant amount of electrical conductivity. The reason of this manifestation is asphalt-resinous substances in oil [12]. Oil emulsion is illustrated in Figure 2.
Oil emulsion.
The demulsifier is a chemical additive to break the crude oil emulsion. The emulsifier destroys the emulsion by reducing the mechanical resistance of the protective shells formed on the surface of the water droplets. By maintaining a strict hydrophilic-lipophilic balance [6]. These emulsions are destroyed using synthetic surfactants (demulsifiers) added to the oil emulsion [13]. The criteria for selecting and evaluating the demulsifier in terms of technology, that is, yield, are as follows [8, 12, 14]:
The velocity of separation of water from oil;
Quality of destruction of emulsions (fullness of water separation);
Reliability in changing production conditions;
The demulsifier must have a good quality/price or cost/efficiency ratio.
The process of dewatering of crude oil enters the oil production process. At the initial production period of a fresh field, wells often produce either anhydrous or low-water oil. However, over time, the water content of the oil produced increases at different rates and sometimes reaches 80–90% in old fields [1, 14]. The desalting (dewatering) processes depend on the type of oils and its content, any of the following typical processes of desalting of crude oil are combined a lot of methods like thermal, chemical, electrical and mechanical Often, a combination of Thermal and chemical methods with the mechanical or the electrical method is used to achieve effective Dehydration of crude oil [11]. The chemical treatment presents itself as a good option. It consists to use a demulsifier. The demulsifier must be introduced as early as possible (at the bottom of the well). This is an increased contact time and the interaction capacity of the demulsifier with emulsion for maximum destruction of the system [15, 16]. The injection of the demulsifying agent before the pump ensures proper contact with the crude oil and minimizes the formation of an emulsion [15]. The Industrial application of demulsifiers is not based on non-electrolytes, as their use is associated with excessive consumption or high price, as well as complex separation from oil after the deposition of the water layer. Preference is given to colloidal surface-active substances, among which are anionic, cationic, and nonionic types [13]. The number of steps (one, two or three) during oil desalination is determined by the characteristics of the initial oil emulsion and the salts contained therein For the desalination of oil emulsion independently of the stage: At the well or the refinery, the main types of equipment used for oil dewatering are electrostatics disasters, sumps, and separators [7], and they are detailed in Figure 3 [7, 17]:
thermo-chemical dehydrator;
sump;
ultrasonic;
centrifugal;
electrostatic desalter.
Some examples of devices for crude oil dewatering, degassing, and desalting. (a) Sump. (b) Separator. (c) Three-phases separator. (d) Hydrodynamic phase separator.
Each of the above-mentioned apparatus has its own peculiarities and its own derivatives, according to the precise tasks to be accomplished:
Advanced separators-vertical flow, horizontal unit with advanced electrostatic oil dehydration capabilities.
Desalting device-vertical flow, horizontal device with improved capabilities of electrostatic dehydration and desalting of oil. The process can occur in one or two stages.
Field separator-electrostatic coagulator, horizontal apparatus of electrostatic coagulator. It contains the initial section of the chimney of the heating section for preheating.
Electromechanical separators-a horizontal device that is characterized by a combination of electrostatic grids, coalescing blocks, and the initial section of the chimney heating section for preheating.
The selection criterion of devices, it is recommended to consider the following parameters when choosing the equipment [8, 12, 18]:
properties of formation fluid and its quantity;
stream type;
the resistance of emulsion;
pressure into the device;
temperature regime.
In the separators, they usually separate gas is usually from the oil in two or three steps under slight pressure or dilution. The separators of the first stage simultaneously play the role of buffer reservoirs and are usually located on the deposit. The separators of the second and third stages are mostly on the territory of central collection and distribution points (the sites of pre-treatment and pumping of oil) [7, 17]. The vertical separators are more productive in comparison with horizontal ones, but also the vertical separators have a higher price. They are suitable for enterprises with high production capacities, as well as if the emulsion contains many solid particles [18]. The horizontal separators are the best option for processing small volumes of material, as well as liquids with a high content of dissolved gas. They are in the greatest demand, as they are quite productive and affordable. To achieve maximum efficiency when using horizontal oil and gas separators, the oil is mixed in the separation process; the temperature is increased, and the pressure is reduced. To increase the depth and improve the quality of separation in Russia, introducing hot drainage water before separation with a three-phase separator is often used. Thus, they use heat, which increases the selection of gas, intensifies the process of demulsification of oil, improves the quality of spilled formation water, reduces investments, energy costs of processes, and significantly improves the conditions of Environmental protection. The three-phase separator can split oil, gas, and water at once. However, separators have limits. Even with a three-stage separation, complete separation of gas from oil is not achieved [8]. Besides, it should be noted that, despite the improvement in oil and gas separation techniques and technologies, field separators remain cumbersome and expensive devices [19]. Their operation is based on an inefficient gravitational principle and they are unproductive; the separators cease to function when the oil and gas mixture forms foam. The loss of energy contained in the flow of oil and gas, with a decrease in the pressure in the degassing in stages, leads to the need to use more pumping and compressor units for the collection and transportation of oil and gas through the pipeline [7, 8].
The final processes of dewatering and desalting are carried out at oil refineries with electrostatic desalter [20]. At the refinery, three types of electrostatic desalter are mainly operated as oil pre-treatment equipment: vertical, horizontal, and ball electrostatic desalter [1].
The salts and minerals often present in the oil are mainly magnesium, calcium, and sodium chlorides with sodium chloride being the abundant type. These salts cause corrosion of equipment. For example, hydrogen chloride (HCl). Hydrogen chloride dissolves in the emulsion’s water producing hydrochloric acid, an extremely corrosive acid. However, NaCl = Na+ + Cl−. Water, though slight, but dissociates into ions, and the equilibrium is established: H2O=H++OH−, thus, in the salt solution, there is a mixture of Na+ cations and OH−, Cl−anions. Ions in the solution move randomly and constantly collide with each other [21]. But these collisions of Na+ and OH− ions, H+ and Cl− ions do not lead to the formation of compounds, since NaOH is a strong base, and HCl is a strong acid. Since weak electrolytes are not formed when sodium chloride is dissolved in water, sodium chloride is not hydrolyzed. The concentration of H+ ions is equal to the concentration of OH− ions, so the color of the indicators does not change [13, 20]. All chemical compounds based on chlorine hydrolyze, except for NaCl, hydrolyze at high temperature to hydrogen chloride:
Any remaining salts are neutralized by the injection of sodium hydroxide which reacts with the calcium and magnesium chloride to produce sodium chloride because NaCl does not hydrolyze to the corrosive hydrogen chloride.
The electrical conductivity of oil emulsions is due to the ionic conductivity of oil, the conductivity of dispersed water droplets in oil. Under certain conditions, droplets of emulsified water in oil form conductive structures in the form of “chains”, located along the field lines [12, 22]. The electrical conductivity of the system in such cases increases sharply (hundreds and thousands of times) in comparison with the electrical conductivity of anhydrous oil. Electrical Conductivity of hydrocarbons (oil), the hydrocarbons have three types of conductivity regimes in general [23]:
The stable insulating regime, this regime is characterized by very high resistance. In this state, conduction is related to traces of dissolved water in the hydrocarbon.
The semiconductor, this regime is independent of the presence of water in the hydrocarbon.
Conductor, relatively stable. The regime, however, it disappears by sufficient removal or reduction of the applied electric field and reappears when it is restored to its initial value.
The modern desalting units are designed with electric dehydrators only horizontal execution and are part of the equipment for preparing oil: both atmospheric and atmospheric-vacuum installations. The horizontal design of electrostatic desalter has several advantages, such as a large area of the electrodes and, accordingly, a greater amount of oil per unit of section of the device, a lower vertical speed of the moving flow of oil, which provides favorable conditions for settling water, as well as implementing processes with higher pressure and temperature [22, 24]. The dominant types of electrostatic desalter are shown in Figure 4. The increases of the electrical conductivity are related to traces of dissolved water in the oil; it has the effect of slowly eliminating this water, correlative elimination of an indefinite increase in resistivity. The work and efficiency of the electrostatic desalter are based on the Stokes formula [25] for the time of deposition of water droplets and the specific electrical conductivity (γ, Om m−1) is the electrical conductivity of a substance measured between flat electrodes of the same area, located at a distance (L) in meter, and divided by the electrode area [12]. The principle of operation of the electrostatic desalter is quite simple. We have one inside two electrodes that have two opposite charges. The oil is supplied to the lower stage of the device, which provides its additional washing and passing through two (2) electric fields: weak and strong as shown in Figure 5. The charges of these electrodes change alternately, resulting in a separation of the different phases: oil, water, and gas [11, 26]. The water has a higher density than the oil and by the gravitational force, so the water is concentrated at the bottom of the electrostatic desalter. The oil and the gas without water, so without salts, come out from the upper part of the electrostatic desalter by manifold as shown in Figure 6 [20]. In the literature, there are indications that the electrical conductivity of oil and petroleum products is largely determined by the content of polar surfactants (asphalt-resins) in them [25].
The major types of electrostatic desalter.
Technical schema of electrostatic desalter design.
The simplified work description of electrostatic desalter.
They can be one and two-stage (respectively, with one or two electrostatics desalters) [20]. To increase the efficiency of the operation, the demulsifiers are added to the crude oil. Two-stage installations are used to reduce the flow of freshwater when washing crude oil [13]. The desalter of this design achieves 90% salt removal. However, 99% salt removal is possible with two-stage desalters [7, 20] as shown in Figure 7. A second stage is also essential since desalter maintenance requires a lengthy amount of time to remove the dirt and sediment which settle at the bottom. Therefore, the crude unit can be operated with a one stage desalter while the other is cleaned.
Two-stage desalting flow processing of crude oil.
The electrostatic desalter volume 96 m3, which length-10 m, diameter –3 m. U (voltage of the electrodes) = 22000 v. Maximum emulsion pre-treatment capacity is 140 tons/h. The program used in our modeling is Mathcad, to calculate the material balance and mechanical calculations of electrostatic desalter. The characteristics of the feedstock are presented in Table 1 [27, 28].
Indicators | Methods | Units of measure | Values |
---|---|---|---|
Density at 15°C | NF EN 12185 | kg/m3 | 884 |
Water content | NF EN 9029 | % mass | 1 |
Total acid number | ASTM D 664 | mg KOH/g | 0.619 |
Sulfur content | NF EN 8754 | % m/m | 0.254 |
API | ASTM D1298 | — | 29 |
Kinematic viscosity at 100°C | ASTM D445 | cSt | 1.9 |
Freezing point | NF EN ISO 3016 | °C | −17 |
The physicochemical characteristics of Bonga crude oil.
The establishment of a material balance is necessary for modeling [7, 25, 29]. The material balance material allows us to have an idea of the results we need to get and correct some errors during the project in order to have a satisfactory performance of our facilities. To calculate the material balance of electrostatic desalter, it is necessary to know the data:
the temperature at the entrance of feedstocks into the electrostatic desalter, t1 = 90°C;
the temperature at the outlet of feedstocks in the electrostatic desalter, t2 = 145°C.
The descriptive diagram of the desalting process.
The quantity of oil emulsion chosen is 140 t/h. the water Content of the initial emulsion is 1% of the total mass. The consumption of the demulsifier (surfactant) is 30 g/t. Our work in this part is to make material balances of the pre-treatment of the oil at the refinery. Electrostatic desalter performs two procedures at the same time which are: dehydration and desalination. The descriptive diagram e of the desalting process is presented in Figure 8. The amount of freshwater or water processing supplied at the desalting stage is 10% of the mass. The reagent is fed only at the dehydration stage. We consider the reagent water-soluble. First, the status of “ incoming “is drawn up. The status “ Expense “ is similar to the desalting- dewatering process. 140 t of emulsion − 1.4 t of water in emulsion = 138.6 t of oil. The status “Expense “is similar to the desalting-dewatering process. Loss is equal:
The amount of water X is 0.0691 t.
The water content-X is 0.0691 t in the desalted oil. The total water content phase in the “incoming” status is 14 t + 0.14 t = 14.14 t.
Based on the previous results and by the possibility that we can really have more losses. We arbitrarily decide to multiply our losses by 2; the total loss is: 0.4191 t + 0.4191 t = 0.8383 t. Consequently, the summary material balance of the installation is made. The total amount of drainage water is equal to the drainage water by oil treatment stage: 0.9332 t + 14.07 t = 15.0032 t. The material balance of the electrostatic desalter installation is presented in Table 2.
The exercise of modeling is a variant very often useful and used in the modeling of units and devices [7, 14, 19]. This task is interesting in case we do not have a simulator or simulation and modeling program like Hysys Aspen to solve this operation. In the framework of modeling the desalination unit, we use the ASTM D 341-2003 standard is based on Walter’s equation and proposes the dependence of the kinematic viscosity of crude oil (hydrocarbon):
where ν – viscosity, cSt, T is the absolute temperature, K; a and b are the constants determined by two known values of viscosity ν1 and ν2 at temperatures, respectively, T1 and T2. The empirical formula of formula Filonov – Reynolds is more convenient for analytical solutions:
where.
νt, νo – Dynamic viscosity of the oil at temperatures t and to, respectively, mPa·s;
ν=
In modeling of electrostatic desalter to determine his maximum performance and the required number of devices for desalting crude oil.
The interaction between water droplets can be increased by increasing the electric field strength, Е.
For to determine the
where
where
The linear velocity of the oil in the electrostatic desalter must be at least 2 times less than the calculated rate of water droplet deposition. The deposition rate is calculated using the Stokes formula [7, 25]:
where
Uwater = 0.0021 m/s.
It is necessary to check the Reynolds number (Re) by the formula:
The condition must be met:
where h1 the distance from the bottom of the electric Hydrator to the oil-water interface. We choose
Knowing the Uw, determine the Uwo and the required cross-section of the electric dehydrator (S). The actual deposition rate of water droplets in the rising oil stream will be:
The performance of the desalter:
The number of devices (N):
where
The required number of parallel running for the electrostatic desalter:
This task is as interesting as the one already solved. In case we do not have a simulator or simulation and modeling program like Ansys to solve this vital operation [1, 18, 29, 30]. The calculation of the strength of a cylindrical shell under internal pressure. The wall thickness is determined by the formula (25).
Permissible internal overpressure.
P is the pressure in the device, mPa; SR – the calculated value of wall thickness, mm; D- intern diameter of the shell, mm;
The steel grade is chosen depending on the properties of the processed medium. For butt and t-shaped double-sided seams performed by automatic welding, the coefficient of the strength of the weld
V is the rate of corrosion (usually take 0.1–0.2 mm/year); T – the service life of the device (usually take 10–12 years). For materials resistant to the processed medium, in the absence of data on permeability, it is recommended to take C = 2 mm. Condition for reliable operation
The choice of corrosion resistance of materials is made concerning this environment is resistant to corrosion.
The wall thickness calculated using this formula is rounded up to the nearest standard sheet thickness (4, 6, 8, 10, 12, 14, 18, 20 mm). The calculation of shells loaded with external over-pressure consists in determining the permissible external pressure since the wall thickness of the shell was determined earlier. Permissible external pressure:
Condition for reliable operation
P – pressure in the device, mPa = 1.1; D-inner diameter of the shell, mm = 3000. The increase in corrosion C is determined by the formula (27).
V is the rate of corrosion (usually take 0.1–0.2 mm/year); T – the service life of the device (usually take 10–12 years), but we take 20 years. For materials resistant to the processed medium, in the absence of data on permeability, it is recommended to take C = 2 mm. According to the table of corrosion resistance of materials, we choose the steel grade 316Ti, S31635-USA (ASTM/AISI), or 1.4571, X6CrNiMoTi17-12-2-Germany (DIN/WNr).
SR=
The wall thickness calculated using this formula is rounded up to the nearest standard sheet thickness (4, 6, 8, 10, 12, 14, 18, 20 mm). We assume S = 14 mm.
Condition for reliable operation
The calculation of shells loaded with external over-pressure consists in determining the permissible external pressure since the wall thickness of the shell was determined earlier.
Allowable pressure of conditions of stability within the limits of elastic deformation:
Permissible external pressure:
Condition for reliable operation
The desalting and dewatering of crude oil take begins on the oil fields. This operation is part of the processing of crude oil, and a good pre-treatment of crude oil implies:
degassing – removal of gases from crude oil;
dewatering – removal of water from crude oil.
If the desalting of crude oil is carried out qualitatively, the oil has almost no harmful effect on the equipment. Most of the impurities that cause corrosion of the metal are in the remains of formation water. Therefore, the fundamental task of desalting is to remove water drops from the oil. This is a fairly complex process, because the water in crude oil is in the form of droplets with a size quantity often. The improvement and appreciation of the oil pretreatment process level are characterized by:
providing effective sludge at high viscosity and density of oil through the use of a sump with intermediate partitions of variable height;
increasing the degree of dehydration and desalination of oil due to effective washing with water from salts;
improving the efficiency of the sump and improving the quality of the prepared oil due to more complete and qualitative removal of the intermediate layer from it, as well as due to a more uniform distribution of fluid flow rates when entering the sump and its cross-section;
ensuring uniform receipt of production of wells for the installation of oil treatment and prevention of failures of its work through the use of the reservoir;
improving the performance of the electrostatic desalter, that is, expanding the range of workloads, improving the efficiency of desalination and dehydration, as well as reducing the cost of oil pre-treatment.
The poor pre-treatment (desalting process) of crude oil can lead to considerable extra costs. We are talking about the high cost of transportation if the product is not cleared of unnecessary substances that give it extra volume and weight as well as financial investments in equipment. After all, oil, which is not derived from salt, can very quickly damage the pipeline. The requirements for the oil content of the water and especially for chlorides more stringent on the refineries. The oil content of water before processing must be no more than 0.1% of the mass and for salts-no more than 5 mg/l [3, 31]. These related requirements using much more expensive equipment (columns, heat exchangers, reboilers, etc.). Also, these the requirements induce to reduce the energy consumption, to reduce the corrosion of the equipment, to increase the life of the catalysts, improves the quality of the petroleum products. If these requirements not performed, the oil is necessarily subjected to desalting and dehydration at the electric desalting plant (electrostatic desalter). The surfactants are added if the crude oil contains a lot of suspended solids. The crude oil is heated usually to a temperature of 50 to 90°C to reduce viscosity and surface tension for easier mixing and separation of water.
The distillation is heating a liquid solution or mixture of liquid stream to produce steam, and then collecting and condensing that steam. In the simplest case, the products of the distillation process are limited to the upper distillate and the bottom, the composition of which differs from the feed. Thus, the major purpose of distillation is the separation or splitting into two or more products from a feed [32]. The distillation or rectification is one of the oldest and most common methods of chemical separation [33]. Historically, one of the most famous uses is the production of spirits from wine. More simply, in other words, the target of distillation is usually to remove the light component from the heavy component mixture, or vice-versa, to separate the heavy product from the light component mixture [32]. One of the components of crude oil refining is distillation, therefore a stage of refining. Oil refining is a rather complex technological process that begins with the transportation of oil from the field to refineries. The fractionation or distillation column exists in practically all oil refining technologies through reforming, thermal cracking, hydrocracking, etc. [20]. Before receiving the petroleum products common to users, the oil goes through several stages before becoming a finished product. Some of these stages are [1, 9, 20, 21]:
pre-treatment of crude oil;
distillation atmospheric and vacuum;
catalytic reforming, isomerization;
alkylation, visbreaking, coking;
catalytic cracking, hydrocracking;
treatment of petroleum products (hydrotreatment, desulphurization, etc.)
The oil emulsion is a complex mixture of naphthenic, paraffin, aromatic carbohydrates, which have different molecular weight and boiling point, and sulfur, oxygen, and nitrogen organic compounds. At distillation receive a big range of oil products and semi-products. The principle of the process is based on the difference between the initial boiling point of the components. As a result, the oil is divided into fractions up to fuel oil and tar and even base oil. The distillation of oil can be carried out [34]:
Single evaporation or flash vaporization
Multiple evaporations
Gradual evaporation
The single evaporation of oil is a one-step separation technique. The single evaporation process involves heating the oil to increase the temperature and enthalpy to the true boiling point (TBP) of the vapor-liquid mixture. The process of multiple evaporations is a sequence of single evaporation with a gradual increase in the heating temperature. Distillation by gradual evaporation is a slight change in the oil’s state with every single evaporation. The main devices in which the distillation of oil are distillation columns, reboilers, furnaces, etc. [1].
The difficulty of separating crude oils is mainly determined by the volatility of the key components or by the difference in the boiling point of the key components [34]. The closer the relative volatility is to one per mole, the more plates or plates are needed and more irrigation is needed to achieve the same purity of distillate and residue. For key components, two adjacent components are taken for key components, one belonging to the distillate, the other to the residual product. The relative volatility of these adjacent components and their proportion in crude oil are the main criterion determining the difficulty of sufficiently clear separation from crude oil [34]. More the tangent of the angle of inclination of the TBP increase, the easier the separation conditions are. The wider the crude oil TBP intervals, more the distillate and the residue obtained during the process are clean. As we all know, crude oil from the bowels of the Earth contains salt as dissolved salt in a tiny drop of water that forms water into an emulsion [1, 9]. This water cannot be completely separated by gravity or mechanical means. The deep separation of water from the emulsion occurs with electrostatic at the plant, before the distillation process [20].
After desalting process, the crude oil is heated in heat exchangers or reboilers (preheating of crude oil). Of course, preheating is not sufficient, since the oil must be partially evaporated to the extent that all products except atmospheric residues must be in the vapor phase when the oil enters the atmospheric column. Thus, the furnace is required to raise the temperature between 330 and 385°C depending on the components of oil [35]. The partially evaporated crude oil is transferred to the flash zone column located at a point below the distillation column and above what is called the stripping section. The main distillation column is generally up to 50 m with a 30–50 valve [34]. The size of the column is determined by the number of plates and the amount of steam. Besides, the amount of steam is determined by the content of crude oil in volatile elements or compounds. As a result, the rising steam in huge amounts and at top flow rates, requires a large diameter column above the flash zone [1, 34]. At the bottom of the section, water vapor is injected into the column to remove the atmospheric residue of any light hydrocarbon and reduce the partial pressure of hydrocarbon vapors in the flash zone [20]. This causes the true boiling point of hydrocarbons to decrease and causing more hydrocarbons to boil and raise the column to eventually thicken and removed as lateral flows. As hot vapors grow from the flash zone, they ascend into the column through the plates to the upper zone of the column [36]. A portion part of the light fraction of naphtha or gasoline returns to the column in the form of reflux. This reflux allows controlling the quality of the distillate and the pressure in the column. The main products of atmospheric petroleum distillation are [33]:
Gas
Gasoline (35–200°C)
Kerosene (220–275°C)
Diesel or gas oil (200–400°C)
Atmosphere residue (above 350°C).
The distillation process is carried out in columns with plates inside and it is as follows: hot vapors, rising on the column, in contact with the cooler liquid (reflux) flowing down. There is a cooling of the vapors, hence condensation; a transition from vapors to liquid. This is the process of mass transfer and heat exchange; the contact efficiency is provided by the plates. Most of the side currents (light fractions) pass through the striping section, where they are again dispersed to control their starting and ending boiling point, while the liquid is heated, the low boiling components evaporate [36]. The temperature and pressure have a great influence on the processes (movement of fluids) due to the plates inside the column [32]. The distillation plates are designed to create close contact between Steam and liquid during the grinding process. Mainly apply grid, groove, cap, s-shape, valve, and other types of plates. The design of the plates, besides the close contact between steam, and liquid must ensure sufficient performance of the column, have a low hydraulic resistance to the flow of steam. For example, the movement of vapors in distillation columns depends on the types of plates shown in Figures 9 and 10 [32]. The materials used in the design are also of great importance because they influence the metal capacity of structures, ease of assembly, and cleaning.
The types of plate in the column: (a) cap, (b) grid, (C) valve.
The movement of steam and liquid flows on the cap plates.
The distillation is designed to separate gas and liquid mixtures comprising two or more components or fractions. We can classify distillation columns according to various characteristics [32, 34]:
by technological application;
by an internal device (plates) ensuring contact between the steam and the liquid;
columns of atmospheric vacuum.
The quality of distillation depends on the number of plates in the column and the amount of irrigation. The speed of movement of vapors in the column and the distance between the plates is great significance. The design of distillation plates is important in the column’s performance. Thus, under practical conditions, the heat exchange between steam and liquid on the plate does not reach the equilibrium state, so the concept of plate efficiency (energy conversion efficiency) was introduced. It depends on the design and operating conditions and usually varies between 0.4 and 0.8 [32]. The distillation column comprises three (3) zones: the separation zone, the crude supply (feeding zone), and the heating zone. The feeding zone is generally below the separation zone. However, in some columns like the stripping columns, the feeding zone is located in the upper area of the column. Also, we can say that the separation zone in this type of column is non-existent. In short, this type of column is a column stabilization.
In oil refining, the first oil separation process is very often operated with complex columns or main columns [20]. The oil is sent to the atmospheric distillation column and after the desalination process. The oil is supplied to the feeding area in the form of steam, liquid, or vapor-liquid mixture. This area is called evaporative. Above the entrance (feeding zone) to the oil is the separation zone of the column, and below-the heating zone. In the evaporation zone of the column, there is single evaporation of the oil heated long before in the furnace or the heat exchanger. The purpose of atmospheric distillation is the primary separation of various “Fractions” of hydrocarbons: fuel gases, liquefied petroleum gas, naphtha, kerosene, diesel fuel, and from the bottom of the distillation; the atmospheric residue (heavy hydrocarbon residue). The residues from the atmospheric distillation column or atmospheric residues are sent to the vacuum distillation column. The atmospheric residues in the vacuum column (under the vacuum condition) and temperatures above 400°C give new fractions (heavy gasoil) [1, 32].
In oil refining, a fairly large number of plate types are widespread; new types are being developed. This situation is explained by the desire to develop more productive and economic plates than those used previously. The choice of the types of plate depends on a load of steam and liquid, the physical properties of steam and liquid [34]. In order to ensure optimal conditions for the operation of columns in various technological processes, it is necessary to use plates of different designs [32]. In atmospheric columns, steam and liquid charges are moderate. While in vacuum columns, large vapor loads and small liquid loads are observed, that is low volumetric expenditures of liquid and high linear velocities of vapors. Thus, for some varieties of columns, several types of plates are recommended, depending on the particular conditions of operation and use of these columns. These operating conditions of the column provide a comparative assessment of the different types of plates under these operating conditions as shown in Table 3. The comparison is carried out on the following characteristics and indicators [34]:
efficiency;
operating stability range;
hydraulic resistance;
ability to work on contaminated raw materials;
cost (or weight) of the column.
Feedstocks | ton/h | % mass | Products | ton/h | % mass |
---|---|---|---|---|---|
1. Oil emulsion, including: • Oil • Water 2. Surfactants (Demulsifiers) 3. Water processing (freshwater) | 140.0000 138.6000 1.4000 0.0004 14.0000 | 100.0000 99.0000 1 0.0003 10 | 1. Stable oil, including: • Desalted oil • Water 2. Drainage water 3. Loss | 138.1589 138.0897 0.06916 15.0032 0.8383 | 98.6849 98.6355 0.0495 10.7191 0.5988 |
Total | 154.0004 | 110.0003 | Total: | 154.0004 | 110.0003 |
The material balance of electrostatic desalter.
Types columns or application | Plates types | Restrictions on column diameter |
---|---|---|
AVDU units or CDU | C or S-shaped plates | No |
Atmospheric distillation of CDU or ADU, with including stripping | C or S-shaped plates | No |
Valve plates | No less 3 m | |
Jet plates | Not over 3.2 m | |
Vacuum distillation of CDU or VDU | Jet plates with bumpers | No |
Any installation, especially if there is no reliable design data | Cap plates | No |
Types of plates common in refining oil plants.
As already noted above, there is a multitude of types of plates. Then we will talk about the most frequent plates in oil plants.
The plates with holes, usually have holes on 3/16 inch to 1 inch. Pairs come out of the holes to get a multi-hole effect. The Steam or vapor velocity prevents liquid from passing through the holes. The number and size of the hole are based on the fall of steam in the column. The fluid flow is transported down the tower using triggers, a dam, and a bypass device on the side of the plate. The Minimum capacity sieve tray capacity is about 70% [30].
The cap plate is a “classic” plate, although it is still very widespread nowadays, it is gradually replaced by plates of other, more effective types. The dominant part of the cover plate is a steel disc (or cover plate) with holes for steam pipes. Usually provided with slots for passing steam, the steam will be in contact with the liquid bubble formed on the next tray. It can operate at low steam and liquid velocities [36] (less than 2 gallons per minute per foot of average flow width). The fittings are welded to the disc. Above the nozzles, caps with a diameter of 60 or 80 mm are installed. Caps have slots with a height of 15; 20 or 30 mm.
The valve plates are mainly used in CDU or AVDU and gas plants. The dominant element of the plate is a valve of round or rectangular shape that closes the holes at the base of the plate of appropriate shape. Structurally, the valve is made so that it cannot be raised to a certain height. The arrangement of the valves of round shape on the plane of the plate is the same as the plugs on the cap plate. The valve plate is used that rises with increasing steam velocity and then decreases as the stream velocity decreases, which stops the liquid from flowing. The valve can be round or rectangular, with or without a frame. The disk rises with an increase in the velocity of steam [30, 36].
The jet plate consists of a flat sheet, on which there are offset slots made in the form of a tongue with the cut-out part bent upwards. All slots are bent at a side angle. The plate has a drainage device of the usual design, but does not have a drain bar at the outlet of the liquid from the plate [32].
The role of the furnace is to heat the oil to a temperature in the range of 330–385°C in order to achieve a vapor-liquid balance before the distillation column [1, 7, 25, 29]. The most popular furnace in the Russian Federation is the tube furnace, as shown in Figure 11. The tube furnace is a unit designed to heat and force chemical processes inside the chamber, which are achieved by using the heat generated when fuel is burned. To calculate the heat balance of the atmospheric column, it is necessary to determine the heat of the furnace by the vapor phase and the liquid phase, therefore determine the material balance of the furnace. For example, the furnace material balance we used Bonga crude and the following data [25]:
the temperature at the entrance of raw materials into the convection chamber t1 = 250°C;
the temperature at the outlet of raw materials in the convection chamber t2 = 380°C;
the pressure at the exit of the furnace, p = 2 bars;
the data of the molar and mass composition of desalted crude are presented in Table 4.
Cross-sectional with heat exchange chamber of a tube furnace.
Components | kg/kmol | kg/h | % mass | Mole fraction | Steam |
---|---|---|---|---|---|
C2H6 | 30 | 22.11 | 0.02 | 0.00 | 1028.85 |
C3H8 | 33 | 388.23 | 0.28 | 0.01 | 404.90 |
Iso-C4H10 | 58 | 563.69 | 0.41 | 0.01 | 135.04 |
N-C4H10 | 58 | 886.98 | 0.64 | 0.02 | 126.43 |
Iso-C5H12 | 72 | 124.34 | 0.09 | 0.00 | 85.12 |
N-C5H12 | 72 | 31.78 | 0.02 | 0.00 | 84.19 |
75–105 | 95.1 | 4863.19 | 3.52 | 0.08 | 103.15 |
105–125 | 107.72 | 3550.68 | 2.57 | 0.05 | 25.25 |
125–145 | 118.72 | 4738.85 | 3.43 | 0.06 | 19.53 |
145–165 | 130.52 | 9035.59 | 6.54 | 0.10 | 15.72 |
165–185 | 143.12 | 2528.31 | 1.83 | 0.03 | 12.51 |
185–205 | 156.52 | 5526.36 | 4.00 | 0.05 | 9.84 |
205–225 | 170.72 | 5567.80 | 4.03 | 0.05 | 7.66 |
225–245 | 185.72 | 7046.10 | 5.10 | 0.06 | 5.88 |
245–265 | 201.52 | 4324.37 | 3.13 | 0.03 | 4.47 |
265–285 | 218.12 | 6769.79 | 4.90 | 0.05 | 3.35 |
285–305 | 235.52 | 7046.10 | 5.10 | 0.04 | 2.47 |
305–325 | 253.72 | 8469.14 | 6.13 | 0.05 | 1.80 |
325–345 | 272.72 | 15017.87 | 10.87 | 0.08 | 1.30 |
345–375 | 297.6 | 21456.08 | 15.53 | 0.11 | 0.92 |
>375 | 443.91 | 30132.46 | 21.81 | 0.10 | 0.58 |
H2O | 18 | 69.08 | 0.05 | 0.01 | 0.05 |
Data of the molar and mass composition of desalted crude.
We use the method of gradual approximation to calculate the percentage of the top product’s distillate, with the Eq. (35).
Where, Cmol-molar composition of the upper product (distillate); emol- the mole fraction of the distillate; Ki-phase equilibrium constant of components
Graph of the vapor-liquid state isotherm.
From the graph (Figure 12) we determine that the molar fraction of distillation is emol = 0.855. The molar composition of the liquid is also found by the formula (36).
The mass fraction of distillation is calculated by the formula (37):
where MsrP is average molecular weight of the vapor phase; MsgC is average molecular weight of feedstocks.
Molecular masses are calculated according to the rule of additivity (38):
Accordingly, MsrР = 180.54; MsrC = 206.77. emas = 0.747.
The amount of steam and liquid mG phases is determined by the formulas (39), (40):
where F (feedstock) is the exiting flow from the electrostatic desalter, and entering the tube furnace.
The mass of the vapor phase = 103,104 kg/h, the mass of liquid phase = 35054.88 kg/h. The mass composition of crude oil, vapor, and liquid phase after furnace are presented in Table 5.
Components | Feedstock | Products | ||||
---|---|---|---|---|---|---|
Crude oil composition | Vapor phase composition | Liquid phase composition | ||||
kg/h | % mass | kg/h | % mass | kg/h | % mass | |
C2H6 | 22.11 | 0.02 | 22.10 | 0.02 | 0.05 | 0.00 |
C3H8 | 388.23 | 0.28 | 388.05 | 0.38 | 1.47 | 0.00 |
Iso-C4H10 | 563.69 | 0.41 | 562.91 | 0.55 | 4.85 | 0.00 |
N-C4H10 | 886.98 | 0.64 | 885.67 | 0.86 | 8.16 | 0.00 |
Iso-C5H12 | 124.34 | 0.09 | 124.07 | 0.12 | 1.37 | 0.00 |
N-C5H12 | 31.78 | 0.02 | 31.71 | 0.03 | 0.35 | 0.00 |
75–105 | 4863.19 | 3.52 | 4827.44 | 4.68 | 135.74 | 0.00 |
105–125 | 3550.68 | 2.57 | 3517.01 | 3.41 | 112.85 | 0.00 |
125–145 | 4738.85 | 3.43 | 4683.13 | 4.54 | 169.45 | 0.00 |
145–165 | 9035.59 | 6.54 | 8902.49 | 8.63 | 368.15 | 0.01 |
165–185 | 2528.31 | 1.83 | 2481.17 | 2.41 | 118.91 | 0.00 |
185–205 | 5526.36 | 4.00 | 5394.59 | 5.23 | 303.92 | 0.01 |
205–225 | 5567.80 | 4.03 | 5396.30 | 5.23 | 362.68 | 0.01 |
225–245 | 7046.10 | 5.10 | 6762.91 | 6.56 | 550.50 | 0.02 |
245–265 | 4324.37 | 3.13 | 4095.48 | 3.97 | 410.07 | 0.01 |
265–285 | 6769.79 | 4.90 | 6293.92 | 6.10 | 787.63 | 0.02 |
285–305 | 7046.10 | 5.10 | 6384.01 | 6.19 | 1014.91 | 0.03 |
305–325 | 8469.14 | 6.13 | 7401.03 | 7.18 | 1519.84 | 0.04 |
325–345 | 15017.87 | 10.87 | 12475.46 | 12.10 | 3365.64 | 0.10 |
345–375 | 21456.08 | 15.53 | 16251.21 | 15.76 | 6314.27 | 0.18 |
>375 | 30132.46 | 21.81 | 6154.41 | 5.97 | 19501.56 | 0.56 |
H2O | 69.08 | 0.05 | 68.95 | 0.07 | 2.51 | 0.00 |
Total | 138158.9 | 100 | 103,104 | 100 | 35054.88 | 100 |
The material balance of tube furnace.
The production capacity of the atmospheric distillation unit for processing crude oils is 1,159,200 tons/year, with an initial load of 140 kg/h. This material balance as shown in Table 6 was made based on the physicochemical characteristics of Bonga crude oil and the typical CDU model without the K-1 oil topping column.
Feedstocks | ton/year | % mass | Products | ton/year | % mass |
---|---|---|---|---|---|
1. Oil emulsion 2. Chemical agent (demulsifiers) 3. Water processing (freshwater) 4. Water vapor | 1,159,200 3.48 115.92 4968 | 99.56 0.00 0.01 0.43 | 1. Gases (LPG) 2. Fractions 35–145 3. Fractions 145–230 4. Fractions 230–320 5. Fractions 320–350 The target products. (sum. fractions) 6. Associated product (Atmospheric residues) 7. Drainage water | 4938.72 69109.88 125052.05 201243.36 231212.84 631556.87 413475.76 119254.770 | 0.42 5.93 10.74 17.28 19.86 54.25 35.51 10.24 |
Total | 1164287.39 | 100 | Total | 1164287.39 | 100 |
The material balance of atmospheric distillation unit with operating time 340 days by year (365 days −20 days)
Based on the evaluation of the concept of the technological scheme for the construction of a technological scheme of crude distillation unit at refineries in Russia. The topping column K-1 in most cases is a simple design as shown in Figure 13 [28], although it fractionates the crude oil into the many components like ethane, light gasoline, etc.. There are schemes in which light gasoline is displayed under the distillate in the top of the column, and heavy gasoline on the side flanks of the column. The topping column K-1 collects 50–60% of the potential of light gasoline. The residues of column K-1 are therefore the raw material of the main atmospheric column. The composition of this raw material is weighted in such a way that an excessively high feed temperature is required, permissible temperature (380°C). The singularities of the topping column K-1 operation are as follows [1, 28]:
The low yield of rectified gasoline (5–15% of the mass of the column load) makes it difficult to collect the gasoline fraction from the oil;
Extremely high liquid loading in the heating zone of the pre-evaporation column due to the low steam load worsens the conditions for steaming light fractions from the residue under the action of hot jet reflux;
The relatively small enthalpy of crude oil (220°C) introduced into the column does not create sufficient heat flow for distillation, therefore, it is necessary to introduce additional heat in the form of hot jet reflux;
Maintaining high pressure in the column to ensure air and water condensation of light gasoline fractions in condensers-refrigerators (separators).
Possible schemes of operation with oil topping column K-1. (a) Column K-1 with back topped crude. (b) Column K-1 with heavy gasoline and back topped crude. (c) Column K-1 without back topped crude.
The purpose of this column is to extract from the oil the remains of dissolved gas (if the oil has not been stabilized) and a light gasoline fraction with a boiling point of 85°C. After atmospheric residue of K-2 shipped to the vacuum column K-5 for to obtain vacuum distillates (heavy gasoil) and tar. In order to illustrate our argument, a typical P&ID flow diagram process of the atmospheric distillation unit in Russian refineries is presented in Figure 14.
The typical P&ID flow diagram process of atmospheric distillation unit at refineries in Russian Federation.
A general technological approach to the atmospheric distillation unit (ADU) can be described as below [28].
The oil topping column K-1:
Top temperature, °С – no higher than 245;
Low temperature, °С – no higher than 150;
Pressure, bar – no more than 3.0.
The typical products of K-1 are;
Gases
Light straight run naphtha (light gasoline or light naphtha)
Heavy gasoline (or military jet fuel)
Topped crude
The main atmospheric column K-2:
Top temperature, °С – no higher than 350;
Low temperature, °С – no higher than 150;
Pressure, bar – no more than 1.4.
The typical products of K-2 are:
Heavy gasoline (or military jet fuel)
Kerosene (light distillate or jet fuel)
Middle distillates or light gas oil (LGO) – Diesel
Heavy distillates – atmospheric gas oil (AGO) or heavy gas oil (HGO)
Crude column bottoms -atmospheric residue or topped crude
The distillation processes are the processes of oil separation into more or less homogeneous fractions without chemical conversion of its constituent substances. The process of separation of liquid substances by their boiling temperatures is atmospheric and vacuum. The atmospheric distillation can be carried out in the following ways:
With a single separation – furnaces and separation of distillate in one (main) distillation column k-2;
Double separation in two distillation columns- in the pre-evaporation column k-1 with separation of light gasoline fractions and the main column-2;
Gradual separation.
The oil topping column K-1, in atmospheric distillation, collects 50–60% of the potential of light gasoline from oil [28]. Otherwise, the composition of oil for the atmospheric column K2 is so weighted that an excessively high supply temperature is required, permissible temperature (380°C). The oil topping column K-1 is especially important in the general crude distillation unit technology in Russia. We know that the choice of flow process technology is dictated by the physicochemical properties of the oils and their compounds. Indeed, the choice of structure of atmospheric vacuum distillation units or atmospheric distillation units is determined by the characteristics of crude oil. Finally, according to our studies, the distillation unit with the oil topping column K-1, is more flexible and versatile, which on the whole allows processing any feedstock. Table 7 shows the conclusions on the different types of atmospheric distillation [28].
Types of CDU | Crude distillation unit with K-1 | Crude distillation unit without K-1 |
---|---|---|
Advantages |
|
|
Disadvantages |
|
|
Summary of advantages and disadvantages of different types of technology.
The crude oil is a complex mixture of paraffin, naphthenic, aromatic, and other hydrocarbons with different molecular masses and boiling temperatures. Also, the oil contains sulfur, oxygen, and nitrogen-containing organic compounds. Therefore, to obtain from oil commodity products for various purposes, apply methods of separation of oil into fractions or groups of hydrocarbons. The modern dewatering-desalting processes are designed with electrostatic desalter only by horizontal geometry design: Atmospheric and atmospheric-vacuum. The horizontal design of electrostatic desalter has a lot of advantages, such as a large area of electrodes and, accordingly, a larger amount of oil per unit section of the device, a lower vertical speed of the moving oil flow, which provides favorable conditions for water sedimentation, as well as implementing processes with higher pressure and temperature. The electrostatics desalters are characterized by:
More favorable conditions for the deposition of water drops;
Specific performance, 3 times higher than vertical and ball structures in the presence of low specific gravity and lower cost of the device;
Simplicity of design, a small amount of electrical equipment, ease of installation, availability of maintenance and maintainability;
Ability to work with high pressure and temperature parameters.
However, the pretreatment of crude oil is not only concerned with its desalting and dewatering, but also with its degasification and packaging into a semi-product under the standard like ASTM D 1250-97, API Petroleum Measurement and GOST R 51858.
The distillation processes are the processes of oil separation into more or less homogeneous fractions (cups) without chemical conversion of its constituent substances. The process of separation of liquid substances by their boiling temperatures is atmospheric and vacuum. The oil distillation via single and multiple evaporations. In industrial conditions, the processes are carried out on the equipment of continuous action. During the single-evaporation distillation, the oil is heated to a certain temperature and all fractions that have passed into the vapor phase are collected. The distillation of the oil by multiple evaporations consists in that the oil is first heated to a temperature allowing to separate the light gasoline fraction. Then the crude without the fraction of light gasoline is heated to a higher temperature, and fractions that boil at about 375°C (that is, fractions of heavy gasoline, jet fuel, and diesel fuel) are also collected. In the residue from distillation, atmospheric residues are obtained. The atmospheric residues are distilled under vacuum, from which the lubricating oil fractions are obtained. Finally, the tar is obtained as residues from vacuum distillation. In other words, oil is consistently heated three times, each time separating the vapor phase from the liquids. The resulting steam and liquid phases are subjected to rectification in columns. Thus, industrial processes of oil distillation are based on a combination of distillation with single and multiple evaporations and subsequent rectification of the steam and liquid phases. We want to emphasize that this is the case, we use the K-1 oil topping column. However, if the process is executed without column k1, the same process is shorter and with the results already mentioned above. In the distillation column, there are distillation plates on which the vapors rising along the column are in contact with the flowing liquid (reflux). Reflux is created due to the fact that part of the upper product returns to the liquid state to the upper plate and flows down, enriching the rising vapors with low-boiling components. One of the ways to increase the concentration of high-boiling components in the residue from oil distillation is to introduce an evaporator into the lower part of the distillation column. As such, you can use water vapor, inert gas (nitrogen, carbon dioxide, petroleum gas), gasoline vapor or kerosene. The water vapor is most widely used as an evaporator for oil refining. Its presence in the distillation column reduces the partial pressure of hydrocarbons, and therefore their boiling point. As a result, the lowest-boiling hydrocarbons in the liquid phase, after single evaporation, pass into a vaporous state and, together with water vapor, rise up the column. In many literatures, it is recommended to use super-heated water vapor and enter it into the column with a temperature equal to the temperature of the feedstock or slightly higher. Usually, the water vapor used after steam pumps and turbines at a pressure of 2–3 bar is superheated in a tube furnace and introduced into a column with a temperature of 350–450°C. The use of wet vapor steam is not practiced, since its temperature and pressure are interrelated, for example, when introducing a column of 350°C, its pressure is equal to 170 bar. Besides, with increasing pressure, the cost of saturated water vapor increases sharply, so it is not economical to use it. If the wet vapor steam enters a column of low-pressure saturated water vapor, for example, 10 bar and, accordingly, with a temperature of 180°C, then part of the heat will go to heat it.
GOST | Russian Interstate-standard |
ASTM | American Society for Testing and Materials |
NF EN ISO | French Norms European Norms International Organization for Standardization |
ρ90 | density at 90°С |
μoil crude | kinematic viscosity of crude oil |
AVDU | atmospheric-vacuum distillation unit |
ADU | atmospheric distillations unit |
CDU | crude distillation unit |
Refinery | petroleum refinery plant |
VDU | vacuum distillation unit |
K1 | oil topping atmospheric column |
K2 | main atmospheric column |
TBP | true boiling point |
t/h | ton/hour |
kg/h | kilogram/hour |
WV | water Vapor |
P&ID | piping and instrumentation diagram |
The goal of the drug development process is to find bioactive molecules that can help in disease therapy [1, 2]. The drug discovery life cycle has multiple steps: drug target identification, target validation, hit identification, lead optimization, preclinical development, clinical trial, approval, and postmarketing monitoring (Figure 1A). Because going through all of these stages of developing a new drug can cost between $1 and $2 billion and take 10–17 years, drug discovery is a big issue in the pharmaceutical business [3]. To speed up the drug discovery process, a considerable number of developments were made in the 1990s using combinatorial and high-throughput screening (HTS) approaches. These approaches were widely used since they allowed for the quick synthesis and screening of vast libraries, but no meaningful success was achieved, and little progress was made toward the discovery of new compounds. To aid the discovery process, a combination of modern computer approaches, biological research, and chemical synthesis was developed, and this combined approach increased the scope of discovery. The term "computer-aided drug design" (CADD) was eventually used to describe the use of computers in drug discovery. Computer-aided drug design (CADD) is one of the most widely utilized approach for reducing drug development costs and time. CADD is a specialized field, in which various computational approaches are employed to mimic receptor–drug interactions in order to identify binding affinities (Figure 1B). The approach, however, is not just for studying chemical interactions and predicting binding affinity; it can be used for everything from designing compounds with desired physiochemical features to managing digital databases of chemicals. CADD is a wide term that encompasses both structure- and ligand-based drug developments. Virtual screening (VS) is a computational method for screening large databases of compounds that has successfully supplemented HTS in drug discovery. The fundamental purpose of VS is to make it feasible to quickly and cheaply screen enormous virtual chemical databases for potential leads for synthesis and future study [4]. Computer-assisted virtual screenings have been a widely used method for estimating various types of ligands to bind with target over time [5, 6, 7, 8]. Additionally, in order to investigate atomistic level of protein/nucleic acid-small molecule interactions, one of the widely utilized computational biophysics tools is molecular dynamics (MD) simulation [9, 10]. MD simulation finds its relevance in shedding lights on the conformational ensembles either of the small molecule or of the target. The technique is seldom utilized to capture the dynamics of proteins and/or to check the stability of modeled protein structures enabling CADD for designing efficient inhibitors [11, 12]. It is also leveraged to investigate a comparative binding of small molecule to different proteins along with complementing experimental observations [13].
Flowchart of events taken place in (A) drug discovery lifecycle and (B) computer aided drug discovery.
The recent expansion of make-on-demand libraries to billions of synthesizable molecules has piqued the interest of the drug-discovery community, as such massive databases allow access to previously unexplored chemical realms. The introduction of ultralarge libraries, on the other hand, has revealed substantial limitations of traditional docking techniques, which typically work on the scale of millions of molecules at a high cost of computation. This aspect depicts CADD as a very useful process, in which only a small portion of the highest-scoring compounds often leaving low scoring but potential compounds are considered for experimental examination. Artificial intelligence (AI) and machine learning (ML) aided approaches provide a low-cost, high-reliability solution to a variety of problems (Figure 2), from protein three-dimensional (3D) structure prediction to physiochemical property calculation and bioactivity prediction to ultralarge docking [14, 15].
Biomolecular analysis core scheme for drug discovery via AI/ML.
The ultimate goal of artificial intelligence (AI) is to train computer programs with human-like intellect. For this, AI uses computers to learn human behaviors, such as learning, judgment, and decision-making by simulating human intelligent behavior with computers. The term artificial intelligence was first proposed in 1956 at a conference at Dartmouth University; however, the major AI-related research started since the end of the twentieth century. AI has provided enormous economic benefits to humanity and has helped all parts of life, while also considerably promoted social growth and ushered in a new era of social development [16, 17]. Both the volume and the multidimensionality of data have increased dramatically as a result of the advent of numerous high-throughput technologies. Big data is both a requirement and a key component for AI to improve its recognition rate and accuracy [16].
Machine learning (ML), a branch of AI, is the use of an algorithm that improves its performance by learning from data. Machine learning, according to Arthur Samuel, is described as a computer\'s ability to analyze without being explicitly programmed [16, 18]. Supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning are the four types of machine learning algorithms [16]. In supervised learning, the test data are trained with a labeled dataset to predict the type or value of new data, whereas unsupervised learning uses unlabeled data based on the input pattern. Support vector machine (SVM), linear discrimination, and decision tree are some of the types of supervised learning algorithms, whereas k-clustering and principal component analysis are the examples of unsupervised learning algorithms. Semisupervised learning combines the benefits of both supervised and unsupervised learning. It can be useful if there exist unlabeled data and collecting the labeled data is a time-consuming procedure. Reinforcement learning seeks to solve a problem through a hit-and-trial strategy, including feedback and decisions, with the ultimate goal of increasing total reward [16, 18, 19]. Deep learning (DL), a subset of machine learning, is one of the most cutting-edge areas of research and development in practically every scientific and technical discipline. Many problems that normal ML algorithms could not solve, such as image recognition and speech recognition, can be solved with the help of DL methods. DL methods also have immense role in the drug discovery pipelines, including drug activity prediction, target identification, and lead molecule discovery. The foundations of DL are frequently implicated in neural network systems, where they are employed to develop systems capable of complicated data recognition, interpretation, and production [20].
Drug design is based on the idea of creating compounds with a regulated interaction profile against a variety of target and off-target proteins in an organism. To understand the mode of action of a candidate drug, three-dimensional (3D) details are of paramount importance. Despite the availability of a variety of experimental methods to decipher the 3D structure of proteins, such as X-ray crystallography, nuclear magnetic resonance (NMR), and cryo-electron microscopy, the sequence–structure gap, in which protein sequences vastly outnumber the number of corresponding 3D structures, frequently causes problems. In such cases, protein structure prediction methods come as a remedy [21, 22].
Over the past 30 years, AI and ML methods have been used to predict protein structure. AI programs have helped to assess and identify most accurate models. To compare the predicted models to known crystal structures, these programs are trained utilizing numerous numerically represented atomic parameters from the models, such as bond lengths, inter-residue interactions, physiochemical properties, and so on. The Critical Assessment of Protein Structure Prediction (CASP) contests have been held biannually since 1994 for the blind evaluation of cutting-edge methods for predicting three-dimensional (3D) protein structures from protein sequences [23, 24]. For the cases where a template is not available for modeling, two approaches are considered: fragment-based assembly and
With near-experimental precision, Alphabet\'s DeepMind won the 13th edition of CASP in 2018 with its latest artificial intelligence (AI) system, AlphaFold [25]. The 3D structure prediction by assembling the most probable fragments by AlphaFold is done by using co-evolution analysis of a multiple sequence alignment and using deep neural networks (DNNs) to discover coevolutionary patterns in protein sequences as contact distributions and transform them into protein-specific statistical energy potentials [23]. DeepFragLib, a fragment library constructed utilizing deep contextual learning techniques to give high-quality, native-like fragments for every segment of a protein for the efficient assembly of near-native conformations, is another example of AI breakthrough in the field of structure prediction. Table 1 represent applications of some AI-ML approaches for protein structure prediction/quality assessment.
S. No. | Tools | Description | Web-link |
---|---|---|---|
1 | AlphaFold [26] | Protein structure prediction using AI | https://github.com/deepmind/alphafold |
2 | DeepFragLib [27] | Fragment library construction software by DNN | https://github.com/ElwynWang/DeepFragLib |
3 | ProQ3/ProQ3D [28] | Protein quality assessment using deep learning | https://proq3.bioinfo.se/ |
4 | QACon [29] | Protein model quality assessment using ML techniques | https://swmath.org/software/34249 |
5 | DeepQA [30] | Protein model quality assessment using deep belief networks | https://swmath.org/software/15927 |
6 | DEFMap [31] | DL-based method for extracting the dynamics associated with atomic fluctuations concealed in cryo-EM density maps | https://github.com/clinfo/DEFMap |
Few examples of applications of AI–ML methods in protein structure methods.
In the biopharmaceutical sectors, the effective and precise forecasting of molecular characteristics of drug compounds is indeed a fundamental component of rationalized compound synthesis. Current techniques span from basic atom summation through bond energy additions, paired interatomic configurations, and more sophisticated machine learning systems capable of representing aggregate reactions among several particles or bonds. In addition, simple correlation force fields show predictive performance comparable to reference energy sources determined utilizing density functional theory with hybrid exchange-correlation functional for steady-state geometric models; even so, properly accounting for the collaborative many-body connections is required for advancing the “magic formula” of compound accuracy of 1 kcal/mol for both the steady-state and out-of-equilibrium topologies [32]. In the years 2010–2012, the initial machine learning (ML) methods for molecular modeling relied on tiny datasets with quantum mechanical (QM) features for 102–103 molecule systems. It is believed that the chemical compound space has 1060–10,100 molecular systems. Chemical spaces have grown in size and complexity during the previous decade. Data are being generated at an astonishing rate owing to large-scale QM and MD methodologies, as well as developments in high-throughput studies [33].
Machine learning models predict small molecule’s properties based on their chemical structure. Because of their ease of interpretation and effectiveness on small datasets, linear models were initially used. However, over time, nonlinear models were developed to capture more complex relationships between structure and activity. The nonlinear approaches include support vector machines, recursive partitioning methods, and deep learning methods. With the availability of standardized large-scale data, deep-learning-based techniques for ADMET (absorption, distribution, metabolism, excretion, and toxicity) prediction are showing growing promise and utility. The ability to identify small compounds with increased efficacy, safety, and dosage is considerably aided by understanding ADMET characteristics. In terms of consistency and predictive performance, the graph convolutional DNN (GCNN) technique is proposed to be superior to existing approaches such as random forest (RF), Cubist, and support vector machine (SVM) for calculating ADMET characteristics [34]. The AI-based ADMET predictors utilize cellular permeability data from a diverse class of molecules generated by different cell lines. To predict acid dissociation constant of compounds, artificial neural network (ANN)-based models, graph kernels, and kernel-ridge-based models have been used. To predict the solubility of the compounds, undirected graph recursive neural networks and GCNN have been used. GCNN methods are also used to predict cytotoxicity, which is one of the important properties used in drug discovery to avoid toxic effects [35]. The latest ANN studies support immunoinformatics and chemoinformatics analysis for novel vaccine and drug discovery [11]. Examples of the AI-based tools for molecular property calculation are DeepTox (www.bioinf.jku.at/research/DeepTox), Chemputer (https://zenodo.org/record/1481731), and ORGANIC (https://github.com/aspuru-guzik-group/ORGANIC) [35].
In order to prioritize compounds for synthesis and/or biological evaluation, quantitative structure-activity relationship (QSAR) modeling has been used [36]. The goal of QSAR models is to find a mathematical relationship between the physicochemical qualities of substances, which are represented by molecular descriptors, and their biological activity. These models are important in drug optimization because they provide a preliminary
To fully comprehend a drug\'s efficacy and usefulness, it is important to determine how it interacts with a receptor or target. Drug-protein interactions have recently been a hot topic in drug repurposing research [38]. ML algorithms have become the advanced approach for estimation of drug–target interactions due to the huge amount of obtainable drugs and target information in huge datasets, advancing as well as innovative computer networking, and inherent characteristics of different types of deep learning. A vast number of proteins have indeed been sequenced, and numerous molecules have now been synthesized since the advent of sequencing technology, high-throughput technologies, and computer-aided drug design methods. Actual information has been organized, and multiple databases have been developed based on existing related efforts and acquired expertise. The majority of data in these sources is open to the public and free to download, thus providing a strong data basis for using deep learning to solve drug-target contact predictions issues. PubChem presently comprises 109 million chemicals and is the world’s biggest database with open access to chemical characterization. PubChem has grown in importance as a source of chemical knowledge for researchers, learners, and the general public. Artificial intelligence can be used to train deep learning models for drug discovery using known drug data [39]. Several ML techniques have been used to predict drug–target interactions including SVM, DL, DNN, convolutional neural network (CNN), etc. The
S. No. | Tools | Description | Web-link |
---|---|---|---|
1 | Ligdream [41] | For | https://playmolecule.com/LigDream/ |
2 | WADDAICA [40] | Uses both deep learning model and classical algorithms for drug design | https://heisenberg.ucam.edu:5000/ |
3 | MolAICal [42] | Uses both deep learning model and classical algorithms for drug design | https://molaical.github.io/ |
4 | OpenChem [39] | A deep learning toolkit for computational chemistry | https://github.com/Mariewelt/OpenChem |
5 | DeepAffinity [43] | A combination of RNN and CNN methods for ligand–protein affinity | https://github.com/Shen-Lab/DeepAffinity |
6 | DeepFrag [44] | Uses deep CNN for fragment-based lead optimization | https://durrantlab.pitt.edu/deepfragmodel/ |
Few examples of applications of AI–ML methods in drug–protein interactions.
Although AI is frequently portrayed as a magic wand that can provide flawless output regardless of the quality of the input, it is not the solution to every problem. The ultimate goal of using AI and machine learning approaches to drug development challenges is to bring the best drugs to market. Throughout the drug discovery process, the combined effort of different AI methods allows for a better understanding and design of novel inputs [45]. The AI-based applications are getting more intelligent, cost-effective, and time-efficient while increasing efficacy, because of more precise algorithms, more powerful supercomputers, and significant private and public investment in the sector [20]. To properly leverage AI in drug development, one must increase the quality of decisions we make regarding compounds that are progressed to clinical trials. However, in many circumstances, the data available to make those decisions are not totally sufficient for this purpose [46]. Since the entire success of AI depends on the availability of a substantial amount of data, we need to conduct trials more efficiently, which can be supported by computational methods [35, 46]. Major challenges faced by AI methods include data accuracy and availability, reproducibility, model appropriateness, etc. Despite the challenges, AI is projected to advance the field of personalized/precision medicine to the point where it becomes regular practice even in the treatment of minor illnesses in the future [47]. By 2028, AI is expected to save the pharmaceutical industry more than US$70 billion in drug discovery costs [48]. With more clinical data and improved AI calculations, AI is projected to improve many elements of drug discovery and development and will eventually become the standard computer-assisted technique for drug discovery.
ANJ would like to acknowledge Department of Science and Technology (DST-SERB File no. CRG/2020/001829), Government of India, for providing computational facilities.
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