Matches in SemOpenAlex for { <https://semopenalex.org/work/W2948061062> ?p ?o ?g. }
- W2948061062 endingPage "2995" @default.
- W2948061062 startingPage "2979" @default.
- W2948061062 abstract "To obtain the high-quality crude oil from the surface processing plants, oil and gas separation plants parameters need to be optimized, by minimizing the intermediate components, flash from the crude oil during primary and secondary separation processes. The aim of this paper is to present an accurate methodology for predicting optimized separation parameters in the multistage crude oil production unit. The new proposed methodology determines the optimum pressures of separators in different stages of separation and consequently optimizes the operating conditions. A dynamic simulator is used to generate the data set for a designed production facility. Then, an optimization algorithm is used to build an optimum artificial neural network model to predict the optimum operating conditions that will maximize the liquid recovery. The ultimate objective of this work is to have an advisory system for optimizing liquid recovery from the production facilities." @default.
- W2948061062 created "2019-06-14" @default.
- W2948061062 creator A5049649985 @default.
- W2948061062 creator A5068063599 @default.
- W2948061062 creator A5081730437 @default.
- W2948061062 creator A5084940954 @default.
- W2948061062 date "2019-06-03" @default.
- W2948061062 modified "2023-09-30" @default.
- W2948061062 title "Intelligent prediction of optimum separation parameters in the multistage crude oil production facilities" @default.
- W2948061062 cites W149442419 @default.
- W2948061062 cites W1617029840 @default.
- W2948061062 cites W1819871327 @default.
- W2948061062 cites W1909045006 @default.
- W2948061062 cites W1963636312 @default.
- W2948061062 cites W1968985240 @default.
- W2948061062 cites W1971441898 @default.
- W2948061062 cites W1976553449 @default.
- W2948061062 cites W1980000853 @default.
- W2948061062 cites W1985928198 @default.
- W2948061062 cites W1987184679 @default.
- W2948061062 cites W1997126365 @default.
- W2948061062 cites W1999352914 @default.
- W2948061062 cites W1999883131 @default.
- W2948061062 cites W2006762922 @default.
- W2948061062 cites W2010035147 @default.
- W2948061062 cites W2013834665 @default.
- W2948061062 cites W2015624944 @default.
- W2948061062 cites W2016482889 @default.
- W2948061062 cites W2017868205 @default.
- W2948061062 cites W2020909940 @default.
- W2948061062 cites W2033518453 @default.
- W2948061062 cites W2034709803 @default.
- W2948061062 cites W2035490663 @default.
- W2948061062 cites W2036166940 @default.
- W2948061062 cites W2036810629 @default.
- W2948061062 cites W2051005367 @default.
- W2948061062 cites W2059927105 @default.
- W2948061062 cites W2060324796 @default.
- W2948061062 cites W2061871963 @default.
- W2948061062 cites W2082001479 @default.
- W2948061062 cites W2102733140 @default.
- W2948061062 cites W2118889673 @default.
- W2948061062 cites W2121706997 @default.
- W2948061062 cites W2129202645 @default.
- W2948061062 cites W2140216421 @default.
- W2948061062 cites W2142166388 @default.
- W2948061062 cites W2164628972 @default.
- W2948061062 cites W2227048027 @default.
- W2948061062 cites W2245212056 @default.
- W2948061062 cites W2413581040 @default.
- W2948061062 cites W2487404630 @default.
- W2948061062 cites W2549123726 @default.
- W2948061062 cites W2555410538 @default.
- W2948061062 cites W2560344098 @default.
- W2948061062 cites W2610428084 @default.
- W2948061062 cites W2620923682 @default.
- W2948061062 cites W2766677625 @default.
- W2948061062 cites W2786052368 @default.
- W2948061062 cites W4300719089 @default.
- W2948061062 doi "https://doi.org/10.1007/s13202-019-0698-6" @default.
- W2948061062 hasPublicationYear "2019" @default.
- W2948061062 type Work @default.
- W2948061062 sameAs 2948061062 @default.
- W2948061062 citedByCount "19" @default.
- W2948061062 countsByYear W29480610622019 @default.
- W2948061062 countsByYear W29480610622020 @default.
- W2948061062 countsByYear W29480610622021 @default.
- W2948061062 countsByYear W29480610622022 @default.
- W2948061062 countsByYear W29480610622023 @default.
- W2948061062 crossrefType "journal-article" @default.
- W2948061062 hasAuthorship W2948061062A5049649985 @default.
- W2948061062 hasAuthorship W2948061062A5068063599 @default.
- W2948061062 hasAuthorship W2948061062A5081730437 @default.
- W2948061062 hasAuthorship W2948061062A5084940954 @default.
- W2948061062 hasBestOaLocation W29480610621 @default.
- W2948061062 hasConcept C119857082 @default.
- W2948061062 hasConcept C127413603 @default.
- W2948061062 hasConcept C139719470 @default.
- W2948061062 hasConcept C154945302 @default.
- W2948061062 hasConcept C162324750 @default.
- W2948061062 hasConcept C21880701 @default.
- W2948061062 hasConcept C2776061190 @default.
- W2948061062 hasConcept C2778348673 @default.
- W2948061062 hasConcept C2987168347 @default.
- W2948061062 hasConcept C41008148 @default.
- W2948061062 hasConcept C50644808 @default.
- W2948061062 hasConcept C78762247 @default.
- W2948061062 hasConceptScore W2948061062C119857082 @default.
- W2948061062 hasConceptScore W2948061062C127413603 @default.
- W2948061062 hasConceptScore W2948061062C139719470 @default.
- W2948061062 hasConceptScore W2948061062C154945302 @default.
- W2948061062 hasConceptScore W2948061062C162324750 @default.
- W2948061062 hasConceptScore W2948061062C21880701 @default.
- W2948061062 hasConceptScore W2948061062C2776061190 @default.
- W2948061062 hasConceptScore W2948061062C2778348673 @default.
- W2948061062 hasConceptScore W2948061062C2987168347 @default.
- W2948061062 hasConceptScore W2948061062C41008148 @default.
- W2948061062 hasConceptScore W2948061062C50644808 @default.