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master's thesis
Predikcija PVT svojstava neuronskom mrežom
diplomski rad
Zagreb: University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, 2017. urn:nbn:hr:169:299292
Pavić, Marčelo
University of Zagreb
Faculty of Mining, Geology and Petroleum Engineering
Department of Petroleum and Gas Engineering and energy

Institutional repository: Faculty of Mining, Geology and Petroleum Engineering Repository, University of Zagreb

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Pavić, M. (2017). Predikcija PVT svojstava neuronskom mrežom : diplomski rad (Master's thesis). Zagreb: University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:169:299292

Pavić, Marčelo. "Predikcija PVT svojstava neuronskom mrežom : diplomski rad." Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, 2017. https://urn.nsk.hr/urn:nbn:hr:169:299292

Pavić, Marčelo. "Predikcija PVT svojstava neuronskom mrežom : diplomski rad." Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, 2017. https://urn.nsk.hr/urn:nbn:hr:169:299292

Pavić, M. (2017). 'Predikcija PVT svojstava neuronskom mrežom : diplomski rad', Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, accessed 22 November 2024, https://urn.nsk.hr/urn:nbn:hr:169:299292

Pavić M. Predikcija PVT svojstava neuronskom mrežom : diplomski rad [Master's thesis]. Zagreb: University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering; 2017 [cited 2024 November 22] Available at: https://urn.nsk.hr/urn:nbn:hr:169:299292

M. Pavić, "Predikcija PVT svojstava neuronskom mrežom : diplomski rad", Master's thesis, University of Zagreb, Faculty of Mining, Geology and Petroleum Engineering, Zagreb, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:169:299292

Metadata
TitlePredikcija PVT svojstava neuronskom mrežom : diplomski rad
Title (english)Prediction of PVT properties with neural networks : master’s thesis
AuthorMarčelo Pavić
MentorDomagoj Vulin (mentor)
Committee memberDomagoj Vulin (predsjednik povjerenstva)
Committee memberTomislav Kurevija (član povjerenstva)
Committee memberLuka Perković (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Mining, Geology and Petroleum Engineering
(Department of Petroleum and Gas Engineering and energy)
Zagreb
Defense date and country2017-02-17, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Mining, Petroleum and Geology Engineering
Petroleum Mining
Abstract
Umjetne neuronske mreže su nova tehnologija koja je nastala kao pokušaj oponašanja rada ljudskog mozga, a našla je primjenu u rješavanju složenih nelinearnih problema na mnogo različitih područja. U ovom radu su neuronske mreže korištene za predikciju pVT (engl. pressure-volume-temperature) svojstava nafte iz polja Žutica. Mreže su trenirane na tri različita seta podataka, za predikciju volumnog faktora nafte, plinskog faktora i tlaka zasićenja nafte. Napravljeno je ukupno 28 različitih modela neuronskih mreža, a razlikuju se po arhitekturi, broju iteracija, stopi učenja i broju podataka u setu za treniranje, kalibraciju i verifikaciju.
Abstract (english)
Abstract: Artificial neural networks are new technology which was developed to simulate human brain and it is used for solving difficult nonlinear problems in many different areas. In this thesis neural networks are used for predicting of PVT (pressure-volume-temperature) properties of oil from Žutica field. Three different data sets were used for training neural networks for prediction of oil formation volume factor, solution gas-oil ratio and bubble point pressure. It was produced 28 different models of neural networks, based on different architecture, number of learning cycles, learning rates or number of data in training, cross-validate or test sets.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:169:299292
Study programmeTitle: Petroleum engineering; specializations in: Petroleum engineering, Energy production and supply, Environmental protection in petroleum engineering
Course: Petroleum engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka naftnog rudarstva (magistar/magistra inženjer/inženjerka naftnog rudarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2017-03-21 13:16:54