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Geostatistical Analysis of permeability data

Georgousakis Konstantinos

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URIhttp://purl.tuc.gr/dl/dias/11EDA683-6B2F-4A68-A514-98260AE2043B-
Identifierhttps://doi.org/10.26233/heallink.tuc.67331-
Languageen-
Extent24.3 MBen
TitleGeostatistical Analysis of permeability dataen
CreatorGeorgousakis Konstantinosen
CreatorΓεωργουσακης Κωνσταντινοςel
Contributor [Thesis Supervisor]Christopoulos Dionysiosen
Contributor [Thesis Supervisor]Χριστοπουλος Διονυσιοςel
Contributor [Committee Member]Varotsis Nikolaosen
Contributor [Committee Member]Βαροτσης Νικολαοςel
Contributor [Committee Member]Gaganis Vasileiosen
Contributor [Committee Member]Γαγανης Βασιλειοςel
PublisherΠολυτεχνείο Κρήτηςel
PublisherTechnical University of Creteen
Academic UnitΠολυτεχνείο Κρήτης::Σχολή Μηχανικών Ορυκτών Πόρωνel
DescriptionThis dissertation is submitted for the degree of Master of Science.en
Content SummaryProperties such as porosity and permeability are of utmost significance in petroleum industry. They are important parameters for both reservoir engineering and reservoir modelling, since they constitute the basis upon which hydrocarbon reserves, as well as hydrocarbon flow characteristics are determined. For that reason, accurate estimation of these properties has been the subject of continuous studies. For the purposes of this thesis, the porosity and permeability data provided by the 10th SPE benchmark reservoir model were used. This model is part of the PUNQ Complex Model and is a highly heterogeneous model, consisting of two parts: A relatively permeable Tarbert formation on top and an Upper Ness formation at the bottom. The latter comprises of permeable anastomosed channels laid on a non–permeable background. The data were analysed using visualization, statistical and geostatistical techniques, in order to investigate the statistical properties and to subsequently quantify and evaluate their spatial correlation and variability. The exploratory analysis was carried out using classical statistics (e.g., histograms, statistical moments, distribution fitting and scatter plots). However, the main results were derived using geostatistical methods. Geostatistical analysis included the calculation of various variograms (i.e., directional, anisotropic, omnidirectional and 3D variograms), and their subsequent fitting with appropriate theoretical variogram models. In addition to this analysis, an upscaling of the reservoir model was performed by implementing the Simplified Renormalization method to both porosity and permeability data. Various conclusions were drawn from this project concerning the behaviour and spatial correlation of the reservoir, as well as the general implementation of the geostatistical methods. The most important outcome was the confirmation of the high heterogeneity and anisotropy characterizing the entire reservoir model. An equally significant observation was that results depend greatly on the number and locations of data included. More specifically, considering more data across the horizontal plane increases the interpretable information of variogram analysis, while considering more data along the vertical direction increases the variability. Finally, upscaling leads to coarse–grained versions of the reservoir model; such reduced dimensionality models should be further evaluated by means of subsequent flow simulation.en
Type of ItemΜεταπτυχιακή Διατριβήel
Type of ItemMaster Thesisen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2017-01-31-
Date of Publication2017-
SubjectTenth SPE en
SubjectUpscalingen
SubjectGeostatisticsen
SubjectPorosityen
SubjectPermeabilityen
Bibliographic CitationΚωνσταντίνος Γεωργουσάκης, "Geostatistical Analysis of permeability data", Μεταπτυχιακή Διατριβή, Σχολή Μηχανικών Ορυκτών Πόρων, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2017el
Bibliographic CitationKonstantinos Georgousakis, "Geostatistical Analysis of Permeability Data", Master Thesis, School of Mineral Resources Engineering, Technical University of Crete, Chania, Greece, 2017en

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