Repository logo
Article

Multiscale evaluation of a thin-bed reservoir

creativeworkseries.issn2299-8004
dc.contributor.authorLis-Śledziona, Anita
dc.date.available2025-08-04T08:45:15Z
dc.date.issued2021
dc.description.abstractA thin-bed laminated shaly-sand reservoir of the Miocene formation was evaluated using two methods: high resolution microresistivity data from the XRMI tool and conventional well logs. Based on high resolution data, the Earth model of the reservoir was defined in a way that allowed the analyzed interval to be subdivided into thin layers of sandstones, mudstones, and claystones. Theoretical logs of gamma ray, bulk density, horizontal and vertical resistivity were calculated based on the forward modeling method to describe the petrophysical properties of individual beds and calculate the clay volume, porosity, and water saturation. The relationships amongst the contents of minerals were established based on the XRD data from the neighboring wells, hence, the high-resolution lithological model was evaluated. Predicted curves and estimated volumes of minerals were used as an input in multimineral solver and based on the assumed petrophysical model the input data were recalculated, reconstructed and compared with the predicted curves. The volumes of minerals and input curves were adjusted during several runs to minimalize the error between predicted and recalculated variables. Another approach was based on electrofacies modeling using unsupervised self-organizing maps. As an input, conventional well logs were used. Then, the evaluated facies model was used during forward modeling of the effective porosity, horizontal resistivity and water saturation. The obtained results were compared and, finally, the effective thickness of the reservoir was established based on the results from the two methods.en
dc.description.placeOfPublicationKraków
dc.description.versionwersja wydawnicza
dc.identifier.doihttp://dx.doi.org/10.7494/geol.2021.47.1.5
dc.identifier.eissn2353-0790
dc.identifier.issn2299-8004
dc.identifier.urihttps://repo.agh.edu.pl/handle/AGH/114123
dc.language.isoeng
dc.publisherWydawnictwa AGH
dc.relation.ispartofGeology, Geophysics & Environment
dc.rightsAttribution 4.0 International
dc.rights.accessotwarty dostęp
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/legalcode
dc.subjectthin bedsen
dc.subjecthigh resolution well logs predictionen
dc.subjecthorizontal resistivityen
dc.subjectunsupervised neural networken
dc.subjectself-organizing mapen
dc.subjectSOMen
dc.subjectelectrofaciesen
dc.subjectlow resistivity payen
dc.subjectcienkie warstwypl
dc.subjectopór powierzchniowypl
dc.subjectsieć neuronowa ANNpl
dc.subjectmapy samoorganizujące się(SOM)pl
dc.subjectelektrofacjepl
dc.titleMultiscale evaluation of a thin-bed reservoiren
dc.title.relatedGeology, Geophysics & Environmenten
dc.typeartykuł
dspace.entity.typePublication
publicationissue.issueNumberNo. 1
publicationissue.paginationpp. 5-20
publicationvolume.volumeNumberVol. 47
relation.isJournalIssueOfPublication2ed836b9-2120-4571-9c4c-e690d6585192
relation.isJournalIssueOfPublication.latestForDiscovery2ed836b9-2120-4571-9c4c-e690d6585192
relation.isJournalOfPublicationb0bafc1e-4fd1-4ff1-822c-c1a78e14c892

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
geol.2021.47.1.5.pdf
Size:
8.7 MB
Format:
Adobe Portable Document Format