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Analyzing and forecasting the performance of water drive gas reservoirs

creativeworkseries.issn2299-4157
dc.contributor.authorLupu, Diana Andreea
dc.contributor.authorŞtefănescu, Dan-Paul
dc.contributor.authorFoidaş, Ion
dc.date.available2024-11-26T13:39:55Z
dc.date.issued2019
dc.descriptionBibliogr. s. [159].
dc.description.abstractThe manner of estimating water drive gas reservoir recovery can vary considerably. Several mathematical models have been developed for estimating water influx in petroleum industry, but the current paper will address the application of Fetkovich aquifer model to predict the gas reservoir performance considering the pressure changes that gradually occur within the aquifer and between the aquifer and reservoir. The applicability of this model has proven to be extremely useful in estimation of initial gas resources, aquifer volume and its parameters, confirming the producing mechanism but also forecasting the production performance of the gas reservoir. The authors will highlight through some case studies, the importance of the water influx analysis and prediction, in particular for natural gas reservoirs, which subsequently allows for adequate planning in optimizing the reserves' recovery.en
dc.description.placeOfPublicationKraków
dc.description.versionwersja wydawnicza
dc.identifier.doihttps://doi.org/10.7494/drill.2019.36.1.143
dc.identifier.issn2300-7052
dc.identifier.urihttps://repo.agh.edu.pl/handle/AGH/110307
dc.language.isoeng
dc.publisherWydawnictwa AGH
dc.relation.ispartofAGH Drilling, Oil, Gas
dc.rightsAGH Licence - Fair Use
dc.rights.accessotwarty dostęp
dc.rights.urihttps://repo.agh.edu.pl/info/fair-use
dc.subjectnatural gas reservoirsen
dc.subjectrecovery factoren
dc.subjectwater drive mechanismen
dc.subjectFetkovich aquifer modelen
dc.subjectperformance predictionen
dc.titleAnalyzing and forecasting the performance of water drive gas reservoirsen
dc.title.relatedAGH Drilling, Oil, Gasen
dc.typeartykuł
dspace.entity.typePublication
publicationissue.issueNumberNo. 1
publicationissue.paginationpp. 143-158, [1]
publicationvolume.volumeNumberVol. 36
relation.isJournalIssueOfPublication6eede8dc-dfe2-4760-996c-da1510f41d57
relation.isJournalIssueOfPublication.latestForDiscovery6eede8dc-dfe2-4760-996c-da1510f41d57
relation.isJournalOfPublicationd59ea52a-1306-4ec1-ae8c-7c2d545cf0f7

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