FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3027753662> ?p ?o ?g. }

• W3027753662 abstract "Abstract Recent research has highlighted the impact mesoscale heterogeneity can have on larger‐scale multiphase fluid flow properties. However, currently, there is no consensus on how to quickly and reliably analyze coreflooding experimental data to gain insights into mesoscale capillary‐dominated flow behaviors and how rock petrophysical properties affect such behaviors. In this study, we combine a machine learning‐based clustering method with physics‐based hypothesis testing to analyze multistage steady‐state coreflooding experimental data. By examining five different sets of coreflooding data, we have found that under capillary‐dominated flow regimes, voxel‐level CO 2 saturation fields are much more heterogeneous as capillary equilibrium is approached. CO 2 saturation time series behaviors are distinctively different between high and low permeability voxels. However, the effect of mesoscale permeability greatly diminishes under viscous‐dominated flow regimes. By computing the maximum and optimal number of clusters on the CO 2 saturation time series data, we are able to differentiate between these two flow regimes. Through this analysis method, it is now also possible to identify regions within a sandstone core with capillary heterogeneity trapping behaviors. It is confirmed that capillary heterogeneity trapping indeed occurs upstream of capillary barriers. Furthermore, we have discovered a new type of capillary heterogeneity trapping—one that occurs within the capillary barrier itself, which can cause parts of the core to achieve residual CO 2 saturations much higher than expected based on existing models of residual gas trapping." @default.
• W3027753662 created "2020-05-29" @default.
• W3027753662 creator A5054164034 @default.
• W3027753662 creator A5084353576 @default.
• W3027753662 date "2020-08-01" @default.
• W3027753662 modified "2023-09-25" @default.
• W3027753662 title "Using Unsupervised Machine Learning to Characterize Capillary Flow and Residual Trapping" @default.
• W3027753662 cites W1490528368 @default.
• W3027753662 cites W1493454437 @default.
• W3027753662 cites W1507901999 @default.
• W3027753662 cites W1580868964 @default.
• W3027753662 cites W1593347402 @default.
• W3027753662 cites W1652711717 @default.
• W3027753662 cites W1752061138 @default.
• W3027753662 cites W1894414046 @default.
• W3027753662 cites W1964511994 @default.
• W3027753662 cites W1966113633 @default.
• W3027753662 cites W1968229119 @default.
• W3027753662 cites W1969231609 @default.
• W3027753662 cites W1977929385 @default.
• W3027753662 cites W1987376609 @default.
• W3027753662 cites W2000190907 @default.
• W3027753662 cites W2005634505 @default.
• W3027753662 cites W2007327444 @default.
• W3027753662 cites W2007674806 @default.
• W3027753662 cites W2012476307 @default.
• W3027753662 cites W2015228833 @default.
• W3027753662 cites W2016381774 @default.
• W3027753662 cites W2019941464 @default.
• W3027753662 cites W2023190378 @default.
• W3027753662 cites W2032002032 @default.
• W3027753662 cites W2039254261 @default.
• W3027753662 cites W2041567011 @default.
• W3027753662 cites W2042197911 @default.
• W3027753662 cites W2042577950 @default.
• W3027753662 cites W2046699786 @default.
• W3027753662 cites W2046769475 @default.
• W3027753662 cites W2048838189 @default.
• W3027753662 cites W2051224630 @default.
• W3027753662 cites W2060484648 @default.
• W3027753662 cites W2071327120 @default.
• W3027753662 cites W2083775573 @default.
• W3027753662 cites W2085155753 @default.
• W3027753662 cites W2090212789 @default.
• W3027753662 cites W2093118732 @default.
• W3027753662 cites W2097747115 @default.
• W3027753662 cites W2131554991 @default.
• W3027753662 cites W2156164149 @default.
• W3027753662 cites W2265722620 @default.
• W3027753662 cites W2283679507 @default.
• W3027753662 cites W2288485989 @default.
• W3027753662 cites W2473182300 @default.
• W3027753662 cites W2487770199 @default.
• W3027753662 cites W2564139954 @default.
• W3027753662 cites W2745809358 @default.
• W3027753662 cites W2782972996 @default.
• W3027753662 cites W2944059447 @default.
• W3027753662 cites W3027753662 @default.
• W3027753662 cites W4230422735 @default.
• W3027753662 cites W4251428492 @default.
• W3027753662 cites W4292865245 @default.
• W3027753662 cites W4301455501 @default.
• W3027753662 cites W576690711 @default.
• W3027753662 cites W616265438 @default.
• W3027753662 cites W88595087 @default.
• W3027753662 cites W970375936 @default.
• W3027753662 cites W982415275 @default.
• W3027753662 cites W2930011387 @default.
• W3027753662 doi "https://doi.org/10.1029/2020wr027473" @default.
• W3027753662 hasPublicationYear "2020" @default.
• W3027753662 type Work @default.
• W3027753662 sameAs 3027753662 @default.
• W3027753662 citedByCount "8" @default.
• W3027753662 countsByYear W30277536622020 @default.
• W3027753662 countsByYear W30277536622021 @default.
• W3027753662 countsByYear W30277536622023 @default.
• W3027753662 crossrefType "journal-article" @default.
• W3027753662 hasAuthorship W3027753662A5054164034 @default.
• W3027753662 hasAuthorship W3027753662A5084353576 @default.
• W3027753662 hasConcept C113378726 @default.
• W3027753662 hasConcept C11413529 @default.
• W3027753662 hasConcept C114614502 @default.
• W3027753662 hasConcept C121332964 @default.
• W3027753662 hasConcept C127313418 @default.
• W3027753662 hasConcept C153294291 @default.
• W3027753662 hasConcept C155512373 @default.
• W3027753662 hasConcept C187320778 @default.
• W3027753662 hasConcept C192562407 @default.
• W3027753662 hasConcept C196806460 @default.
• W3027753662 hasConcept C205649164 @default.
• W3027753662 hasConcept C2777924906 @default.
• W3027753662 hasConcept C2779379648 @default.
• W3027753662 hasConcept C28413391 @default.
• W3027753662 hasConcept C33923547 @default.
• W3027753662 hasConcept C38349280 @default.
• W3027753662 hasConcept C40382383 @default.
• W3027753662 hasConcept C41008148 @default.
• W3027753662 hasConcept C46293882 @default.
• W3027753662 hasConcept C57879066 @default.
• W3027753662 hasConcept C6648577 @default.

• next