Matches in SemOpenAlex for { <https://semopenalex.org/work/W2340950140> ?p ?o ?g. }
Showing items 1 to 77 of
77
with 100 items per page.
- W2340950140 abstract "Abstract An integrated multivariate statistics procedure was adopted for the accurate Lithofacies classification prediction to be incorporated with well log attributes into core permeability modeling. Logistic Boosting Regression and Generalized Linear Modeling were adopted for Lithofacies Classification and core permeability estimation, respectively. Logistic Boosting Regression (LogitBoost) was used to model the lithofacies sequences given well log and core data to predict the discrete lithofacies distribution at missing intervals. In this paper, the permeability modeling and estimation was validated through bootstrapping and cross-validation. The well log interpretations that were considered for lithofacies classification and permeability modelling are neutron porosity, shale volume, and water saturation as a function of depth. The measured discrete lithofacies types include three main lithology types: sand, shaly sand, and shale. LogitBoost was adopted for modelling and prediction the discrete Lithofacies distribution for the entire reservoir depth that was then incorporated into permeability modelling. Next, GLM was applied to create the relationship between core permeability and the explanatory variables of well log and Lithofacies. In GLM results, the accuracy of the entire permeability modelling was assessed by K-fold cross-validation that showed significant reduction in prediction variance. GLM has also led to overcome the multicollinearity that was available between shale volume and water saturation. Bootstrapping was then adopted, as an approval tool to ensure that there is no doubt about the validity and accuracy of the fitted GLM model. Bootstrapping simply re-samples the data into a specific number of times and recalculates the variable given each sample. The bootstrapping was implemented for Adjusted R-squared of the overall GLM approach." @default.
- W2340950140 created "2016-06-24" @default.
- W2340950140 creator A5027047123 @default.
- W2340950140 date "2016-05-05" @default.
- W2340950140 modified "2023-09-30" @default.
- W2340950140 title "Incorporation of Bootstrapping and Cross-Validation for Efficient Multivariate Facies and Petrophysical Modeling" @default.
- W2340950140 cites W1989499882 @default.
- W2340950140 cites W1996877265 @default.
- W2340950140 cites W2016680212 @default.
- W2340950140 cites W2024046085 @default.
- W2340950140 cites W2034303231 @default.
- W2340950140 cites W2085014703 @default.
- W2340950140 cites W2090525252 @default.
- W2340950140 cites W2118845193 @default.
- W2340950140 cites W2310882183 @default.
- W2340950140 cites W2328495118 @default.
- W2340950140 cites W2330062918 @default.
- W2340950140 cites W2333431616 @default.
- W2340950140 cites W3106889297 @default.
- W2340950140 cites W4300515633 @default.
- W2340950140 cites W1968763486 @default.
- W2340950140 doi "https://doi.org/10.2118/180277-ms" @default.
- W2340950140 hasPublicationYear "2016" @default.
- W2340950140 type Work @default.
- W2340950140 sameAs 2340950140 @default.
- W2340950140 citedByCount "13" @default.
- W2340950140 countsByYear W23409501402018 @default.
- W2340950140 countsByYear W23409501402021 @default.
- W2340950140 countsByYear W23409501402022 @default.
- W2340950140 countsByYear W23409501402023 @default.
- W2340950140 crossrefType "proceedings-article" @default.
- W2340950140 hasAuthorship W2340950140A5027047123 @default.
- W2340950140 hasConcept C105795698 @default.
- W2340950140 hasConcept C11413529 @default.
- W2340950140 hasConcept C127313418 @default.
- W2340950140 hasConcept C149782125 @default.
- W2340950140 hasConcept C154945302 @default.
- W2340950140 hasConcept C159390177 @default.
- W2340950140 hasConcept C161584116 @default.
- W2340950140 hasConcept C187320778 @default.
- W2340950140 hasConcept C199163554 @default.
- W2340950140 hasConcept C207609745 @default.
- W2340950140 hasConcept C33923547 @default.
- W2340950140 hasConcept C41008148 @default.
- W2340950140 hasConcept C46293882 @default.
- W2340950140 hasConcept C6648577 @default.
- W2340950140 hasConceptScore W2340950140C105795698 @default.
- W2340950140 hasConceptScore W2340950140C11413529 @default.
- W2340950140 hasConceptScore W2340950140C127313418 @default.
- W2340950140 hasConceptScore W2340950140C149782125 @default.
- W2340950140 hasConceptScore W2340950140C154945302 @default.
- W2340950140 hasConceptScore W2340950140C159390177 @default.
- W2340950140 hasConceptScore W2340950140C161584116 @default.
- W2340950140 hasConceptScore W2340950140C187320778 @default.
- W2340950140 hasConceptScore W2340950140C199163554 @default.
- W2340950140 hasConceptScore W2340950140C207609745 @default.
- W2340950140 hasConceptScore W2340950140C33923547 @default.
- W2340950140 hasConceptScore W2340950140C41008148 @default.
- W2340950140 hasConceptScore W2340950140C46293882 @default.
- W2340950140 hasConceptScore W2340950140C6648577 @default.
- W2340950140 hasLocation W23409501401 @default.
- W2340950140 hasOpenAccess W2340950140 @default.
- W2340950140 hasPrimaryLocation W23409501401 @default.
- W2340950140 hasRelatedWork W2053542176 @default.
- W2340950140 hasRelatedWork W2089610442 @default.
- W2340950140 hasRelatedWork W2267219236 @default.
- W2340950140 hasRelatedWork W2622157825 @default.
- W2340950140 hasRelatedWork W2885793850 @default.
- W2340950140 hasRelatedWork W4220961233 @default.
- W2340950140 hasRelatedWork W4242062841 @default.
- W2340950140 hasRelatedWork W4255876030 @default.
- W2340950140 hasRelatedWork W4255920913 @default.
- W2340950140 hasRelatedWork W4307730820 @default.
- W2340950140 isParatext "false" @default.
- W2340950140 isRetracted "false" @default.
- W2340950140 magId "2340950140" @default.
- W2340950140 workType "article" @default.