FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2946560601> ?p ?o ?g. }

• W2946560601 endingPage "2910" @default.
• W2946560601 startingPage "2893" @default.
• W2946560601 abstract "Water alternating gas (WAG) injection process is a proven EOR technology that has been successfully deployed in many fields around the globe. The performance of WAG process is measured by its incremental recovery factor over secondary recovery. The application of this technology remains limited due to the complexity of the WAG injection process which requires time-consuming in-depth technical studies. This research was performed for a purpose of developing a predictive model for WAG incremental recovery factor based on integrated approach that involves reservoir simulation and data mining. A thousand reservoir simulation models were developed to evaluate WAG injection performance over waterflooding. Reservoir model parameters assessed in this research study were horizontal and vertical permeabilities, fluids properties, WAG injection scheme, fluids mobility, trapped gas saturation, reservoir pressure, residual oil saturation to gas, and injected gas volume. The outcome of the WAG simulation models was fed to the two selected data mining techniques, regression and group method of data handling (GMDH), to build WAG incremental recovery factor predictive model. Input data to the machine learning technique were split into two sets: 70% for training the model and 30% for model validation. Predictive models that calculate WAG incremental recovery factor as a function of the input parameters were developed. The predictive models correlation coefficient of 0.766 and 0.853 and root mean square error of 3.571 and 2.893 were achieved from regression and GMDH methods, respectively. GMDH technique demonstrated its strength and ability in selecting effective predictors, optimizing network structure, and achieving more accurate predictive model. The achieved WAG incremental recovery factor predictive models are expected to help reservoir engineers perform quick evaluation of WAG performance and assess a WAG project risk prior launching detailed time-consuming and costly technical studies." @default.
• W2946560601 created "2019-05-29" @default.
• W2946560601 creator A5006379329 @default.
• W2946560601 creator A5010375854 @default.
• W2946560601 creator A5054507847 @default.
• W2946560601 date "2019-05-20" @default.
• W2946560601 modified "2023-10-03" @default.
• W2946560601 title "Novel approach for predicting water alternating gas injection recovery factor" @default.
• W2946560601 cites W1975727361 @default.
• W2946560601 cites W1979688148 @default.
• W2946560601 cites W1988780598 @default.
• W2946560601 cites W1989813308 @default.
• W2946560601 cites W1999646019 @default.
• W2946560601 cites W2006131114 @default.
• W2946560601 cites W2016579760 @default.
• W2946560601 cites W2023696186 @default.
• W2946560601 cites W2024157002 @default.
• W2946560601 cites W2028060674 @default.
• W2946560601 cites W2029506923 @default.
• W2946560601 cites W2050914025 @default.
• W2946560601 cites W2052571383 @default.
• W2946560601 cites W2052693351 @default.
• W2946560601 cites W2075167552 @default.
• W2946560601 cites W2108172397 @default.
• W2946560601 cites W2275272754 @default.
• W2946560601 cites W2317396987 @default.
• W2946560601 cites W2321088635 @default.
• W2946560601 cites W2340330766 @default.
• W2946560601 cites W2468992649 @default.
• W2946560601 cites W2487770199 @default.
• W2946560601 cites W2519474534 @default.
• W2946560601 cites W2532380539 @default.
• W2946560601 cites W2589839874 @default.
• W2946560601 cites W2594367229 @default.
• W2946560601 cites W2749671105 @default.
• W2946560601 cites W2766541729 @default.
• W2946560601 cites W2775085403 @default.
• W2946560601 cites W2802159372 @default.
• W2946560601 cites W2885418228 @default.
• W2946560601 cites W4230737036 @default.
• W2946560601 cites W4244042888 @default.
• W2946560601 doi "https://doi.org/10.1007/s13202-019-0673-2" @default.
• W2946560601 hasPublicationYear "2019" @default.
• W2946560601 type Work @default.
• W2946560601 sameAs 2946560601 @default.
• W2946560601 citedByCount "12" @default.
• W2946560601 countsByYear W29465606012020 @default.
• W2946560601 countsByYear W29465606012021 @default.
• W2946560601 countsByYear W29465606012022 @default.
• W2946560601 countsByYear W29465606012023 @default.
• W2946560601 crossrefType "journal-article" @default.
• W2946560601 hasAuthorship W2946560601A5006379329 @default.
• W2946560601 hasAuthorship W2946560601A5010375854 @default.
• W2946560601 hasAuthorship W2946560601A5054507847 @default.
• W2946560601 hasBestOaLocation W29465606011 @default.
• W2946560601 hasConcept C11413529 @default.
• W2946560601 hasConcept C119857082 @default.
• W2946560601 hasConcept C124101348 @default.
• W2946560601 hasConcept C127413603 @default.
• W2946560601 hasConcept C13926793 @default.
• W2946560601 hasConcept C155512373 @default.
• W2946560601 hasConcept C2778668878 @default.
• W2946560601 hasConcept C2779681308 @default.
• W2946560601 hasConcept C2780092901 @default.
• W2946560601 hasConcept C41008148 @default.
• W2946560601 hasConcept C78762247 @default.
• W2946560601 hasConceptScore W2946560601C11413529 @default.
• W2946560601 hasConceptScore W2946560601C119857082 @default.
• W2946560601 hasConceptScore W2946560601C124101348 @default.
• W2946560601 hasConceptScore W2946560601C127413603 @default.
• W2946560601 hasConceptScore W2946560601C13926793 @default.
• W2946560601 hasConceptScore W2946560601C155512373 @default.
• W2946560601 hasConceptScore W2946560601C2778668878 @default.
• W2946560601 hasConceptScore W2946560601C2779681308 @default.
• W2946560601 hasConceptScore W2946560601C2780092901 @default.
• W2946560601 hasConceptScore W2946560601C41008148 @default.
• W2946560601 hasConceptScore W2946560601C78762247 @default.
• W2946560601 hasIssue "4" @default.
• W2946560601 hasLocation W29465606011 @default.
• W2946560601 hasOpenAccess W2946560601 @default.
• W2946560601 hasPrimaryLocation W29465606011 @default.
• W2946560601 hasRelatedWork W1994128058 @default.
• W2946560601 hasRelatedWork W2048360048 @default.
• W2946560601 hasRelatedWork W2066860326 @default.
• W2946560601 hasRelatedWork W2597765436 @default.
• W2946560601 hasRelatedWork W2760950287 @default.
• W2946560601 hasRelatedWork W2969358436 @default.
• W2946560601 hasRelatedWork W3002906244 @default.
• W2946560601 hasRelatedWork W4307663447 @default.
• W2946560601 hasRelatedWork W4311833219 @default.
• W2946560601 hasRelatedWork W4313573811 @default.
• W2946560601 hasVolume "9" @default.
• W2946560601 isParatext "false" @default.
• W2946560601 isRetracted "false" @default.
• W2946560601 magId "2946560601" @default.
• W2946560601 workType "article" @default.