Matches in SemOpenAlex for { <https://semopenalex.org/work/W3202041025> ?p ?o ?g. }
Showing items 1 to 50 of
50
with 100 items per page.
- W3202041025 abstract "Summary Traditional porosity prediction methods usually adopt two consecutive steps including seismic inversion and petrophysical modelling to convert seismic data into porosity. Machine learning can take full advantage of available geophysical information to directly build the nonlinear mapping for predicting porosity from seismic data. To realize the one-step reservoir porosity estimation, we propose the semi-supervised recurrent neural networks (SSRNNs) based porosity modelling method. SSRNNs include an encoder subnet and a decoder subnet. The encoder simulates the generalized seismic inversion to convert the input post-stack seismic data into the predicted porosity, and the decoder acts as a forward model to make the predicted porosity can return to the generated seismic data and reduce resolution space. In addition, seismic data at the non-well positions are randomly selected in each iteration of SSRNNs to boost the lateral continuity of the predicted porosity result. Without the demand of some approximate assumptions and accurate elastic parameters, well logs and seismic data at well locations and non-well locations are integrated into SSRNNs to directly predict high-precision porosity from seismic data. A numerical model example and a real data example are used to verify the effectiveness and accuracy of the SSRNNs based reservoir lateral porosity prediction method." @default.
- W3202041025 created "2021-10-11" @default.
- W3202041025 creator A5008135736 @default.
- W3202041025 creator A5008601244 @default.
- W3202041025 creator A5025033760 @default.
- W3202041025 creator A5028047145 @default.
- W3202041025 creator A5081183312 @default.
- W3202041025 date "2021-01-01" @default.
- W3202041025 modified "2023-09-23" @default.
- W3202041025 title "Semi-supervised seismic data and well logs integration for reservoir lateral porosity prediction" @default.
- W3202041025 doi "https://doi.org/10.3997/2214-4609.202113181" @default.
- W3202041025 hasPublicationYear "2021" @default.
- W3202041025 type Work @default.
- W3202041025 sameAs 3202041025 @default.
- W3202041025 citedByCount "0" @default.
- W3202041025 crossrefType "proceedings-article" @default.
- W3202041025 hasAuthorship W3202041025A5008135736 @default.
- W3202041025 hasAuthorship W3202041025A5008601244 @default.
- W3202041025 hasAuthorship W3202041025A5025033760 @default.
- W3202041025 hasAuthorship W3202041025A5028047145 @default.
- W3202041025 hasAuthorship W3202041025A5081183312 @default.
- W3202041025 hasConcept C124101348 @default.
- W3202041025 hasConcept C127313418 @default.
- W3202041025 hasConcept C187320778 @default.
- W3202041025 hasConcept C41008148 @default.
- W3202041025 hasConcept C6648577 @default.
- W3202041025 hasConcept C72634772 @default.
- W3202041025 hasConceptScore W3202041025C124101348 @default.
- W3202041025 hasConceptScore W3202041025C127313418 @default.
- W3202041025 hasConceptScore W3202041025C187320778 @default.
- W3202041025 hasConceptScore W3202041025C41008148 @default.
- W3202041025 hasConceptScore W3202041025C6648577 @default.
- W3202041025 hasConceptScore W3202041025C72634772 @default.
- W3202041025 hasLocation W32020410251 @default.
- W3202041025 hasOpenAccess W3202041025 @default.
- W3202041025 hasPrimaryLocation W32020410251 @default.
- W3202041025 hasRelatedWork W2045034287 @default.
- W3202041025 hasRelatedWork W2061935911 @default.
- W3202041025 hasRelatedWork W2113855145 @default.
- W3202041025 hasRelatedWork W2150071508 @default.
- W3202041025 hasRelatedWork W2347219288 @default.
- W3202041025 hasRelatedWork W2366221835 @default.
- W3202041025 hasRelatedWork W2384234764 @default.
- W3202041025 hasRelatedWork W2387580419 @default.
- W3202041025 hasRelatedWork W2391544241 @default.
- W3202041025 hasRelatedWork W2896740510 @default.
- W3202041025 isParatext "false" @default.
- W3202041025 isRetracted "false" @default.
- W3202041025 magId "3202041025" @default.
- W3202041025 workType "article" @default.