Matches in SemOpenAlex for { <https://semopenalex.org/work/W3120334342> ?p ?o ?g. }
Showing items 1 to 98 of
98
with 100 items per page.
- W3120334342 endingPage "V196" @default.
- W3120334342 startingPage "V185" @default.
- W3120334342 abstract "It is well known that source deghosting can best be applied to common-receiver gathers, whereas receiver deghosting can best be applied to common-shot records. The source-ghost wavefield observed in the common-shot domain contains the imprint of the subsurface, which complicates source deghosting in the common-shot domain, in particular when the subsurface is complex. Unfortunately, the alternative, that is, the common-receiver domain, is often coarsely sampled, which complicates source deghosting in this domain as well. To solve the latter issue, we have trained a convolutional neural network to apply source deghosting in this domain. We subsample all shot records with and without the receiver-ghost wavefield to obtain the training data. Due to reciprocity, these training data are a representative data set for source deghosting in the coarse common-receiver domain. We validate the machine-learning approach on simulated data and on field data. The machine-learning approach gives a significant uplift to the simulated data compared to conventional source deghosting. The field-data results confirm that the proposed machine-learning approach can remove the source-ghost wavefield from the coarsely sampled common-receiver gathers." @default.
- W3120334342 created "2021-01-18" @default.
- W3120334342 creator A5007473838 @default.
- W3120334342 creator A5063680863 @default.
- W3120334342 date "2021-03-11" @default.
- W3120334342 modified "2023-10-16" @default.
- W3120334342 title "Source deghosting of coarsely sampled common-receiver data using a convolutional neural network" @default.
- W3120334342 cites W1490069092 @default.
- W3120334342 cites W1901129140 @default.
- W3120334342 cites W1969225718 @default.
- W3120334342 cites W2024829194 @default.
- W3120334342 cites W2035374127 @default.
- W3120334342 cites W2052971568 @default.
- W3120334342 cites W2053376610 @default.
- W3120334342 cites W2077327649 @default.
- W3120334342 cites W2082202949 @default.
- W3120334342 cites W2137324082 @default.
- W3120334342 cites W2152398027 @default.
- W3120334342 cites W2313207773 @default.
- W3120334342 cites W2326190888 @default.
- W3120334342 cites W2510189879 @default.
- W3120334342 cites W2524954458 @default.
- W3120334342 cites W2592517375 @default.
- W3120334342 cites W2601307685 @default.
- W3120334342 cites W2620364597 @default.
- W3120334342 cites W2745439097 @default.
- W3120334342 cites W2749171740 @default.
- W3120334342 cites W2755708472 @default.
- W3120334342 cites W2769717799 @default.
- W3120334342 cites W2776585113 @default.
- W3120334342 cites W2806786936 @default.
- W3120334342 cites W2891510963 @default.
- W3120334342 cites W2891932361 @default.
- W3120334342 cites W2891968093 @default.
- W3120334342 cites W2900512821 @default.
- W3120334342 cites W2923484039 @default.
- W3120334342 cites W2966965831 @default.
- W3120334342 cites W2968094316 @default.
- W3120334342 cites W2968967238 @default.
- W3120334342 cites W2971840196 @default.
- W3120334342 cites W2972685163 @default.
- W3120334342 cites W2984603160 @default.
- W3120334342 cites W3025154588 @default.
- W3120334342 cites W4230607828 @default.
- W3120334342 doi "https://doi.org/10.1190/geo2020-0186.1" @default.
- W3120334342 hasPublicationYear "2021" @default.
- W3120334342 type Work @default.
- W3120334342 sameAs 3120334342 @default.
- W3120334342 citedByCount "7" @default.
- W3120334342 countsByYear W31203343422021 @default.
- W3120334342 countsByYear W31203343422022 @default.
- W3120334342 countsByYear W31203343422023 @default.
- W3120334342 crossrefType "journal-article" @default.
- W3120334342 hasAuthorship W3120334342A5007473838 @default.
- W3120334342 hasAuthorship W3120334342A5063680863 @default.
- W3120334342 hasBestOaLocation W31203343422 @default.
- W3120334342 hasConcept C134306372 @default.
- W3120334342 hasConcept C153180895 @default.
- W3120334342 hasConcept C154945302 @default.
- W3120334342 hasConcept C202444582 @default.
- W3120334342 hasConcept C33923547 @default.
- W3120334342 hasConcept C36503486 @default.
- W3120334342 hasConcept C41008148 @default.
- W3120334342 hasConcept C58489278 @default.
- W3120334342 hasConcept C81363708 @default.
- W3120334342 hasConcept C9652623 @default.
- W3120334342 hasConceptScore W3120334342C134306372 @default.
- W3120334342 hasConceptScore W3120334342C153180895 @default.
- W3120334342 hasConceptScore W3120334342C154945302 @default.
- W3120334342 hasConceptScore W3120334342C202444582 @default.
- W3120334342 hasConceptScore W3120334342C33923547 @default.
- W3120334342 hasConceptScore W3120334342C36503486 @default.
- W3120334342 hasConceptScore W3120334342C41008148 @default.
- W3120334342 hasConceptScore W3120334342C58489278 @default.
- W3120334342 hasConceptScore W3120334342C81363708 @default.
- W3120334342 hasConceptScore W3120334342C9652623 @default.
- W3120334342 hasIssue "3" @default.
- W3120334342 hasLocation W31203343421 @default.
- W3120334342 hasLocation W31203343422 @default.
- W3120334342 hasOpenAccess W3120334342 @default.
- W3120334342 hasPrimaryLocation W31203343421 @default.
- W3120334342 hasRelatedWork W2175746458 @default.
- W3120334342 hasRelatedWork W2732542196 @default.
- W3120334342 hasRelatedWork W2738221750 @default.
- W3120334342 hasRelatedWork W2760085659 @default.
- W3120334342 hasRelatedWork W2767651786 @default.
- W3120334342 hasRelatedWork W2883200793 @default.
- W3120334342 hasRelatedWork W2912288872 @default.
- W3120334342 hasRelatedWork W2940661641 @default.
- W3120334342 hasRelatedWork W3012978760 @default.
- W3120334342 hasRelatedWork W3093612317 @default.
- W3120334342 hasVolume "86" @default.
- W3120334342 isParatext "false" @default.
- W3120334342 isRetracted "false" @default.
- W3120334342 magId "3120334342" @default.
- W3120334342 workType "article" @default.