FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4245555989> ?p ?o ?g. }

• W4245555989 endingPage "295" @default.
• W4245555989 startingPage "282" @default.
• W4245555989 abstract "Flexural-dipole sonic logging has been widely used as the primary method to measure formation shear slowness because it can be applied in both fast and slow formations and can resolve azimuthal anisotropy. The flexural-dipole waveforms are dispersive borehole-guided waves that are sensitive to borehole geometry, mud, and formation properties, and therefore the processing techniques need to honor the physical dispersive signatures to obtain an accurate estimation of shear slowness. Traditional processing techniques are based on either a model-dependent method, in which an isotropic model is used as a reference to compensate for the dispersion effect, or a model-independent method, which optimizes nonphysical parameters to fit a simplified model to the field dispersion data extracted in the slowness-frequency domain. Many methods often require inputs, such as mud slowness, frequency bandpass filter, or an initial guess of formation shear. Consequently, these methods often fail to interpret the dispersion signature properly when those inputs are inaccurate or when the waveform quality is poor due to downhole logging noises. The users must manually tune the processing parameters and/or choose different methods as a workaround, which causes extra time and effort to obtain the result, hence imposes a significant challenge for automating sonic shear processing. We developed a physics-driven, machine-learning-based method for enhancing the interpretation of borehole sonic dipole data for wireline logging in an openhole scenario. A synthetic database is generated from an anisotropic root-finding, mode-search routine and used to train a neural network model as an accurate and efficient proxy. This neural network model can be used for real-time sensitivity analysis and performing inversion to the measured sonic dipole dispersion data to estimate relevant model parameters with associated uncertainties. We introduce how this trained model can be used to enhance the labeling and extraction of the dipole dispersion mode. We developed a new method that outperforms previous model-dependent and model-independent approaches because the new method introduces a mechanism to constrain the solution with physics that also has the capability to incorporate more complicated physical dispersion signatures. This new method does not rely on a good initial guess on mud slowness and formation shear slowness, nor any tuning parameter. This leads to significant progress toward fully automated sonic interpretation. The algorithm has been tested on field data for challenging borehole and geological conditions." @default.
• W4245555989 created "2022-05-12" @default.
• W4245555989 creator A5087020613 @default.
• W4245555989 creator A5088973373 @default.
• W4245555989 date "2021-06-01" @default.
• W4245555989 modified "2023-10-12" @default.
• W4245555989 title "Machine-Learning-Enabled Automatic Sonic Shear Processing" @default.
• W4245555989 doi "https://doi.org/10.30632/pjv62n3-2021a3" @default.
• W4245555989 hasPublicationYear "2021" @default.
• W4245555989 type Work @default.
• W4245555989 citedByCount "1" @default.
• W4245555989 countsByYear W42455559892022 @default.
• W4245555989 crossrefType "journal-article" @default.
• W4245555989 hasAuthorship W4245555989A5087020613 @default.
• W4245555989 hasAuthorship W4245555989A5088973373 @default.
• W4245555989 hasConcept C11940443 @default.
• W4245555989 hasConcept C120665830 @default.
• W4245555989 hasConcept C121332964 @default.
• W4245555989 hasConcept C127313418 @default.
• W4245555989 hasConcept C150560799 @default.
• W4245555989 hasConcept C159737794 @default.
• W4245555989 hasConcept C161028810 @default.
• W4245555989 hasConcept C165205528 @default.
• W4245555989 hasConcept C187320778 @default.
• W4245555989 hasConcept C197424946 @default.
• W4245555989 hasConcept C24890656 @default.
• W4245555989 hasConcept C2777139213 @default.
• W4245555989 hasConcept C2993313656 @default.
• W4245555989 hasConcept C33556824 @default.
• W4245555989 hasConcept C41008148 @default.
• W4245555989 hasConcept C554190296 @default.
• W4245555989 hasConcept C76155785 @default.
• W4245555989 hasConceptScore W4245555989C11940443 @default.
• W4245555989 hasConceptScore W4245555989C120665830 @default.
• W4245555989 hasConceptScore W4245555989C121332964 @default.
• W4245555989 hasConceptScore W4245555989C127313418 @default.
• W4245555989 hasConceptScore W4245555989C150560799 @default.
• W4245555989 hasConceptScore W4245555989C159737794 @default.
• W4245555989 hasConceptScore W4245555989C161028810 @default.
• W4245555989 hasConceptScore W4245555989C165205528 @default.
• W4245555989 hasConceptScore W4245555989C187320778 @default.
• W4245555989 hasConceptScore W4245555989C197424946 @default.
• W4245555989 hasConceptScore W4245555989C24890656 @default.
• W4245555989 hasConceptScore W4245555989C2777139213 @default.
• W4245555989 hasConceptScore W4245555989C2993313656 @default.
• W4245555989 hasConceptScore W4245555989C33556824 @default.
• W4245555989 hasConceptScore W4245555989C41008148 @default.
• W4245555989 hasConceptScore W4245555989C554190296 @default.
• W4245555989 hasConceptScore W4245555989C76155785 @default.
• W4245555989 hasIssue "3" @default.
• W4245555989 hasLocation W42455559891 @default.
• W4245555989 hasOpenAccess W4245555989 @default.
• W4245555989 hasPrimaryLocation W42455559891 @default.
• W4245555989 hasRelatedWork W2003307536 @default.
• W4245555989 hasRelatedWork W2013758816 @default.
• W4245555989 hasRelatedWork W2032087968 @default.
• W4245555989 hasRelatedWork W2046181026 @default.
• W4245555989 hasRelatedWork W2128739370 @default.
• W4245555989 hasRelatedWork W2362084199 @default.
• W4245555989 hasRelatedWork W2589111251 @default.
• W4245555989 hasRelatedWork W3160493548 @default.
• W4245555989 hasRelatedWork W4285180745 @default.
• W4245555989 hasRelatedWork W4310359934 @default.
• W4245555989 hasVolume "62" @default.
• W4245555989 isParatext "false" @default.
• W4245555989 isRetracted "false" @default.
• W4245555989 workType "article" @default.