FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4311895957> ?p ?o ?g. }

• W4311895957 endingPage "846" @default.
• W4311895957 startingPage "840" @default.
• W4311895957 abstract "Petrophysical inversion is an important aspect of reservoir modeling. However, due to the lack of a unique and straightforward relationship between seismic traces and rock properties, predicting petrophysical properties directly from seismic data is a complex task. Many studies have attempted to identify the direct end-to-end link using supervised machine learning techniques, but they face challenges such as lack of a large petrophysical training data set or estimates that may not conform with physics or depositional history of the rocks. We present a rock- and wave-physics-informed neural network (RW-PINN) model that can estimate porosity directly from seismic image traces with no wells or with a limited number of wells and with predictions that are consistent with rock physics and geologic knowledge of deposition. The RW-PINN takes advantage of auto-differentiation to compute the gradients across the rock- and wave-physics models. As an example, we use the uncemented-sand rock-physics model and normal-incidence wave physics to guide the learning of the RW-PINN to eventually get good estimates of porosities from normal-incidence seismic traces and limited well data. Training the RW-PINN with few wells (weakly supervised scenario) helps in tackling the problem of nonuniqueness as different porosity logs can give similar seismic traces. We use a weighted normalized root mean square error loss function to train the weakly supervised network and demonstrate the impact of different weights on porosity predictions. The RW-PINN's estimated porosities and seismic traces are compared to predictions from a completely supervised model, which gives slightly better porosity estimates but matches the seismic traces poorly and requires a large amount of labeled training data. We demonstrate the complete workflow for executing petrophysical inversion of seismic data using self-supervised or weakly supervised RW-PINNs." @default.
• W4311895957 created "2023-01-02" @default.
• W4311895957 creator A5013088513 @default.
• W4311895957 creator A5057998765 @default.
• W4311895957 date "2022-12-01" @default.
• W4311895957 modified "2023-09-28" @default.
• W4311895957 title "Direct estimation of porosity from seismic data using rock- and wave-physics-informed neural networks" @default.
• W4311895957 cites W1512208174 @default.
• W4311895957 cites W1538120041 @default.
• W4311895957 cites W1677182931 @default.
• W4311895957 cites W1997357068 @default.
• W4311895957 cites W1999647928 @default.
• W4311895957 cites W2026204455 @default.
• W4311895957 cites W2026492705 @default.
• W4311895957 cites W2030619630 @default.
• W4311895957 cites W2033280612 @default.
• W4311895957 cites W2041210248 @default.
• W4311895957 cites W2066375611 @default.
• W4311895957 cites W2074176021 @default.
• W4311895957 cites W2096990985 @default.
• W4311895957 cites W2102589063 @default.
• W4311895957 cites W2114735878 @default.
• W4311895957 cites W2123023966 @default.
• W4311895957 cites W2141708759 @default.
• W4311895957 cites W2151074885 @default.
• W4311895957 cites W2307550859 @default.
• W4311895957 cites W2592140522 @default.
• W4311895957 cites W2604304196 @default.
• W4311895957 cites W2789444873 @default.
• W4311895957 cites W2804203206 @default.
• W4311895957 cites W2947704004 @default.
• W4311895957 cites W2968094316 @default.
• W4311895957 cites W3032991056 @default.
• W4311895957 cites W3084211254 @default.
• W4311895957 cites W4211024465 @default.
• W4311895957 cites W4253970696 @default.
• W4311895957 cites W4256129314 @default.
• W4311895957 cites W4281812189 @default.
• W4311895957 cites W4283398272 @default.
• W4311895957 cites W4312608366 @default.
• W4311895957 doi "https://doi.org/10.1190/tle41120840.1" @default.
• W4311895957 hasPublicationYear "2022" @default.
• W4311895957 type Work @default.
• W4311895957 citedByCount "1" @default.
• W4311895957 countsByYear W43118959572023 @default.
• W4311895957 crossrefType "journal-article" @default.
• W4311895957 hasAuthorship W4311895957A5013088513 @default.
• W4311895957 hasAuthorship W4311895957A5057998765 @default.
• W4311895957 hasConcept C11413529 @default.
• W4311895957 hasConcept C127313418 @default.
• W4311895957 hasConcept C154945302 @default.
• W4311895957 hasConcept C159737794 @default.
• W4311895957 hasConcept C165205528 @default.
• W4311895957 hasConcept C187320778 @default.
• W4311895957 hasConcept C199289684 @default.
• W4311895957 hasConcept C2524010 @default.
• W4311895957 hasConcept C33923547 @default.
• W4311895957 hasConcept C35817400 @default.
• W4311895957 hasConcept C39267094 @default.
• W4311895957 hasConcept C41008148 @default.
• W4311895957 hasConcept C46293882 @default.
• W4311895957 hasConcept C50644808 @default.
• W4311895957 hasConcept C64370902 @default.
• W4311895957 hasConcept C6648577 @default.
• W4311895957 hasConcept C78542244 @default.
• W4311895957 hasConcept C8058405 @default.
• W4311895957 hasConceptScore W4311895957C11413529 @default.
• W4311895957 hasConceptScore W4311895957C127313418 @default.
• W4311895957 hasConceptScore W4311895957C154945302 @default.
• W4311895957 hasConceptScore W4311895957C159737794 @default.
• W4311895957 hasConceptScore W4311895957C165205528 @default.
• W4311895957 hasConceptScore W4311895957C187320778 @default.
• W4311895957 hasConceptScore W4311895957C199289684 @default.
• W4311895957 hasConceptScore W4311895957C2524010 @default.
• W4311895957 hasConceptScore W4311895957C33923547 @default.
• W4311895957 hasConceptScore W4311895957C35817400 @default.
• W4311895957 hasConceptScore W4311895957C39267094 @default.
• W4311895957 hasConceptScore W4311895957C41008148 @default.
• W4311895957 hasConceptScore W4311895957C46293882 @default.
• W4311895957 hasConceptScore W4311895957C50644808 @default.
• W4311895957 hasConceptScore W4311895957C64370902 @default.
• W4311895957 hasConceptScore W4311895957C6648577 @default.
• W4311895957 hasConceptScore W4311895957C78542244 @default.
• W4311895957 hasConceptScore W4311895957C8058405 @default.
• W4311895957 hasIssue "12" @default.
• W4311895957 hasLocation W43118959571 @default.
• W4311895957 hasOpenAccess W4311895957 @default.
• W4311895957 hasPrimaryLocation W43118959571 @default.
• W4311895957 hasRelatedWork W123647398 @default.
• W4311895957 hasRelatedWork W1963705337 @default.
• W4311895957 hasRelatedWork W1990108033 @default.
• W4311895957 hasRelatedWork W2030909681 @default.
• W4311895957 hasRelatedWork W2139345627 @default.
• W4311895957 hasRelatedWork W2159054789 @default.
• W4311895957 hasRelatedWork W2333972267 @default.
• W4311895957 hasRelatedWork W2749055182 @default.
• W4311895957 hasRelatedWork W3215723174 @default.
• W4311895957 hasRelatedWork W1753523577 @default.

• next