Matches in SemOpenAlex for { <https://semopenalex.org/work/W4323308548> ?p ?o ?g. }
Showing items 1 to 98 of
98
with 100 items per page.
- W4323308548 abstract "Abstract Geologic CO2 sequestration (GCS) is a promising engineering measure to reduce global greenhouse emissions. However, accurate detection of CO2 leakage locations from underground traps remains a challenging problem. This study proposes a workflow that combines Bayesian inversion and deep learning algorithms to detect the sites of CO2 leakage. There are four main steps in the workflow. Step 1: we identify the key uncertainty parameters. Here we mean the CO2 leakage location. Then we get the training set using Latin Hypercube Sampling (LHS) method and perform the high-fidelity simulation using CMG. Step 2: we train the surrogate model using the data set collected from the last step, in which the Bayesian optimization is used to tune the hyperparameters automatically. Step 3: we perform the Bayesian inversion to invert the CO2 leakage location, in which the surrogate serves as the forward model to reduce the computational expense. Step 4: we feed the inverted CO2 leakage location into the high-fidelity model to produce the pressure response. If the error between the pressure response between the surrogate and the high-fidelity model is small enough, the solution is accepted. Otherwise, the accuracy of the surrogate model and the convergence of the Bayesian inversion process are revisited. We validate this method using a synthetic model of CO2 injection. Results show that the proposed Bayesian inversion assisted by the deep learning algorithm can accurately detect the CO2 leakage location with narrow uncertainties. This approach provides an accurate and efficient way to detect CO2 leakage locations in real-time applications." @default.
- W4323308548 created "2023-03-07" @default.
- W4323308548 creator A5009325358 @default.
- W4323308548 creator A5009674104 @default.
- W4323308548 creator A5045839676 @default.
- W4323308548 creator A5067974945 @default.
- W4323308548 creator A5072179993 @default.
- W4323308548 creator A5084996089 @default.
- W4323308548 date "2023-03-07" @default.
- W4323308548 modified "2023-10-17" @default.
- W4323308548 title "Locating CO2 Leakage in Subsurface Traps Using Bayesian Inversion and Deep Learning" @default.
- W4323308548 cites W1654083295 @default.
- W4323308548 cites W1992268555 @default.
- W4323308548 cites W2036717564 @default.
- W4323308548 cites W2092773322 @default.
- W4323308548 cites W2126974166 @default.
- W4323308548 cites W2472318300 @default.
- W4323308548 cites W3157423656 @default.
- W4323308548 cites W4285212076 @default.
- W4323308548 doi "https://doi.org/10.2118/213522-ms" @default.
- W4323308548 hasPublicationYear "2023" @default.
- W4323308548 type Work @default.
- W4323308548 citedByCount "0" @default.
- W4323308548 crossrefType "proceedings-article" @default.
- W4323308548 hasAuthorship W4323308548A5009325358 @default.
- W4323308548 hasAuthorship W4323308548A5009674104 @default.
- W4323308548 hasAuthorship W4323308548A5045839676 @default.
- W4323308548 hasAuthorship W4323308548A5067974945 @default.
- W4323308548 hasAuthorship W4323308548A5072179993 @default.
- W4323308548 hasAuthorship W4323308548A5084996089 @default.
- W4323308548 hasConcept C105795698 @default.
- W4323308548 hasConcept C107673813 @default.
- W4323308548 hasConcept C109007969 @default.
- W4323308548 hasConcept C11413529 @default.
- W4323308548 hasConcept C119857082 @default.
- W4323308548 hasConcept C124101348 @default.
- W4323308548 hasConcept C127313418 @default.
- W4323308548 hasConcept C131675550 @default.
- W4323308548 hasConcept C139719470 @default.
- W4323308548 hasConcept C151730666 @default.
- W4323308548 hasConcept C154945302 @default.
- W4323308548 hasConcept C162324750 @default.
- W4323308548 hasConcept C177212765 @default.
- W4323308548 hasConcept C1893757 @default.
- W4323308548 hasConcept C19499675 @default.
- W4323308548 hasConcept C20820323 @default.
- W4323308548 hasConcept C2776459999 @default.
- W4323308548 hasConcept C2777042071 @default.
- W4323308548 hasConcept C2778049539 @default.
- W4323308548 hasConcept C2781395549 @default.
- W4323308548 hasConcept C32230216 @default.
- W4323308548 hasConcept C33923547 @default.
- W4323308548 hasConcept C41008148 @default.
- W4323308548 hasConcept C76155785 @default.
- W4323308548 hasConcept C77088390 @default.
- W4323308548 hasConcept C8642999 @default.
- W4323308548 hasConceptScore W4323308548C105795698 @default.
- W4323308548 hasConceptScore W4323308548C107673813 @default.
- W4323308548 hasConceptScore W4323308548C109007969 @default.
- W4323308548 hasConceptScore W4323308548C11413529 @default.
- W4323308548 hasConceptScore W4323308548C119857082 @default.
- W4323308548 hasConceptScore W4323308548C124101348 @default.
- W4323308548 hasConceptScore W4323308548C127313418 @default.
- W4323308548 hasConceptScore W4323308548C131675550 @default.
- W4323308548 hasConceptScore W4323308548C139719470 @default.
- W4323308548 hasConceptScore W4323308548C151730666 @default.
- W4323308548 hasConceptScore W4323308548C154945302 @default.
- W4323308548 hasConceptScore W4323308548C162324750 @default.
- W4323308548 hasConceptScore W4323308548C177212765 @default.
- W4323308548 hasConceptScore W4323308548C1893757 @default.
- W4323308548 hasConceptScore W4323308548C19499675 @default.
- W4323308548 hasConceptScore W4323308548C20820323 @default.
- W4323308548 hasConceptScore W4323308548C2776459999 @default.
- W4323308548 hasConceptScore W4323308548C2777042071 @default.
- W4323308548 hasConceptScore W4323308548C2778049539 @default.
- W4323308548 hasConceptScore W4323308548C2781395549 @default.
- W4323308548 hasConceptScore W4323308548C32230216 @default.
- W4323308548 hasConceptScore W4323308548C33923547 @default.
- W4323308548 hasConceptScore W4323308548C41008148 @default.
- W4323308548 hasConceptScore W4323308548C76155785 @default.
- W4323308548 hasConceptScore W4323308548C77088390 @default.
- W4323308548 hasConceptScore W4323308548C8642999 @default.
- W4323308548 hasLocation W43233085481 @default.
- W4323308548 hasOpenAccess W4323308548 @default.
- W4323308548 hasPrimaryLocation W43233085481 @default.
- W4323308548 hasRelatedWork W1990724965 @default.
- W4323308548 hasRelatedWork W2921683824 @default.
- W4323308548 hasRelatedWork W2966473332 @default.
- W4323308548 hasRelatedWork W3042131354 @default.
- W4323308548 hasRelatedWork W3128150010 @default.
- W4323308548 hasRelatedWork W3199608561 @default.
- W4323308548 hasRelatedWork W3201485852 @default.
- W4323308548 hasRelatedWork W4287118170 @default.
- W4323308548 hasRelatedWork W4287374055 @default.
- W4323308548 hasRelatedWork W4323308548 @default.
- W4323308548 isParatext "false" @default.
- W4323308548 isRetracted "false" @default.
- W4323308548 workType "article" @default.