Littérature scientifique sur le sujet « Multiphysical inversion »
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Articles de revues sur le sujet "Multiphysical inversion"
Zheng, Yi-kang, Chong Wang, Hao-hong Liang, Yi-bo Wang et Rong-shu Zeng. « 3D seismic forward modeling from the multiphysical inversion at the Ketzin CO2 storage site ». Applied Geophysics 21, no 3 (septembre 2024) : 593–605. http://dx.doi.org/10.1007/s11770-024-1132-5.
Texte intégralAl-Yasiri, Zainab Riyadh Shaker, Hayder Majid Mutashar, Klaus Gürlebeck et Tom Lahmer. « Damage Sensitive Signals for the Assessment of the Conditions of Wind Turbine Rotor Blades Using Electromagnetic Waves ». Infrastructures 7, no 8 (12 août 2022) : 104. http://dx.doi.org/10.3390/infrastructures7080104.
Texte intégralColombo, Daniele, Diego Rovetta et Ersan Turkoglu. « CSEM-regularized seismic velocity inversion : A multiscale, hierarchical workflow for subsalt imaging ». GEOPHYSICS 83, no 5 (1 septembre 2018) : B241—B252. http://dx.doi.org/10.1190/geo2017-0454.1.
Texte intégralSun, Jiajia, Daniele Colombo, Yaoguo Li et Jeffrey Shragge. « Geophysics introduces new section on multiphysics and joint inversion ». Leading Edge 39, no 10 (octobre 2020) : 753–54. http://dx.doi.org/10.1190/tle39100753.1.
Texte intégralGao, Guozhong, Aria Abubakar et Tarek M. Habashy. « Joint petrophysical inversion of electromagnetic and full-waveform seismic data ». GEOPHYSICS 77, no 3 (1 mai 2012) : WA3—WA18. http://dx.doi.org/10.1190/geo2011-0157.1.
Texte intégralLouboutin, Mathias, Ziyi Yin, Rafael Orozco, Thomas J. Grady, Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte, Olav Møyner, Gerard J. Gorman et Felix J. Herrmann. « Learned multiphysics inversion with differentiable programming and machine learning ». Leading Edge 42, no 7 (juillet 2023) : 474–86. http://dx.doi.org/10.1190/tle42070474.1.
Texte intégralTu, Xiaolei, et Michael S. Zhdanov. « Joint Gramian inversion of geophysical data with different resolution capabilities : case study in Yellowstone ». Geophysical Journal International 226, no 2 (5 avril 2021) : 1058–85. http://dx.doi.org/10.1093/gji/ggab131.
Texte intégralColombo, Daniele, Diego Rovetta, Taqi Al-Yousuf, Ernesto Sandoval, Ersan Turkoglu et Gary McNeice. « Multiple joint wavefield inversions : Theory and field data implementations ». Leading Edge 39, no 6 (juin 2020) : 411–21. http://dx.doi.org/10.1190/tle39060411.1.
Texte intégralZhdanov, Michael S., Michael Jorgensen et Leif Cox. « Advanced Methods of Joint Inversion of Multiphysics Data for Mineral Exploration ». Geosciences 11, no 6 (21 juin 2021) : 262. http://dx.doi.org/10.3390/geosciences11060262.
Texte intégralWu, Pingping, Handong Tan, Changhong Lin, Miao Peng, Huan Ma et Zhengwen Yan. « Joint inversion of two-dimensional magnetotelluric and surface wave dispersion data with cross-gradient constraints ». Geophysical Journal International 221, no 2 (25 janvier 2020) : 938–50. http://dx.doi.org/10.1093/gji/ggaa045.
Texte intégralThèses sur le sujet "Multiphysical inversion"
Varignier, Geoffrey. « Construction de fonctions de sensibilité spatiales et prédictions rapides de diagraphies nucléaires en environnement de puits tubés ». Electronic Thesis or Diss., Université Grenoble Alpes, 2024. http://www.theses.fr/2024GRALY026.
Texte intégralIn petroleum wells, many tools operating on different physical principles are commonly used for data acquisition. This thesis focuses on actives nuclear logging probes involving a neutron or a gamma source. They are used in the oil industry to characterize the well geology and have been initially developed to realize quantitative measurements in open hole conditions where the probe is directly in contact with the rock formation. Once the petroleum well is drilled, a steel casing is installed and cemented, the probes are then no longer in contact with the rock formation and the measurements are considered qualitative due to the complexity of the geometry and the signal attenuation.With the hydrocarbon resources rarefaction, the number of explorations projects decease each year. Petroleum companies have more and more mature wells whose production capacities must be maintained and others at the end of their life which must be abandoned. Those phases require systematically logging measurements. The quantity of logs in cased-hole configuration tends to increase a lot and it becomes necessary to improve their interpretation.The industrial problematic is to characterize quantitatively, in a filed with strong radial heterogeneity, all the components the well (e.g. the fluids, the casing, the cement) and not just the rock reservoir parameters. The approach developed in the thesis is based on the concept of sensitivity function of nuclear logging probes, which represents the 3D dependency of the measurement to the model elements and are obtained by Monte-Carlo simulation. Due to the large number of unknowns, a multiphysical inversion considering the all the measurements of the different nuclear probes (porosity by neutron diffusion, density by gamma diffusion, lithology by neutron-gamma activation) is essential.The first part of the thesis allowed to compare the Monte-Carlo particles transport codes GEANT4 and MCNP for Geosciences applications. Results show a very good agreement for the gamma-gamma physics and a good agreement for the neutron-neutron physics but significant discrepancies for the neutron-gamma physics where MCNP seems to be more relevant.The second part of the thesis allowed to experimental validate Monte-Carlo simulations and to design a sensitivity function computation method specific for the cased-hole configuration. The validation is a comparison between the experimental sensitivity functions measured in calibration center and the numerical sensitivity functions computed using two different methods, the first one based on spatial importances estimated with MCNP and the second one based on interaction locations obtained with GEANT4. The results show good experimental agreement between the measured and calculated radial and axial sensitivity profiles, which validates the concept of sensitivity function with a preference for the interaction locations method which presents greater radial contrast between the different components of the well.The third part of the thesis consisted of making the geological interpretation of a reservoir zone of a cased hole well with sensitivity functions. The neutron-gamma and porosity logs predicted using the sensitivity functions are compared to the measured logs. An optimal earth model is obtained by iteration, showing a good capacity of the fast forward modeling algorithums to quantitatively reproduce the logs in cased-hole configuration providing that a relevant calibration is apply
Livres sur le sujet "Multiphysical inversion"
Zhdanov, Michael S. Advanced Methods of Joint Inversion and Fusion of Multiphysics Data. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6722-3.
Texte intégralZhdanov, Michael. Advanced Methods of Joint Inversion and Fusion of Multiphysics Data. Springer, 2023.
Trouver le texte intégralChapitres de livres sur le sujet "Multiphysical inversion"
Zhdanov, Michael S. « Joint Focusing Inversion of Multiphysics Data ». Dans Advanced Methods of Joint Inversion and Fusion of Multiphysics Data, 193–213. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6722-3_10.
Texte intégralZhdanov, Michael S. « Machine Learning Inversion of Multiphysics Data ». Dans Advanced Methods of Joint Inversion and Fusion of Multiphysics Data, 305–15. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6722-3_16.
Texte intégralZhdanov, Michael S. « Introduction to Inversion Theory ». Dans Advanced Methods of Joint Inversion and Fusion of Multiphysics Data, 3–12. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6722-3_1.
Texte intégralZhdanov, Michael S. « Joint Minimum Entropy Inversion ». Dans Advanced Methods of Joint Inversion and Fusion of Multiphysics Data, 215–24. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6722-3_11.
Texte intégralZhdanov, Michael S. « Probabilistic Approach to Gramian Inversion ». Dans Advanced Methods of Joint Inversion and Fusion of Multiphysics Data, 245–58. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6722-3_13.
Texte intégralZhdanov, Michael S. « Joint Inversion Based on Structural Similarities ». Dans Advanced Methods of Joint Inversion and Fusion of Multiphysics Data, 177–92. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6722-3_9.
Texte intégralZhdanov, Michael S. « Gradient-Type Methods of Nonlinear Inversion ». Dans Advanced Methods of Joint Inversion and Fusion of Multiphysics Data, 129–59. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6722-3_7.
Texte intégralZhdanov, Michael S. « Gramian Method of Generalized Joint Inversion ». Dans Advanced Methods of Joint Inversion and Fusion of Multiphysics Data, 225–43. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6722-3_12.
Texte intégralZhdanov, Michael S. « Simultaneous Processing and Fusion of Multiphysics Data and Images ». Dans Advanced Methods of Joint Inversion and Fusion of Multiphysics Data, 259–74. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6722-3_14.
Texte intégralZhdanov, Michael. « Modeling and Inversion of Potential Field Data ». Dans Advanced Methods of Joint Inversion and Fusion of Multiphysics Data, 319–37. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6722-3_17.
Texte intégralActes de conférences sur le sujet "Multiphysical inversion"
Feng, Shihang, Peng Jin, Xitong Zhang, Yinpeng Chen, David Alumbaugh, Michael Commer et Youzuo Lin. « Extremely weak supervision inversion of multiphysical properties ». Dans Second International Meeting for Applied Geoscience & Energy. Society of Exploration Geophysicists and American Association of Petroleum Geologists, 2022. http://dx.doi.org/10.1190/image2022-3746487.1.
Texte intégralHallinan, Stephen, Wolfgang Soyer, Randall Mackie, Carsten Scholl et Federico Miorelli. « Geologically Consistent Multiphysics Inversion ». Dans International Petroleum Technology Conference. IPTC, 2022. http://dx.doi.org/10.2523/iptc-21936-ea.
Texte intégralHu, Yanyan, Xiaolong Wei, Xuqing Wu, Jiajia Sun, Jiefu Chen, Jiuping Chen et Yueqing Huang. « Deep learning-enhanced multiphysics joint inversion ». Dans First International Meeting for Applied Geoscience & Energy. Society of Exploration Geophysicists, 2021. http://dx.doi.org/10.1190/segam2021-3583667.1.
Texte intégralMolodtsov, Dmitry, et Vladimir Troyan. « Multiphysics joint inversion through joint sparsity regularization ». Dans SEG Technical Program Expanded Abstracts 2017. Society of Exploration Geophysicists, 2017. http://dx.doi.org/10.1190/segam2017-17792589.1.
Texte intégralHu, Yanyan, Jiefu Chen, Xuqing Wu et Yueqin Huang. « Multiphysics Joint Inversion Using Successive Deep Perceptual Constraints ». Dans 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/USNC-URSI). IEEE, 2022. http://dx.doi.org/10.1109/ap-s/usnc-ursi47032.2022.9887246.
Texte intégralCeci, F., et A. Battaglini. « Reducing geothermal exploration uncertainty via multiphysics joint inversion ». Dans 2nd Geoscience & Engineering in Energy Transition Conference. European Association of Geoscientists & Engineers, 2021. http://dx.doi.org/10.3997/2214-4609.202121025.
Texte intégralShahin, A., M. Myers et L. Hathon. « Deciphering Dual Porosity Carbonates Using Multiphysics Modeling and Inversion ». Dans Third EAGE WIPIC Workshop : Reservoir Management in Carbonates. European Association of Geoscientists & Engineers, 2019. http://dx.doi.org/10.3997/2214-4609.201903112.
Texte intégralHu, Yanyan, Jiefu Chen, Xuqing Wu et Yueqin Huang. « Deep Learning Enhanced Joint Inversion of Multiphysics Data with Nonconforming Discretization ». Dans 2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (APS/URSI). IEEE, 2021. http://dx.doi.org/10.1109/aps/ursi47566.2021.9703802.
Texte intégralChikhaoui, Zeineb, Julien Gomand, François Malburet et Pierre-Jean Barre. « Complementary Use of BG and EMR Formalisms for Multiphysics Systems Analysis and Control ». Dans ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/esda2012-82318.
Texte intégralDomenzain, Diego, John Bradford et Jodi Mead. « Multiphysics joint inversion of field FWI-GPR and ER surface acquired data ». Dans First International Meeting for Applied Geoscience & Energy. Society of Exploration Geophysicists, 2021. http://dx.doi.org/10.1190/segam2021-3576479.1.
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