A novel methodology for hydrocarbon depth prediction in seabed logging: Gaussian process-based inverse modeling of electromagnetic data
Seabed logging (SBL) is an application of electromagnetic (EM) waves for detecting potential marine hydrocarbon-saturated reservoirs reliant on a source-receiver system. One of the concerns in modeling and inversion of the EM data is associated with the need for realistic representation of complex g...
محفوظ في:
المؤلفون الرئيسيون: | Daud, H., Mohd Aris, M.N., Mohd Noh, K.A., Dass, S.C. |
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التنسيق: | مقال |
منشور في: |
MDPI AG
2021
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الوصول للمادة أونلاين: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100842547&doi=10.3390%2fapp11041492&partnerID=40&md5=c3c8adda9b88afe635a490c91d1c5151 http://eprints.utp.edu.my/23787/ |
الوسوم: |
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مواد مشابهة
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Multivariate Gaussian Process Regression for Evaluating Electromagnetic Profile in Screening Process of Seabed Logging Application
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منشور في: (2021) -
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APPLICATION USING GAUSSIAN PROCESS
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منشور في: (2018) -
Modelling 1-D synthetic seabed logging data for thin hydrocarbon detection: An application of Gaussian process
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منشور في: (2020) -
Multivariate Gaussian Process Regression for Evaluating Electromagnetic Profile in Screening Process of Seabed Logging Application
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منشور في: (2022) -
Gaussian Process-based Inversion for Estimating Hydrocarbon Depth and Resistivity in Marine Controlled-Source Electromagnetic Application
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منشور في: (2023)