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International Journal of Scholarly Research in Science and Technology
Sustainable exploration in the energy industry necessitates innovative approaches that address environmental concerns without compromising the efficiency (or robustness) of subsurface modeling.
Obobi Ume Onwuka, Akinsola Adu
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Sustainable exploration in the energy industry necessitates innovative approaches that address environmental concerns without compromising the efficiency (or robustness) of subsurface modeling.
Obobi Ume Onwuka, Akinsola Adu
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ChannelSeg3D: Channel simulation and deep learning for channel interpretation in 3D seismic images
Geophysics, 2021Seismic channel interpretation involves detecting channel structures, which often appear as meandering shapes in 3D seismic images. Many conventional methods are proposed for delineating channel structures using different seismic attributes.
Hang Gao, Xinming Wu, Guofeng Liu
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Probabilistic Seismic Interpretation Using Bayesian Neural Networks
81st EAGE Conference and Exhibition 2019, 2019Summary Recent progress in deep learning and especially convolutional neural networks has brought new advances in the automatic interpretation of seismic datasets.
L. Mosser, R. Oliveira, M. Steventon
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Interpreting Subsurface Seismic Data
2022Interpreting Subsurface Seismic Data presents recent advances in methodologies for seismic imaging and interpretation across multiple applications in geophysics including exploration, marine geology, and hazards. It provides foundational information for context, as well as focussing on recent advances and future challenges.
Rebecca Bell, David Iacopini, Mark Vary
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Why using CNN for seismic interpretation? An investigation
SEG technical program expanded abstracts, 2018Summary Three-dimensional seismic interpretation plays a key role in robust hydrocarbon exploration and production of subsurface reservoirs. With the dramatic growing size of 3D seismic surveys, however, manually interpreting a seismic volume turns to be
H. Di, Zhen Wang, G. AlRegib
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Seismic graph analysis to aid seismic interpretation
Interpretation, 2019During the seismic interpretation process, geoscientists rely on their experience and visual analysis to assess the similarity between seismic sections. However, evaluating all of the seismic sections in a 3D survey can be a time-consuming task. When interpreters are working on a data set, a common procedure is to divide the cube in increasingly finer ...
Rodrigo S. Ferreira +3 more
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The Leading Edge, 2018
Interpretation of time-lapse (or 4D) seismic data in terms of reservoir changes due to production posed many challenges in the Norne Field as the field experienced intense production activity from 1997 to 2006.
M. Maleki, A. Davólio, D. Schiozer
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Interpretation of time-lapse (or 4D) seismic data in terms of reservoir changes due to production posed many challenges in the Norne Field as the field experienced intense production activity from 1997 to 2006.
M. Maleki, A. Davólio, D. Schiozer
semanticscholar +1 more source
IEEE Transactions on Geoscience and Remote Sensing, 1984
During the past decade, interest in fuzzy sets has led to the development of a well-organized theory developed by Zadeh [1]. This theory has particular applications in pattern recognition, fuzzy automata, and mapping. This paper concerns the application of fuzzy sets to the problem of seismic Interpretation.
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During the past decade, interest in fuzzy sets has led to the development of a well-organized theory developed by Zadeh [1]. This theory has particular applications in pattern recognition, fuzzy automata, and mapping. This paper concerns the application of fuzzy sets to the problem of seismic Interpretation.
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Quantitative Seismic Interpretation
2005Quantitative Seismic Interpretation demonstrates how rock physics can be applied to predict reservoir parameters, such as lithologies and pore fluids, from seismically derived attributes. The authors provide an integrated methodology and practical tools for quantitative interpretation, uncertainty assessment, and characterization of subsurface ...
Per Avseth, Tapan Mukerji, Gary Mavko
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Seismic stratigraphy interpretation by deep convolutional neural networks: A semisupervised workflow
Geophysics, 2020Depicting geologic sequences from 3D seismic surveying is of significant value to subsurface reservoir exploration, but it is usually time- and labor-intensive for manual interpretation by experienced seismic interpreters.
H. Di, Zhun Li, H. Maniar, A. Abubakar
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