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Common-azimuth seismic data fault analysis using residual UNet
, 2020Seismic fault interpretation is one of the key steps for seismic structure interpretation, which is a time-consuming task and strongly depends on the experience of the interpreter.
Naihao Liu +5 more
semanticscholar +1 more source
Deep-learning-based seismic data interpolation: A preliminary result
Geophysics, 2019Seismic data interpolation is a longstanding issue. Most current methods are only suitable for randomly missing cases. To deal with regularly missing cases, an antialiasing strategy should be included.
Benfeng Wang +3 more
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SEG Technical Program Expanded Abstracts 1988, 1988
Seismic data acquisition involves a number of different subjects, and I am not expert in each of these areas. In fact, it is possible that such an expert in all phases of seismic acquisition may be entirely hypothetical. My approach, therefore, will be to list and briefly describe some ideas which I think are likely to be important in the future.
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Seismic data acquisition involves a number of different subjects, and I am not expert in each of these areas. In fact, it is possible that such an expert in all phases of seismic acquisition may be entirely hypothetical. My approach, therefore, will be to list and briefly describe some ideas which I think are likely to be important in the future.
openaire +1 more source
Adaptive Dictionary Learning for Blind Seismic Data Denoising
IEEE Geoscience and Remote Sensing Letters, 2020The data-driven tight frame (DDTF) method is a dictionary learning method which has been used widely in the adaptive sparse representation and the seismic random noise attenuation. In the DDTF method, the thresholding operator setting plays a significant
Xiaojing Wang, Jianwei Ma
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Deep learning for low-frequency extrapolation from multioffset seismic data
Geophysics, 2019Low-frequency seismic data are crucial for convergence of full-waveform inversion (FWI) to reliable subsurface properties. However, it is challenging to acquire field data with an appropriate signal-to-noise ratio in the low-frequency part of the ...
O. Ovcharenko +4 more
semanticscholar +1 more source
Seismic data interpolation using deep learning with generative adversarial networks
Geophysical Prospecting, 2020We propose an algorithm for seismic trace interpolation using generative adversarial networks, a type of deep neural network. The method extracts feature vectors from the training data using self‐learning and does not require any pre‐processing to create
H. Kaur, N. Pham, Sergey Fomel
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Low-Frequency Noise Suppression Method Based on Improved DnCNN in Desert Seismic Data
IEEE Geoscience and Remote Sensing Letters, 2019High-quality seismic data are the basis for stratigraphic imaging and interpretation, but the existence of random noise can greatly affect the quality of seismic data.
Yuxing Zhao +3 more
semanticscholar +1 more source
SEG Technical Program Expanded Abstracts 1998, 1998
This work describes Seismic Data Mapping (SDM), its definition, properties, applications, limitations and goals. A variety of problems such as offset-continuation, azimuthal-continuation (AMO), layer replacement and datuming can be cast as special cases of SDM.
Herman Jaramillo, Norman Bleistein
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This work describes Seismic Data Mapping (SDM), its definition, properties, applications, limitations and goals. A variety of problems such as offset-continuation, azimuthal-continuation (AMO), layer replacement and datuming can be cast as special cases of SDM.
Herman Jaramillo, Norman Bleistein
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2020
Seismic data interpretation is a very crucial step and hence needs special care to the data. If some ambiguity will remain in the data, the interpretation will be false and hence loss of time and money. This chapter describes some of the processing steps of the seismic data that is necessary before proceeding towards the interpretation of seismic data.
S. P. Maurya, N. P. Singh, K. H. Singh
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Seismic data interpretation is a very crucial step and hence needs special care to the data. If some ambiguity will remain in the data, the interpretation will be false and hence loss of time and money. This chapter describes some of the processing steps of the seismic data that is necessary before proceeding towards the interpretation of seismic data.
S. P. Maurya, N. P. Singh, K. H. Singh
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Proceedings of the IEEE, 1984
We present a brief review of those aspects of seismic data gathering which have a bearing on seismic data processing and interpretation. A summary of sources, detectors, and other instruments is given. Noises that interfere with seismic reflection data are described.
H.W. Cooper, R.E. Cook
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We present a brief review of those aspects of seismic data gathering which have a bearing on seismic data processing and interpretation. A summary of sources, detectors, and other instruments is given. Noises that interfere with seismic reflection data are described.
H.W. Cooper, R.E. Cook
openaire +1 more source