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  • 1
    Online Resource
    Online Resource
    Geosteering Phase Attributes: A New Detector for the Discontinuities of Seismic Images
    Institute of Electrical and Electronics Engineers (IEEE) ; 2019
    In:  IEEE Geoscience and Remote Sensing Letters Vol. 16, No. 1 ( 2019-1), p. 145-149
    Details
    In: IEEE Geoscience and Remote Sensing Letters, Institute of Electrical and Electronics Engineers (IEEE), Vol. 16, No. 1 ( 2019-1), p. 145-149
    Type of Medium: Online Resource
    ISSN: 1545-598X , 1558-0571
    URL: Article
    DOI: 10.1109/LGRS.2018.2866419
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2019
    detail.hit.zdb_id: 2138738-2
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  • 2
    Online Resource
    Online Resource
    Survival Risk Prediction of Esophageal Cancer Based on the Kohonen Network Clustering Algorithm and Kernel Extreme Learning Machine
    MDPI AG ; 2022
    In:  Mathematics Vol. 10, No. 9 ( 2022-04-19), p. 1367-
    Details
    In: Mathematics, MDPI AG, Vol. 10, No. 9 ( 2022-04-19), p. 1367-
    Abstract: Accurate prediction of the survival risk level of patients with esophageal cancer is significant for the selection of appropriate treatment methods. It contributes to improving the living quality and survival chance of patients. However, considering that the characteristics of blood index vary with individuals on the basis of their ages, personal habits and living environment etc., a unified artificial intelligence prediction model is not precisely adequate. In order to enhance the precision of the model on the prediction of esophageal cancer survival risk, this study proposes a different model based on the Kohonen network clustering algorithm and the kernel extreme learning machine (KELM), aiming to classifying the tested population into five catergories and provide better efficiency with the use of machine learning. Firstly, the Kohonen network clustering method was used to cluster the patient samples and five types of samples were obtained. Secondly, patients were divided into two risk levels based on 5-year net survival. Then, the Taylor formula was used to expand the theory to analyze the influence of different activation functions on the KELM modeling effect, and conduct experimental verification. RBF was selected as the activation function of the KELM. Finally, the adaptive mutation sparrow search algorithm (AMSSA) was used to optimize the model parameters. The experimental results were compared with the methods of the artificial bee colony optimized support vector machine (ABC-SVM), the three layers of random forest (TLRF), the gray relational analysis–particle swarm optimization support vector machine (GP-SVM) and the mixed-effects Cox model (Cox-LMM). The results showed that the prediction model proposed in this study had certain advantages in terms of prediction accuracy and running time, and could provide support for medical personnel to choose the treatment mode of esophageal cancer patients.
    Type of Medium: Online Resource
    ISSN: 2227-7390
    URL: Article
    DOI: 10.3390/math10091367
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704244-3
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  • 3
    Online Resource
    Online Resource
    Gas Reservoir Characterization Using Lp-Norm Constrained High-Resolution Seismic Spectral Attributes
    Springer Science and Business Media LLC ; 2020
    In:  Pure and Applied Geophysics Vol. 177, No. 11 ( 2020-11), p. 5417-5433
    Details
    In: Pure and Applied Geophysics, Springer Science and Business Media LLC, Vol. 177, No. 11 ( 2020-11), p. 5417-5433
    Type of Medium: Online Resource
    ISSN: 0033-4553 , 1420-9136
    URL: Article
    DOI: 10.1007/s00024-020-02585-y
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 1464028-4
    detail.hit.zdb_id: 216719-0
    SSG: 16,13
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  • 4
    Online Resource
    Online Resource
    Inversion-Based 3-D Seismic Denoising for Exploring Spatial Edges and Spatio-Temporal Signal Redundancy
    Institute of Electrical and Electronics Engineers (IEEE) ; 2018
    In:  IEEE Geoscience and Remote Sensing Letters Vol. 15, No. 11 ( 2018-11), p. 1682-1686
    Details
    In: IEEE Geoscience and Remote Sensing Letters, Institute of Electrical and Electronics Engineers (IEEE), Vol. 15, No. 11 ( 2018-11), p. 1682-1686
    Type of Medium: Online Resource
    ISSN: 1545-598X , 1558-0571
    URL: Article
    DOI: 10.1109/LGRS.2018.2854929
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2018
    detail.hit.zdb_id: 2138738-2
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  • 5
    Online Resource
    Online Resource
    Multispectral Phase-Based Geosteering Coherence Attributes for Deep Stratigraphic Feature Characterization
    Institute of Electrical and Electronics Engineers (IEEE) ; 2019
    In:  IEEE Geoscience and Remote Sensing Letters Vol. 16, No. 8 ( 2019-8), p. 1309-1313
    Details
    In: IEEE Geoscience and Remote Sensing Letters, Institute of Electrical and Electronics Engineers (IEEE), Vol. 16, No. 8 ( 2019-8), p. 1309-1313
    Type of Medium: Online Resource
    ISSN: 1545-598X , 1558-0571
    URL: Journal
    URL: Article
    DOI: 10.1109/LGRS.8859
    DOI: 10.1109/LGRS.2019.2894004
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2019
    detail.hit.zdb_id: 2138738-2
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  • 6
    Online Resource
    Online Resource
    Goal-Oriented Inversion-Based NMO Correction Using a Convex $l_{2,1}$ -Norm
    Institute of Electrical and Electronics Engineers (IEEE) ; 2020
    In:  IEEE Geoscience and Remote Sensing Letters Vol. 17, No. 1 ( 2020-1), p. 162-166
    Details
    In: IEEE Geoscience and Remote Sensing Letters, Institute of Electrical and Electronics Engineers (IEEE), Vol. 17, No. 1 ( 2020-1), p. 162-166
    Type of Medium: Online Resource
    ISSN: 1545-598X , 1558-0571
    URL: Journal
    URL: Article
    DOI: 10.1109/LGRS.8859
    DOI: 10.1109/LGRS.2019.2915520
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2020
    detail.hit.zdb_id: 2138738-2
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  • 7
    Online Resource
    Online Resource
    Enhancing low-wavenumber components of full-waveform inversion using an improved wavefield decomposition method in the time-space domain
    Elsevier BV ; 2018
    In:  Journal of Applied Geophysics Vol. 157 ( 2018-10), p. 10-22
    Details
    In: Journal of Applied Geophysics, Elsevier BV, Vol. 157 ( 2018-10), p. 10-22
    Type of Medium: Online Resource
    ISSN: 0926-9851
    URL: Article
    DOI: 10.1016/j.jappgeo.2018.06.013
    RVK:
    UA 4543
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2018
    detail.hit.zdb_id: 1496997-X
    SSG: 16,13
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  • 8
    Online Resource
    Online Resource
    Stable inversion-based multitrace deabsorption method for spatial continuity preservation and weak signal compensation
    Society of Exploration Geophysicists ; 2016
    In:  GEOPHYSICS Vol. 81, No. 3 ( 2016-05), p. V199-V212
    Details
    In: GEOPHYSICS, Society of Exploration Geophysicists, Vol. 81, No. 3 ( 2016-05), p. V199-V212
    Abstract: Nonstationary seismic data can be expressed using a linear matrix-vector multiplication system derived from wave theory when anelastic effects of the earth can be quantified by the intrinsic quality factor (or [Formula: see text]) and [Formula: see text] is frequency independent in the seismic bandwidth. On the basis of the linear modeling system and singular value decomposition, we have assessed the stability using weights associated with the left singular vectors, data, and singular values, and we assessed the compensation/resolution limitation of inversion-based deabsorption using the right singular vectors. In addition, a stable inversion-based multitrace deabsorption method was developed by minimizing the [Formula: see text]-norm of coefficients in the frequency-wavenumber ([Formula: see text] ) domain of reflectivity subject to the time-domain nonstationary data misfit. The optimum deabsorption result can be obtained by sequentially solving a series of lasso subproblems until the stopping condition is reached. As the number of solving lasso subproblems increases, the role of [Formula: see text] magnitude sparsity constraint relative to data misfit gradually decreases. In this way, the proposed method can highlight the spatial continuities and reduce the influence of noise on the updated result during starting iterations due to [Formula: see text] magnitude sparsity, whereas compensate details including some discontinuities of events and weak reflections during later iterations due to the dominant role of data misfit. We tested the method on a series of data sets, including a synthetic data set, a physical modeling data set, and a field data set. Our results determined that the proposed method can provide stable compensation results, even in the presence of coherent noise and/or strong random noise. Compared with the trace-by-trace [Formula: see text]-norm regularization deabsorption method, our method performed better in spatial continuity preservation and weak signal compensation.
    Type of Medium: Online Resource
    ISSN: 0016-8033 , 1942-2156
    URL: Article
    DOI: 10.1190/geo2015-0247.1
    RVK:
    UA 4068.4
    Language: English
    Publisher: Society of Exploration Geophysicists
    Publication Date: 2016
    detail.hit.zdb_id: 2033021-2
    detail.hit.zdb_id: 2184-2
    SSG: 16,13
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  • 9
    Online Resource
    Online Resource
    Three-dimensional geosteering coherence attributes for deep-formation discontinuity detection
    Society of Exploration Geophysicists ; 2018
    In:  GEOPHYSICS Vol. 83, No. 6 ( 2018-11-01), p. O105-O113
    Details
    In: GEOPHYSICS, Society of Exploration Geophysicists, Vol. 83, No. 6 ( 2018-11-01), p. O105-O113
    Abstract: Deep-formation oil/gas exploration is a key objective in the geophysical field, and structural and stratigraphic discontinuities, such as faults and channels, usually contribute to the construction of traps and reservoirs. Coherence has been used successfully to identify these abnormal features in seismic amplitude volumes. However, the current coherence algorithms seldom involve the geologic concept. We propose geosteering coherence attributes by implementing the coherence calculation perpendicular to the direction of the structural trend in a 3D curved plane. We estimate a group of time lags between the original analysis trace and each original neighboring trace along a certain spatial direction by using dip scanning. For each spatial direction, we subsequently construct two new model traces by weighting phase traces derived from the complex seismic traces, in which time lags are eliminated. We then use the new model traces to compute the crosscorrelation coefficients for each spatial direction. We finally obtain the 3D geosteering coherence attributes by taking the minimum values among the modulus of the crosscorrelation coefficients along different spatial directions to approximately characterize the coherence perpendicular to the structural trend in a 3D curved plane. An example of the 3D physical modeling involving fracture groups and faults embedded in the deep formation is used to demonstrate the effectiveness of the 3D geosteering coherence attributes. The applications on two real 3D seismic data sets of sand reservoirs from western deep formation illustrate that our method can alleviate the influence of dipping strata and can highlight subtle structures. Compared to the conventional coherence method, our method can highlight subtle geologic structures more and better, suggesting that it may be serve as a future tool for detecting the distribution of geologic abnormalities in deep exploration.
    Type of Medium: Online Resource
    ISSN: 0016-8033 , 1942-2156
    URL: Article
    DOI: 10.1190/geo2017-0642.1
    RVK:
    UA 4068.4
    Language: English
    Publisher: Society of Exploration Geophysicists
    Publication Date: 2018
    detail.hit.zdb_id: 2033021-2
    detail.hit.zdb_id: 2184-2
    SSG: 16,13
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  • 10
    Online Resource
    Online Resource
    Multichannel spatially correlated reflectivity inversion using block sparse Bayesian learning
    Society of Exploration Geophysicists ; 2017
    In:  GEOPHYSICS Vol. 82, No. 4 ( 2017-07-01), p. V191-V199
    Details
    In: GEOPHYSICS, Society of Exploration Geophysicists, Vol. 82, No. 4 ( 2017-07-01), p. V191-V199
    Abstract: The reflectivity inversion approach based on a variety of regularization terms was extensively developed and applied to image subsurface structure in recent years. In addition, multichannel reflectivity inversion or deconvolution considering the lateral continuity of reflection interfaces or reflectivity in adjacent channels has been developed. However, these processing operations seldom adaptively judge the stratal continuity or automatically alter the parameters of the corresponding algorithm. To use the special correlation of the reflection information contained in the seismic data, a multichannel spatially correlated reflectivity inversion using block sparse Bayesian learning (bSBL) is introduced. The method adopts a covariance matrix that describes the spatial relationship of reflectivity and simultaneously controls the temporal sparsity. With an expectation-maximization algorithm, we can obtain the parameters of the multichannel reflectivity model, including the mean (i.e., the estimated multichannel reflectivity) and the covariance matrix (i.e., the correlation of nonzero reflection impulses). The noise variance in the observed seismic data is also estimated during the inversion processing. Due to the contribution of reflectivity correlation in different traces, the performance of the multichannel spatially correlated reflectivity inversion using bSBL is significantly superior to the trace-by-trace processing method in the presence of a medium level of noise. The synthetic and real data examples illustrate that the lateral continuity is well-preserved in seismic profiles after inversion.
    Type of Medium: Online Resource
    ISSN: 0016-8033 , 1942-2156
    URL: Article
    DOI: 10.1190/geo2016-0366.1
    RVK:
    UA 4068.4
    Language: English
    Publisher: Society of Exploration Geophysicists
    Publication Date: 2017
    detail.hit.zdb_id: 2033021-2
    detail.hit.zdb_id: 2184-2
    SSG: 16,13
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