Abstract
Based on an analysis of the information processing mechanism in the primary visual cortex of biological vision, this study proposes an integration method of bar-combination of shifted filter responses (B-COSFIRE) filter with the differential evolution (DE) algorithm for enhancing the precision of events extraction. First, the B-COSFIRE filter incorporates trainable and unsupervised features, utilizing the two-dimensional expression of the difference-of-Gaussians (DoG) model to simulate the receptive field model. By capitalizing on the blur and shift properties of the DoG response, the proposed approach enhances the continuous effective signal while attenuating discontinuous noise signal, thereby demonstrating superior noise robustness compared to conventional methods. Second, the selectivity of proposed filter is not predefined during the implementation but automatically determined based on the given prototype pattern during the configuration process, resulting in a universal solution adaptable to various target patterns. Lastly, we employ the DE algorithm to optimize the feature selection process, enabling the extraction of a minimum feature subset that maximizes the performance of events characterization. The B-COSFIRE method is widely used in the field of image processing. When applying it to seismic exploration, the seismic data used by this algorithm is in ‘sgy’ format, providing richer information than traditional image data. The proposed model can effectively detect the event in seismic data with significant data volume and substantial noise interference. The B-COSFIRE filter method outperforms conventional edge detection techniques by accurately capturing seismic events of varying widths, aligning with the principles observed in biological vision mechanisms. The extracted events exhibit enhanced continuity and accuracy compared to existing approaches.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Arrowsmith SJ, Eisner L (2006) A technique for identifying microseismic multiplets and application to the Valhall field, North Sea. Geophys J Int 71(2):V31–V40
Azzopardi G, Petkov N (2012) A CORF computational model of a simple cell that relies on LGN input outperforms the Gabor function model. Biol Cybern 106:177–189
Azzopardi G, Petkov N (2013) Trainable COSFIRE filters for keypoint detection and pattern recognition. IEEE Trans Pattern Anal Mach Intell 35(2):490–503
Azzopardi G, Strisciuglio N, Vento M, Petkov N (2015) Trainable cosfire filters for vessel delineation with application to retinal images. Med Image Anal 19(1):46–57. https://doi.org/10.1016/j.media.2014.08.002
Badawi SA, Fraz MM (2018) Optimizing the trainable B-COSFIRE filter for retinal blood vessel segmentation. PeerJ. https://doi.org/10.7717/peerj.5855
Bondar I (1992) Seismic horizon detection using image processing algorithms. Geophys Process 40(7):785–800. https://doi.org/10.1111/j.1365-2478.1992.tb00552.x
Chen Y (2020) Automatic microseismic event picking via unsupervised machine learning. Geophys J Int 222(3):1750–1764. https://doi.org/10.1093/gji/ggaa186
Ding WH, Pan GH, Gou ZH, Fu XM, Zhang JB, Hu TJ (2012) The research of interactive auto pickup of seismic events based on energy ratio and cross-correlation. Acta Oceanol Sin 34(3):87–91. https://doi.org/10.1007/s11783-011-0280-z
Gao JH, Yang S, Wang D et al (2011) Estimation of quality factor Q from the instantaneous frequency at the envelope peak of a seismic signal. J Comput Acoust 19(02):155–179
Gibbons SJ, Ringdal F (2006a) The detection of low magnitude seismic events using array-based waveform correlation. Geophys J Int 165(1):149–166. https://doi.org/10.1111/j.1365-246X.2006.02865.x
Gibbons SJ, Ringdal F, Kvaerna T (2006b) Detection and characterization of seismic phases using continuous spectral estimation on incoherent and partially coherent arrays. Geophys J Int 172(1):405–421. https://doi.org/10.1111/j.1365-246X.2007.03650.x
Glinsky ME (1991) Automatic event picking in prestack migrated gathers using aprobablistic neural network. Geophysics 66(5):1488–1496. https://doi.org/10.1190/1.1487094
Haralick RM (1984) Digital step edges from zero crossing of second directional derivatives. IEEE Trans Pattern Anal Mach Intel PAMI 6(1):58–68. https://doi.org/10.1109/TPAMI.1984.4767475
Irvine G, Casagrande V, Norton T (1993) Center surround relationships of magnocellular, parvocellular, and koniocellular relay cells in primate lateral geniculate-nucleus. Vis Neurosci 10:363–373
Lara MD, Kristian G, George A (2019) Age group recognition from face images using a fusion of CNN- and COSFIRE-based features. In: Proceedings of the 2nd International conference on applications of intelligent systems (APPIS '19). https://doi.org/10.1145/3309772.3309784
Li HX, Liu C, Tao CH (2007) The study of application of edge measuring technique to the detection of phase axis of the seismic section. Prog Geophys 22(5):1607–1610. https://doi.org/10.1016/S1872-5791(08)60015-9
Li X (2015) Automatic seismic event pickup using edge measuring technique. Ocean University of China
Liu N, Chen J, Wu H, Li F, Gao J (2022) Microseismic first-arrival picking using fine-tuning feature pyramid networks. IEEE Geosci Remote Sens Lett 19:1–5
Lu JM (1993) Principles of seismic exploration. China University of Petroleum Press, Qingdao
Ma P, Ren J, Sun G, Zhao H, Jia X, Yan Y, Zabalza J (2023) Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. IEEE Transact Geosci Remote Sen 61:1–12. https://doi.org/10.1109/TGRS.2023.3260634
McComack MD (1993) First-break refraction event picking and seismic data trace editing using neural network. Geophysics 58(1):67. https://doi.org/10.1190/1.1443352
Michelet S, Toksöz MN (2007) Fracture mapping in the Soultz-sous-forets geothermal field using microearthquake locations. J Geophys Res 112:B07315. https://doi.org/10.1029/2006JB004442
Ning JS, Wang HH, Luo ZC (2015) Downward continuation of gravity signals based on the multiscale edge constraint. Chin J Geophys 48(1):63–68. https://doi.org/10.3321/j.issn:0001-5733.2005.01.011. (in Chinese)
Rodieck RW (1965) Quantitative analysis of cat retinal ganglion cell response to visual stimuli. Vis Res 5:583–601
Schultz R, Yu Jeffrey Gu (2013) Flexible, inversion-based Matlab implementation of the Radon transform. Comput Geosci 52:437–442
Song F, Toksöz MN (2011) Full-waveform based complete moment tensor inversion and source parameter estimation from downhole microseismic data for hydrofracture monitoring. Geophysics 76(6):WC103–WC116. https://doi.org/10.1190/geo2011-0027.1
Song F, Kuleli HS, Toksöz MN, Ay E, Zhang H (2010) An improved method for hydrofracture-induced microseismic event detection and phase picking. Geophysics 75(6):A47–A52. https://doi.org/10.1190/1.3484716
Spagnolini U (1991) Adaptive picking of refracted first arrivals. Geophy Prosp 39(3):293–312. https://doi.org/10.1111/j.1365-2478.1991.tb00314.x
Strisciuglio N, Azzopardi G, Vento M, Petkov N (2016) Supervised vessel delineation in retinal fundus images with the automatic selection of b-cosfire filters. Mach vis Appl 27(8):1137–1149. https://doi.org/10.1007/s00138-016-0781-7
Strisciuglio N, Petkov N (2017) Delineation of line patterns in images using B-COSFIRE filters. In:International conference and workshop on bioinspired intelligence (IWOBI). doi:https://doi.org/10.1109/iwobi.2017.7985538
Strisciuglio N, Azzopardi G, Petkov N (2017) Detection of curved lines with b-cosfire filters: a case study on crack delineation. In: International conference on computer analysis of images and patterns. Cham. pp. 108–120.
Tu P, Mason I, Zisserman A (1993) An automated system for picking seismic events. SEG 63rd annual meeting, 1993. pp 234–237
Wang C, Gao JH (2012) High-dimensional waveform inversion with cooperative coevolutionary differential evolution algorithm. IEEE Geosci Remote Sens Lett 9:297–301. https://doi.org/10.1109/LGRS.2011.2166532
Wang Z, Ren JC, Zhang D, Sun M, Jiang J (2018) A deep-learning based feature hybrid framework for spatiotemporal saliency detection inside videos. Neurocomputing 287:68–83. https://doi.org/10.1016/j.neucom.2018.01.076
Wang C, Gao JH (2010a) A new differential evolution algorithm with cooperative coevolutionary selection operator for waveform inversion. IEEE International Geoscience and Remote Sensing Symposium (IGARSS). pp 688–690. https://doi.org/10.1109/igarss.2010.5652032
Wang C, Gao J (2010b) A new differential evolution algorithm with cooperative coevolutionary selection operator for waveform inversion. In: IEEE. 2010. pp 688–690
Xiong HJ, Guan YP, Yu YJ (2009) Extraction of cophasal axes on seismic ections based on the edge detection method. Prog Geophys 24(6):2250–2254. https://doi.org/10.3969/j.issn.1004-2903.2009.06.045. (in Chinese)
Xu X, Bonds A, Casagrande V (2002) Modeling receptive-field structure of koniocellular, magnocellular, and parvocellular LGN cells in the owl monkey (Aotus trivigatus). Visual Neurosci 19:703–711
Zhao J, Gao JH, Wang DX, Zhang ML (2013) Q-factor and velocity inversion from zero-offset VSP data. J Appl Geophys 101:51–67
Zhao J, Ren JC, Gao JH, Tschannerl J, Murray P, Wang DX (2019) Automatic events extraction in pre-stack seismic data based on edge detection in slant-stacked peak amplitude profiles. J Petrol Sci Eng 178:459–466. https://doi.org/10.1016/j.petrol.2019.03.062
Zhao H (2005) The layer tracking of fault’s sides based on the artificial neural networks. Chengdu University of Technology.
Zhou YJ, Yue H, Kong QK, Zhou SY (2019) Hybrid event detection and phase-picking algorithm using convolutional and recurrent neural networks. Seismol Res Lett 90:1079–1087. https://doi.org/10.1785/0220180319
Zhu WB, Li B, Tian LF, Li XX, Chen QL (2015) Topology adaptive vessel network skeleton extraction with novel medialness measuring function. Comput Biol Med 64:40–61. https://doi.org/10.1016/j.compbiomed.2015.06.006
Acknowledgements
The authors are thankful to the reviewers for their useful suggestions.
Funding
This work is partially supported by the Natural Science Foundation of Shaanxi Province, China (2021JQ-587), National Natural Science Foundation of China (41604113), National Nature Science Foundation Project of International Cooperation (41711530128), Key research and development projects in Shaanxi Province (2022GY-148). We also thank Changqing oilfield for their field data.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Additional information
Edited by Prof. Gulan Zhang (ASSOCIATE EDITOR) / Prof. Gabriela Fernández Viejo (CO-EDITOR-IN-CHIEF).
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Zhao, J., Li, Y., Lei, H. et al. Seismic events extraction method based on the B-COSFIRE filter combined with the differential evolution algorithm. Acta Geophys. (2023). https://doi.org/10.1007/s11600-023-01222-1
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11600-023-01222-1