Skip to main content
SpringerLink
Log in

Wireless Sensor Network for Multi-channel 3D Data Synchronizing Acquisition System and Visual Simulation Research

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

A multi-channel three-dimension (3D) data synchronizing acquisition system based on wireless sensor network is proposed and used to collect underground three-dimension data in this paper. The channel number and the sampling rate of the data acquisition are the bottleneck of the seismic exploration. The synchronization precision of the multi-channel data affects the oil seismic exploration efficiency directly. The system adopts distributing collecting, conversion, storage and transfer multi-channel seismic data during specific time. The system can synchronizing gather 1024 channel data, and the collective data can form 3D data cube by corresponding process. The data structure of 3D data cube is analyzed and the 3D simulation model of underground oil reservoir is established. The methods of displaying slice for the 3D simulation model are studied using the technology of computer graphic and image processing, and we accomplish the horizontal slices, vertical slices of underground oil reservoir from multi-direction and multi-angle in this paper. Some typical simulation images for an underground oil reservoir are given by programming the corresponding algorithm and graphic display program using C++.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23

Similar content being viewed by others

References

  1. Tian, J. (2001). Underground oil reservoir emulation and prediction. Doctor degree paper of Harbin Engineering University.

  2. Yuan, Z. (2006). Principle of seismic exploration instruments. Beijing: Petroleum Industry Press.

    Google Scholar 

  3. Zhongyin, P., Jian, H., Zhongya, Z., & Xiaolong, M. (2006). Synchronization technique for seismic data acquisition. Geophysical Equipment, 16(3), 165–167.

    Google Scholar 

  4. Savazzi, S., & Spaqnolini, U. (2008). Wireless geophone networks for high-density land acquisition: Technologies and future potential. The Leading Edge, 27(7), 882–886.

    Article  Google Scholar 

  5. Greunen, J. V., & Rabaey, J. (2003). Lightweight time synchronization for sensor networks. In Proceedings of the 2th ACM international workshop on wireless sensor networks and applications, San Diego, pp. 11–19.

  6. Dai, H., & Han, R. (2004). TSync: A lightweight bidirectional time synchronization service for wireless sensor networks. ACM Mobile Computing and Communications Review, 8(1), 125–139.

    Article  Google Scholar 

  7. Hongyuan, Y. A. N. G., Liguo, H. A. N., Jun, L. I. N., & Zubin, C. H. E. N. (2009). Synchronous acquisition technology in network of lineless telemetric seismic instrument. Instrument Technique and Sensor, 3, 15–18.

    Google Scholar 

  8. Zhenshan, L., & Guining, C. (2007). Study and application of synchronous data acquisition technique in large-scale test network. Chinese Journal of Scientific Instrument, 28(4), 748–751.

    Google Scholar 

  9. Wenzhong, L., & Chaoyu, D. (2007). The elementary course and actual combat of ZigBee wireless network technology. Beijing: Beijing University of Aeronautics and Astronautics Press.

    Google Scholar 

  10. Farahani, S. (2008). ZigBee wireless and transceivers, Newnes, USA.

  11. Tianbao, D. I. N. G., & Qiyuan, L. V. (2007). GPS synchronous clock solution for data acquisition in tests. Journal of Gun Launch & Control, 1, 20–23.

    Google Scholar 

  12. Miklos, M., Branislav, K., Gyula, S., & Akos, L. (2004). The flooding time synchronization protocol. In Proceedings of the 2t h ACM conference on embedded networked sensor systems. Baltimore, pp. 39–49.

  13. Li, Q., & Rus, D. (2006). Global clock synchronization in sensor networks. IEEE Transactions on Computers, 55(2), 214–226.

    Article  Google Scholar 

  14. Ren, F. Y., Dong, S. Y., & Lin, C. (2007). Time synchronization scheme and algorithm based on phase locked loop in wireless sensor network. Journal of Software, 18(2), 372–380.

    Article  Google Scholar 

  15. Xu, Z., Zhang, H., Hu, C., Mei, L., Xuan, J., Choo, K. R., et al. (2016). Building knowledge base of urban emergency events based on crowdsourcing of social media. Concurrency and Computation: Practice and Experience, 28(15), 4038–4052.

    Article  Google Scholar 

  16. Xu, Z., Zhang, H., Sugumaran, V., Choo, K. R., Mei, L., & Zhu, Y. (2016). Participatory sensing-based semantic and spatial analysis of urban emergency events using mobile social media. EURASIP Journal of Wireless Communications and Networking, 2016, 44.

    Article  Google Scholar 

  17. Xu, Z., Wei, X., Liu, Y., Mei, L., Hu, C., Choo, K. R., et al. (2016). Building the search pattern of web users using conceptual semantic space model. IJWGS, 12(3), 328–347.

    Article  Google Scholar 

  18. Xu, Z., Liu, Y., Mei, L., Luo, X., Hu, C., Zhang, H., et al. (2016). The mobile media based emergency management of web events influence in cyber-physical space. Wireless Personal Communications. doi:10.1007/s11277-016-3689-7.

    Google Scholar 

  19. Hearn, D., Pauline Baker, M., & Carithers, W. R. (2012). Computer graphics, publishing house of electronics industry.

  20. Hu, H. U. A. N. G., Lizhong, I. L. U., Bin, Y. A. N., & Jian, C. H. E. N. (2010). Review of three-dimensional visualization technology. Journal of Information Engineering University, 11(2), 218–222.

    Google Scholar 

  21. Xinping, Z. E. N. G., Zian, Y. A. N. G., Bihong, L. I. U., Pubin, Z. H. A. N. G., & Lin, Z. O. U. (2005). A study on the technique and methods of 3D visualization modeling of geologic body. Mineal Rersources and Geology, 19(107), 103–106.

    Google Scholar 

  22. McGlinn, K., O’Neill, E., Gibney, A., O’Sullivan, D., & Lewis, D. (2010). SimCon: A tool to support rapid evaluation of smart building application design using context simulation and virtual reality. Journal of Universal Computer Science, 16(15), 1992–2018.

    Google Scholar 

  23. Decraene, J., & Hinze, T. (2010). A multidisciplinary survey of computational techniques for the modelling, simulation and analysis of biochemical networks. Journal of Universal Computer Science, 16(9), 1152–1175.

    Google Scholar 

  24. Papazoglou, P. M., Karras, D. A., & Papademetriou, R. C. (2008). An improved multi-agent simulation methodology for modelling and evaluating wireless communication systems resource allocation algorithms. Journal of Universal Computer Science, 14(7), 1061–1069.

    Google Scholar 

  25. Huasar R. B., & Falke, S. R. Uncertainty in the spatial interpolation of PM 10 monitoring data in Southern California EB/OL. http://capita.wustl.edu/CAPITA/CapitaReports/CaInterp/CaINTERP.HTML. 1997-03003/1999-10-25.

  26. Lam, N. S. (1983). Spatinal interpolation mechods: A review. The American Cartographer, 10(2), 129–149.

    Article  Google Scholar 

  27. Declercq, F. A. N. (1996). Interpolation methods for scattered sample data: Accuracy, spatial patterns, processing times. Cartography and Geographic Information Systems, 23(3), 128–144.

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported in part by the National Natural Science Foundation of China under Grant Nos. 40674028 and 61271370, the National High Technology Research and Development Program of China (863 Program) under Grant No. 2013AA013202, and Funding Project for Academic Human Resources Development in Beijing Union University No. 11101501105.

Author information

Authors and Affiliations

  1. College of Information Technology, Beijing Union University, Beijing, China

    Jingwen Tian, Meijuan Gao & Yue Zhou

Authors
  1. Jingwen Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Meijuan Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yue Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jingwen Tian.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tian, J., Gao, M. & Zhou, Y. Wireless Sensor Network for Multi-channel 3D Data Synchronizing Acquisition System and Visual Simulation Research. Wireless Pers Commun 95, 1981–2001 (2017). https://doi.org/10.1007/s11277-016-3875-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-016-3875-7

Keywords

Search

Navigation