1887
  1. Home
  2. A-Z Publications
  3. Geophysical Prospecting
  4. Volume 66, Issue 4
  5. Article
Volume 66, Issue 4
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

There is growing pressure from regulators on operators to adhere to increasingly stricter regulations related to the environment and safety. Hence, operators are required to predict and contain risks related to hydrocarbon production and their infrastructure in order to maintain their licence to operate. A deeper understanding of production optimisation and production‐related risk requires strengthened knowledge of reservoir behaviour and overburden dynamics. To accomplish this, sufficient temporal and spatial resolution is required as well as an integration of various sources of measurements. At the same time, tremendous developments are taking place in sensors, networks, and data analysis technologies. Sensors and accompanying channels are getting smaller and cheaper, and yet they offer high fidelity. New ecosystems of ubiquitous wireless communications including Internet of Things nowadays allow anyone to affordably connect to the Internet at any time and anywhere. Recent advances in cloud storage and computing combined with data analytics allow fast and efficient solutions to handle considerable amounts of data. This paper is an effort to pave the way for exploiting these three fundamental advances to create Internet of Things‐based wireless networks of seismic sensors.

To this aim, we propose to employ a recently developed Internet of Things‐based wireless technology, so‐called low‐power wide‐area networks, to exploit their long range, low power, and inherent compatibility to cloud storage and computing. We create a remotely operated minimum‐maintenance wireless solution for four major seismic applications of interest. By proposing appropriate network architecture and data coordination (aggregation and transmission) designs, we show that neither the low data rate nor the low duty cycle of low‐power wide‐area networks imposes fundamental issues in handling a considerable amount of data created by complex seismic scenarios as long as the application is delay tolerant. In order to confirm this claim, we cast our ideas into a practical large‐scale networking design for simultaneous seismic monitoring and interferometry and carry out an analysis on the data generation and transmission rates. Finally, we present some results from a small‐scale field test in which we have employed our Internet of Things‐based wireless nodes for real‐time seismic quality control over clouds.

© 2018 European Association of Geoscientists & Engineers © 2018 European Association of Geoscientists & Engineers
Loading

Article metrics loading...

/content/journals/10.1111/1365-2478.12617
2018-03-23
2024-04-25

  • From This Site

    /content/journals/10.1111/1365-2478.12617
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. AllinsonD.2009. The evolution of cableless seismic. ION Geophysical, Exploration Technology.
  2. BarakatS.2008. Systems and methods for seismic data acquistion employing asynchronous, decoupled data sampling and transmission. US Patent No. 7660203.
  3. BatraA., BalakrishnanJ., AielloG.R., FoersterJ.R. and DabakA.2004. Design of a multiband OFDM system for realistic UWB channel environments. IEEE Transactions on Microwave Theory and Techniques52, 2123–2138.
     [Google Scholar]
  4. CampilloM. and PaulA.2003. Long‐range correlations in the diffuse seismic data. Science299, 547–549.
     [Google Scholar]
  5. ChunduryR.2008. Mobile broadband backhaul: addressing the challenge. Ericsson White Paper.
  6. de WaalJ.A., Muntendam‐BosA.G. and RoestJ.P.A.2015. Production‐induced subsidence and seismicity in the Groningen gas field—can it be managed? Proceedings of the International Association of Hydrological Sciences372, 129.
     [Google Scholar]
  7. FischerJ., KühnlenzF., AhrensK. and EveslageI.2009. Model‐based development of self‐organising earthquake early warning systems. Proceedings of the International Conference on Mathematical Modelling, 1–19.
     [Google Scholar]
  8. FlemingK., PicozziM., MilkereitC., KühnlenzF., LichtblauB., FischerJ.et al. 2009. The self‐organizing seismic early warning information network (SOSEWIN). Seismological Research Letters80, 755–771.
     [Google Scholar]
  9. GanaA.R.2008. Wireless communication system for land seismic operations: a feasibility study. PhD thesis, Norwegian University of Science and Technology, Norway.
     [Google Scholar]
  10. GoldsmithA.2005. Wireless Communications. Cambridge, UK: Cambridge University Press.
     [Google Scholar]
  11. HollisJ., IseliJ., WilliamsM. and HoenmansS.2005. The future of land seismic. E&P November, 33–37.
     [Google Scholar]
  12. HuskerA., StubailoI., LukacM., NaikV., GuyR., DavisP.et al. 2008. WiLSoN: The wirelessly linked seismological network and its application in the middle American subduction experiment. Seismological Research Letters79, 438–443.
     [Google Scholar]
  13. Jamali‐RadH. and CampmanX.2017. Method, Sensor and System for Wireless Seismic Networking. European Patent No. EP17155229 (filed).
  14. Jamali‐RadH., McKayI., CampmanX., WalkW., BekerM. and van den BrandJ.2018. IoT‐based wireless seismic QC. Accepted to be published in The Leading Edge.
  15. Jamali‐RadH., TangZ., CampmanX., DroujinineA. and LeusG.2015. Sparsity‐aware multiple microseismic event localization blind to the source time‐function. Geophysical Prospecting63, 70–77.
     [Google Scholar]
  16. KendallR.2015. Cableless seismic acquisition. http://www.geoconvention.com/archives/2015/309_GC2015_Cableless_Seismic_Acquisition.pdf. (GeoConvention).
  17. LeCampionB., JeffreyR. and DetournayE.2004. Real‐time estimation of fracture volume and hydraulic fracturing treatment efficiency. Proceedings of the 6th North American Rock Mechanics Symposium, 1–9.
     [Google Scholar]
  18. LinkLabs
    LinkLabs2016. A comprehensive look at low‐power wide‐area networks. http://info.link‐labs.com/lpwan.
  19. LoRa Alliance
    LoRa Alliance2015. LoRaWAN: What is it? A Technical Overview of LoRA and LoRaWAN. https://www.lora‐alliance.org.
  20. Nokia
    Nokia2016. LTE‐M optimizing LTE for the Internet of Things. https://novotech.com/docs/default‐source/default‐document‐library/lte‐m‐optimizing‐lte‐for‐the‐internet‐of‐things.pdf?sfvrsn=0.
  21. PellegrinoM., PajolaN., TortiniG., EspositoA., FollinoP. and Di LecceA.2012. Wireless vs. wireline land 3D seismic in North Italy. SEG Technical Program Expanded Abstracts 2012, 1–5.
     [Google Scholar]
  22. PereiraR.L., TrindadeJ., GonçalvesF., SureshL., BarbosaD. and VazaoT.2014. A wireless sensor network for monitoring volcano seismic signals. Natural Hazard and Earth System Sciences14, 3123–3142.
     [Google Scholar]
  23. PicozziM., MilkereitC., ParolaiS., JaeckelK.H., VeitI., FischerJ.et al. 2010. GFZ wireless seismic array (GFZ‐WISE), a wireless mesh network of seismic sensors: new perspectives for seismic noise array investigations and site monitoring. Sensors10, 3280–3304.
     [Google Scholar]
  24. PowersS.2013. Debate on new fracking rules continues. http://peoriapublicradio.org/post/debate‐new‐fracking‐rules‐continues#stream/0.
  25. ProakisJ.G. and SalehiM.2007. Digital Communications, 5th edn. New York City, NY: Mc‐Graw Hill Education.
     [Google Scholar]
  26. SavazziS., GorattiL., FontanellaD., NicoliM. and SpagnoliniU.2011. Pervasive UWB sensor networks for oil exploration. IEEE International Conference on Ultra‐Wideband (ICUWB), 225–229.
     [Google Scholar]
  27. SavazziS., GorattiL., SpagnoliniU. and Latva‐ahoM.2009a. Short‐range wireless sensor networks for high density seismic monitoring. Proceedings of Wireless World Research Forum, 1–5.
     [Google Scholar]
  28. SavazziS., MolteniD. and SpagnoliniU.2010. Energy‐aware compress and forward systems for wireless monitoring of time‐varying fields. EEE 21st International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 1–5.
     [Google Scholar]
  29. SavazziS. and SpagnoliniU.2008. Wireless geophone networks for high‐density land acquisitions: technologies and future potential. The Leading Edge27, 882–886.
     [Google Scholar]
  30. SavazziS. and SpagnoliniU.2009. Synchronous ultra‐wideband wireless sensors networks for oil and gas exploration. IEEE Symposium on Computers and Communications (ISCC), 907–912.
     [Google Scholar]
  31. SavazziS., VittorioV. and SpagnoliniU.2009b. High‐density wireless geophone networks for oil and gas monitoring and exploration. ERCIM News76, 43–45.
     [Google Scholar]
  32. SEMTECH Co.
    SEMTECH Co.2016. SEMTECH LoRa technology. http://www.semtech.com/wireless‐rf/lora.html.
  33. ShapiroN.M. and CampilloM.2004. Emergence of broadband Rayleigh waves from correlations of the ambient seismic noise. Geophysical Research Letters31, 1–4.
     [Google Scholar]
  34. SrinivasY. and RaoK.R.2014. Landslide warning system using Zigbee and GPS. IOSR Journal of Engineering (IOSRJEN)4, 1–6.
     [Google Scholar]
  35. TanenbaumA.2002. Computer Networks, 4th edn. Upper Saddle River, NJ: Prentice Hall Professional Technical Reference.
     [Google Scholar]
  36. TranB.Q.2007. Wireless sensor data processing systems. US Patent No. 7224642 B1.
  37. van Thienen‐VisserK. and BreuneseJ.N.2015. Induced seismicity of the Groningen gas field: history and recent developments. The Leading Edge34, 664–671.
     [Google Scholar]
  38. WeberE., ConvertitoV., IannacconeG., ZolloA., BobbioA., CantoreL.et al. 2007. An advanced seismic network in the southern Apennines (Italy) for seismicity investigations and experimentation with earthquake early warning. Seismological Research Letters78, 622–634.
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.1111/1365-2478.12617
Loading
Internet of Things‐based wireless networking for seismic applications
Geophysical Prospecting 66, 833 (2018); https://doi.org/10.1111/1365-2478.12617
/content/journals/10.1111/1365-2478.12617
/content/journals/10.1111/1365-2478.12617
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): Internet of things (IoT); Low‐power wide‐area networks (LPWANs); Wireless seismic networking

Most Cited This Month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error