Improvement of Wired Drill Pipe Data Quality via Data Validation and Reconciliation

  • Dan SuiEmail author
  • Olha Sukhoboka
  • Bernt Sigve Aadnøy
Research Article


Wired drill pipe (WDP) technology is one of the most promising data acquisition technologies in today’s oil and gas industry. For the first time it allows sensors to be positioned along the drill string which enables collecting and transmitting valuable data not only from the bottom hole assembly (BHA), but also along the entire length of the wellbore to the drill floor. The technology has received industry acceptance as a viable alternative to the typical logging while drilling (LWD) method. Recently more and more WDP applications can be found in the challenging drilling environments around the world, leading to many innovations to the industry. Nevertheless most of the data acquired from WDP can be noisy and in some circumstances of very poor quality. Diverse factors contribute to the poor data quality. Most common sources include miscalibrated sensors, sensor drifting, errors during data transmission, or some abnormal conditions in the well, etc. The challenge of improving the data quality has attracted more and more focus from many researchers during the past decade.

This paper has proposed a promising solution to address such challenge by making corrections of the raw WDP data and estimating unmeasurable parameters to reveal downhole behaviors. An advanced data processing method, data validation and reconciliation (DVR) has been employed, which makes use of the redundant data from multiple WDP sensors to filter/remove the noise from the measurements and ensures the coherence of all sensors and models. Moreover it has the ability to distinguish the accurate measurements from the inaccurate ones. In addition, the data with improved quality can be used for estimating some crucial parameters in the drilling process which are unmeasurable in the first place, hence provide better model calibrations for integrated well planning and realtime operations.


Data quality wired drill pipe (WDP) data validation and reconciliation (DVR) drilling models 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



This work is supported by University of Stavanger, Norway. The authors wish to thank SINTEF, the Center for Integrated Operations in the Petroleum Industry and the management of National Oilwell Varco IntelliServ for their contribution and support in publishing this paper.


  1. [1]
    R. F. Spinnler, F. A. Stone. Mud Pulse Logging While Drilling Telemetry System: Design, Development, and Demonstrations, Technical Report BERC/TPR-78/4, Houston, Texas, USA, 1978.CrossRefGoogle Scholar
  2. [2]
    M. J. Jellison, R. Urbanowski, H. Sporker, M. E. Reeves. Intelligent drill pipe improves drilling efficiency, enhances well safety and provides added value. In Proceedings of IADC World Drilling Conference, Dubrovnik, Croatia, 2004.Google Scholar
  3. [3]
    American Association of Oilwell Drilling Contractory. Along-string pressure, temperature measurements hold revolutionary promise for downhole management. Drilling Contractor, vol. 65, no. 2, pp. 36–40, 2009.Google Scholar
  4. [4]
    R. Nybø, D. Sui, J. Petersen, J. Froyen, T. A. Jackson, D. Veeningen. Getting the most out of networked drillstrings. In Proceedings of SPE Intelligent Energy International, SPE, Utrecht, The Netherlands, pp. 1–14, 2012.Google Scholar
  5. [5]
    A. N. Eaton, L. D. R. Beal, S. D. Thorpe, E. H. Janis, C. Hubbell, J. D. Hedengren, R. Nybo, M. Aghito, K. Bjørkevoll, R. El Boubsi, J. Braaksma, G. van og. Ensemble model predictive control for robust automated managed pressure drilling. In Proceedings of SPE Annual Technical Conference and Exhibition, SPE, Houston, USA, pp. 1–16, 2015.Google Scholar
  6. [6]
    R. A. Shishavan, C. Hubbell, H. Perez, J. Hedengren, D. S. Pixton. Combined rate of penetration and pressure regulation for drilling optimization using high speed telemetry. In Proceedings of SPE Deepwater Drilling and Completions Conference, SPE, USA, pp. 1–16, 2014.Google Scholar
  7. [7]
    D. S. Pixton, R. A. Shishavan, H. D. Perez, J. D. Hedengren, A. Craig. Addressing UBO and MPD challenges with wired drill pipe telemetry. In Proceedings of SPE/IADC Managed Pressure Drilling and underbalanced Operations Conference and Exhibition, SPE, Madrid, Spain, pp. 1–16, 2014.Google Scholar
  8. [8]
    R. A. Shishavan, C. Hubbell, H. Perez, J. Hedengren, D. S. Pixton, A. P. Pink. Multivariate control for managed pressure drilling systems using high speed telemetry. In Proceedings of SPE Annual Technical Conference and Exhibition, SPE, Amsterdam, Netherlands, pp. 1–18,2014.Google Scholar
  9. [9]
    J. D. Hedengren, A. N. Eaton. Overview of estimation methods for industrial dynamic systems. Optimization and Engineering, doi:10.1007/s11081-015-9295-9, 2015.zbMATHGoogle Scholar
  10. [10]
    D. Pixton, A. Craig. Drillstring network 2.0: An enhanced drillstring network based on 100 wells of experience. In Proceedings of IADC/SPE Drilling Conference and Exhibition, SPE, Fort Worth, USA, pp. 1–15, 2014.Google Scholar
  11. [11]
    S. Shils, R. Teelken, B. Van Burkleo, O. J. Rossa, N. Edwards. The use of wired drillpipe technology in a complex drilling environment increased drilling efficiency and reduced well times. In Proceedings of IADC/SPE Drilling Conference and Exhibition, SPE, Fort Worth, USA, pp. 1–18, 2016.Google Scholar
  12. [12]
    R. Rommetveit, K. S. Bjørkevoll, S. I. Odegrd, M. Herbert, G. W. Halsey, R. Kluge, T. Korsvold. eDrilling used on ekofisk for real-time drilling supervision, simulation, 3D visualization and diagnosis. In Proceedings of SPE Intelligent Energy Conference and Exhibition, SPE, Amsterdam, The Netherlands, pp. 1–14, 2008.Google Scholar
  13. [13]
    K. R. Zhao, D. Sui. Drilling data quality control via wired drill pipe technology. In Proceedings of the 34th Chinese Control Conference, IEEE, Hangzhou, China, pp. 7883–7888, 2015.Google Scholar
  14. [14]
    G. M. Stanley, R. S. H. Mah. Observability and redundancy in process data estimation. Chemical Engineering Science, vol. 36, pp. 259–272, 1981.Google Scholar
  15. [15]
    T. Amand, G. Heyen, B. Kalitventzeff. Plant monitoring and fault detection: Synergy between data reconciliation and principal component analysis. Computers and Chemical Engineering, vol. 25, no. 4–6, pp. 501–507, 2001.CrossRefGoogle Scholar
  16. [16]
    G. M. Stanley, R. S. H. Mah. Estimation of flows and temperatures in process networks. AIChE Journal, vol. 23, no. 5, pp. 642–650, 1977.CrossRefGoogle Scholar
  17. [17]
    I. N. Almeida, P. D. Antunes, F. O. C. Gonzalez, R. A. Yamachita, A. Nascimento, J. L. Goncalves. A review of telemetry data transmission in unconventional petroleum environments focused on information density and reliability. Journal of Software Engineering and Applications, vol. 8, pp. 455–462, 2015.CrossRefGoogle Scholar
  18. [18]
    K. Solem. The Impact of Wired Drill Pipe on the Martin Linge Field, Master dissertation, University of Stavanger, Norway, 2015.Google Scholar
  19. [19]
    J. E. Gravdal, R. J. Lorentzen, R. W. Time. Wired drill pipe telemetry enables real-time evaluation of kick during managed pressure drilling. In Proceedings of SPE Asia Pacific Oil and Gas Conference and Exhibition, SPE, Brisbane, Australia, pp. 1–20, 2010.Google Scholar
  20. [20]
    C. J. Coley, S. T. Edwards. The use of along string annular pressure measurements to monitor solids transport and hole cleaning. In Proceedings of IADC/SPE Drilling Conference, SPE, Amsterdam, The Netherlands, pp. 1–35, 2013.Google Scholar
  21. [21]
    J. Rasmus, A. Dorel, T. Azizi, A. David, E. Duran, H. Lopez, G. Aguinaga, J. C. Beltran, A. Ospino, E. Ochoa. Utilizing wired drill pipe technology during managed pressure drilling operations to maintain direction control, constant bottom-hole pressures, and well-bore integrity in a deep, ultra-depleted reservoir. In Proceedings of IADC/SPE Drilling Conference, SPE, Amsterdam, The Netherlands, pp. 1–19, 2013.Google Scholar
  22. [22]
    O. N. Stamnes. Nonlinear Estimation with Applications to Drilling, Ph. D. dissertation, NTNU, Trondheim, 2011.Google Scholar
  23. [23]
    J. F. Kenney, E. S. Keeping. Linear regression and correlation. Mathematics of Statistics, 3rd ed., J. F. Kenney, Ed., Princeton, USA: Van Nostrand, pp. 252–285, 1962.Google Scholar
  24. [24]
    P. R. Bevington, K. D. Robinson. Data Reduction and Error Analysis for the Physical Sciences, 3rd ed., New York, USA, USA: McGraw Hill, 2003.Google Scholar
  25. [25]
    O. Baris, L. Ayala, W. W. Robert. Numerical modeling of foam drilling hydraulics. The Journal of Engineering Research, vol.4, no. 1, pp. 103–119, 2007.Google Scholar
  26. [26]
    E. Karstad. Time-dependent Temperature Behavior in Rock and Borehole, Ph. D. dissertation, University of Stavanger, Norway, 1999.Google Scholar
  27. [27]
    M. Zamora, S. Roy, K. S. Slater, J. C. Troncosco. Study on the volumetric behavior of base oils, brines, and drilling fluids under extreme temperatures and pressures. SPE Drilling and Completion, vol. 28, no. 3, pp. 278–288, 2013.CrossRefGoogle Scholar
  28. [28]
    H. J. Ramey Jr. Wellbore heat transmission. SPE Journal of Petroleum Technology, vol. 14, no. 4, pp. 427–435, 1962.CrossRefGoogle Scholar
  29. [29]
    J. Hagoort. Rameys wellbore heat transmission revisited. SPE Journal, vol. 9, no. 4, pp. 465–474, 2004.CrossRefGoogle Scholar
  30. [30]
    C. S. Kabir, A. R. Hasan, G. E. Kouba, M. Ameen. Determining circulating fluid temperature in drilling, workover, and well control operations. SPE Journal of Petroleum Technology, vol. 11, no. 2, pp. 74–79, 1996.Google Scholar
  31. [31]
    E. Kárstad, B. S. Aadnoy. Analysis of temperature measurements during drilling. In Proceedings of SPE Annual Technical Conference and Exhibition, SPE, San Antonio, USA, pp. 381–391, 1997.Google Scholar
  32. [32]
    M. B. Villas Boas. Temperature profile of a fluid flowing within a well. In Proceedings of SPE Latin America Petroleum Engineering Conference, SPE, Rio de Janeiro, Brazil, 1990.Google Scholar
  33. [33]
    W. H. McAdams. Heat Transmission, 3rd ed., New York, USA: McGraw-Hill, 1954.Google Scholar
  34. [34]
    C. F. Colebrook, C. M. White. Experiments with fluid friction in roughened pipes. In Proceedings of the Royal Society of London, Series A, Mathematical and Physical Sciences, vol.161, no. 906, pp. 367–381, 1937.Google Scholar
  35. [35]
    A. Whittaker. Theory and applications of drilling fluid hydraulics. The EXLOG Series of Petroleum Geology and Engineering Handbooks, Netherlands: Springer, 1985.CrossRefGoogle Scholar
  36. [36]
    J. D. Hedengren, R. A. Shishavan, K. M. Powell, T. F. Edgar. Nonlinear modeling, estimation and predictive control in APMonitor. Computers and Chemical Engineering, vol. 70, pp. 133–148, 2014.CrossRefGoogle Scholar
  37. [37]
    O. N. Stamnes, J. Zhou, G. O. Kaasa, O. M. Aamo. Adaptive observer design for the bottomhole pressure of a managed pressure drilling system. In Proceedings of the 47th Conference on Decision and Control, IEEE, Cancun, pp. 2961–2966, 2008.Google Scholar

Copyright information

© Institute of Automation, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Petroleum Engineering DepartmentUniversity of StavangerStavangerNorway

Personalised recommendations