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The Impact of Diagenesis and Compaction on Drilling Failure Detection

[+] Author Affiliations
Nur Suriani Mamat

Universiti Teknologi Malaysia, Johor Bahru, Malaysia

Paper No. OMAE2017-61858, pp. V008T11A007; 11 pages
doi:10.1115/OMAE2017-61858
From:
  • ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering
  • Volume 8: Polar and Arctic Sciences and Technology; Petroleum Technology
  • Trondheim, Norway, June 25–30, 2017
  • Conference Sponsors: Ocean, Offshore and Arctic Engineering Division
  • ISBN: 978-0-7918-5776-2
  • Copyright © 2017 by ASME

abstract

An important problem during drilling operation is wellbore instability; a complex problem caused by mechanical and chemical related factors. Even the best drilling practice could evade small instability problems that later may become irreparable. The risk of wellbore stability is mostly related to drilling, tripping and reaming activity with, including lost circulation, sloughing repair and loss of penetration. In this paper, the impact of historical and state of diagenesis and compaction on borehole instability has been studied, systematized, and used for general modelling. All the concepts are presented as symbolic concepts in a hierarchical order and linked in a chain of cause-effect relationships to wellbore failures. Through surveillance of drilling parameters, diagenesis and compaction were identified through formation hardness, well depth, shale type, and cuttings/cavings characteristic. From the analysis, kaolinite, which normally exists in intermediate diagenesis, is most likely to cause bit balling when hydrated. Smectite, which is water-sensitive clay, would cause chemical wellbore instability in water-based mud. Carbonates formation such as dolomite and limestone is more likely to result in lost circulation as compared to shale. Our work demonstrates how state of diagenesis and compaction could influence wellbore instability condition. This knowledge could be applied to understand the behavior of rock formation being drilled and would influence the prediction of probable failures as an end result. The method presented here integrates theoretical knowledge and real-time drilling data to envisage the most likely failure.

Copyright © 2017 by ASME

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