Automated Monitoring of Torque and Drag in Real-time

Research output: ThesisMaster's Thesis

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Abstract

Torque and drag are two parameters in the well construction process that deserve special concern, as they are ever-present factors during drilling and tripping operations. Especially todays increase in drilling and completing highly inclined and extended reach wells, often results in situations where these drilling parameters are pushed to their limits. Everyone involved in the well construction process needs to be aware of the challenges resulting from excessive torque and drag. Due to the difficult well paths to be drilled, stuck and lost pipe situations may be encountered more easily, but need to be avoided at all costs. As a consequence, detailed monitoring of torque and drag is a key element in the successful construction of a planned well path. Although this is already done in an excessive manner, the important parameters to enable a reduction of lost and hidden lost time are still taken manually and inconsistently. These parameters that need to be tracked are hook load, while drilling and running in respectively out of the hole, as well as torque, during pipe rotation. Trend analyses, based on this manually process, for wellbore health status evaluation, are still uncommon. In order to improve the monitoring process, it is essential to make use of the mudlogging sensor data combined with an automated algorithm, recognizing the ongoing rig operations. An improved approach of tracking torque and drag in real-time, as well as the newly developed software application for this purpose, are described throughout this thesis. In addition, already available monitoring approaches have been evaluated and discussed, based on their advantages and limitations. The main principle behind the used technique is a hook load and torque comparison of actual versus planned (simulated) values. These actual values are calculated for different operations (drilling, tripping, running casing, etc.) on a stand per stand basis and plotted over the measured depth of the bit. The resulting trend analysis that can be performed, allows identification of upcoming critical situations at an early stage. Based on this information, the drilling crew is able to react immediately by executing the appropriate counteractions, and expensive lost time situations can be prevented thereof. In advance, wellbore conditioning operations can be optimized based on the quality of the wellbore, which is evaluated without interfering ongoing rig operations.
Translated title of the contributionAutomatische Überwachung von Torque und Drag in Echtzeit
Original languageEnglish
QualificationDipl.-Ing.
Awarding Institution
  • Montanuniversität
Supervisors/Advisors
  • Thonhauser, Gerhard, Supervisor (internal)
Award date3 Apr 2009
Publication statusPublished - 2009

Bibliographical note

embargoed until null

Keywords

  • torque drag friction factor real-time operations recognition hook load

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