Automated Real-Time Hookload and Torque Monitoring
- Richard Josef Werner Kucs (OMV E&P GmbH) | Hermann F. Spoerker (OMV Exploration/Production Ltd) | Gerhard Thonhauser (TDE Thonhauser Data Engineering GmbH) | Philipp Zoellner (TDE)
- Document ID
- Society of Petroleum Engineers
- IADC/SPE Drilling Conference, 4-6 March, Orlando, Florida, USA
- Publication Date
- Document Type
- Conference Paper
- 2008. IADC/SPE Drilling Conference
- 1.6.10 Running and Setting Casing, 1.10 Drilling Equipment, 1.7.7 Cuttings Transport, 4.1.2 Separation and Treating, 1.10.1 Drill string components and drilling tools (tubulars, jars, subs, stabilisers, reamers, etc), 1.6.1 Drilling Operation Management, 1.12.6 Drilling Data Management and Standards, 1.6.6 Directional Drilling, 1.6 Drilling Operations
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Today important parameters to enable a reduction of lost and hidden lost time during drilling, like hook loads for pulling and slacking off the drill string, and torque for drill string rotation, are still taken manually. Analysing torque trends during drilling and reaming is hardly done.
A key to reduce lost and hidden lost time by analysing drilling data is to automatically recognize ongoing operations in real time from this data. That allows the automatic identification and picking of pulling-up; slacking-off and rotating hook loads, as well as torque values without spending extra time or work force. Relevant parameters can be sampled and analysed automatically in real time from the rig sensor data stream without interfering drilling operations.
This automated process allows monitoring changing torque and drag trends for each stand of drill string moved during drilling, tripping, or reaming operations. To monitor trends in the torque and drag development in real time, parameters may be combined with simulated hook load and torque curves in a graphical way. Simulated values are imported from engineering applications. This allows the user to react immediately, not only after hand taken values are manually entered into a graph. The possibility to broadcast all the data to computers worldwide enables a great level of cooperation.
Instant measures against increasing torque and drag can be taken before reaching critical ranges on a stand per stand basis. Also excessive reaming and washing can be avoided as low torque and drag may be an indication for a good hole quality. This can save wellbore treatment time.
The paper presents the development of the system, its validation against live well data from recent 20,000ft wells in the Vienna basin and the planned application of the system on an extended reach field development project offshore New Zealand.
OMV is planning a campaign of 9 extended reach wells in the Maari field offshore New Zealand. When drilling extended reach wells, two major issues will have to be addressed as part of the preparation work for the project . On one hand this is torque and drag, on the other it is the evaluation of measures to manage adequate cuttings transport.
A workflow and system should be developed to help the drilling team on the rig-site and in the remote operating center to collaborate to manage these challenges. A requirement was a highly automated handling of the data and the automatic generation of the required real-time input values. Furthermore, the possibility of the on-shore support team to support the rig in a way, that the rig team can focus on the drilling process without human intervention in the system from their site, was a requirement.
The aim was to generate
- pulling up,
- slacking off, and
- rotating off bottom
hook loads automatically and to overlay expected torque and drag values with such measurements graphically. Based on a trend analysis conclusions on the wellbore health status can be made.
Using automated operations recognition it should furthermore be possible to evaluate wellbore treatment time to optimize flat times and utilize reaming and washing as well as circulating efforts in the best possible way (Fig. 1, Fig. 2).
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