Design and Development of an Engineering Drilling Simulator and Application for Offshore Drilling for MODUs and Deepwater Environments
Bibliographic record
Abstract
Abstract Unmitigated vibrations in drillstrings, Bottom Hole Assemblies (BHA) and related drilling components can cause significant financial losses and safety problems for drilling in deepwater environments. A drilling laboratory has been developed at Memorial University to study the effect of vibration on drilling performance. The distinctive capability of the simulator is that it utilizes closed loop control of hydraulic actuator, pneumatic actuators and variable speed motors to simulate complex drillstring, bit-rock, and drilling rig interactions that translate to axial and torsional vibrations and compliances. For offshore drilling simulation, the facility can apply low-frequency heave vibration as experienced by offshore drilling units, and higher-frequency vibration arising from drillstring motions, downhole tools or bit-rock interaction. The laboratory apparatus has a short, very stiff drillstring due to space constraints; however, the simulation system is able to re-create vibration arising from a much more compliant significantly longer drillstring, potentially thousands of meters in length. Hardware-in-the-Loop (HIL) system is designed as follows to make the laboratory drillstring behave like the lower portion of a deep-well BHA. A load cell records dynamic bit-rock interaction force, and uses it as the input to a high-fidelity nonlinear computer model of a full drillstring. The computer model predicts resulting bit motion, and the laboratory drill rig actuators apply that motion to the physical bit. If a deep well drillstring would be exhibiting bit bounce or stick-slip under certain conditions, then the bit in the laboratory will have the same motion. The effect of vibration mitigating measures such as changing WOB or RPM can then be investigated. Prior to implementation into the physical apparatus, the HIL, drillstring computer model and control algorithms were tested and refined through control simulation, as outlined in this paper. For these simulations, the physical rig is represented by a computer model, the "virtual rig". The virtual rig bit force is recorded and used to drive the deep-well drillstring simulation, which returns a predicted bit position at each time step. A controller generates a command signal to the virtual rig hydraulic actuators to drive the bit to the desired position. The results show that the short, stiff laboratory drillstring behaves like a deep well drillstring through use of HIL. The usage of the physical drilling simulator is expected to answer industry and academia questions on drilling vibration issues, mitigation measures for which would be impractical, if not impossible, to test through full-scale field trials. The authors feel that the drilling laboratory system and controller, for which the proof-of-concept is validated in this paper, is unique in its capability to integrate dynamic models of BHA, drill pipe, Mobile Offshore Drilling Unit (MODU) subsystems, and ocean environmental conditions in an HIL environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".