Simulation Technology To Assess ROV Operations at an Early Planning Phase
Bibliographic record
Abstract
Abstract This paper documents the use of Vortex simulation technology and vSIT methodology used for the design of the subsea production system (SPS) for the Laggan-Tormore gas condensate fields west of Shetland. Subsea operations in these extreme weather conditions are very technically challenging, and simulation tools have been developed for verifying full and safe ROV access and operability throughout SPS development. Introduction This paper documents the use of Vortex real-time dynamics simulation as part of the detailed design of the subsea production system (SPS) for the Laggan-Tormore gas condensate fields west of Shetland. The two fields are developed and operated by Total E&P UK Limited along with its joint venture partner DONG E&P (UK) Limited. The SPS, situated at 600 m (1,968 ft) water depth, is designed and procured by FMC Technologies. It includes two 6-slot Template Manifolds, one Satellite Well Protection Structure and 9 Subsea Trees (XT), and is very technically challenging due to extreme weather conditions. To be able to verify full and safe ROV access and operability throughout SPS development, Total commissioned the use of a ROV simulator. This resulted in CM Labs, FMC Technologies Schilling Robotics and FMC Technologies combining to develop a desktop software ROV simulation tool. Examples of simulated operations include umbilical end termination and well jumper installation, XT installation and subsea control module change-out. Thirty-seven operations have been simulated on two working sites of the Laggan-Tormore fields (one Template and one Satellite) in order to verify planned operations from an engineering perspective, including analysis of custom equipment design. By simulating interventions using state-of-the-art simulation software, we were able to allow ROV operators to interact with the simulated environment (as opposed to preset motion planning). Simulating the dynamic interactions between the ROV, ROV tooling and the subsea equipment enables understanding of operations beyond what is achievable with purely kinematic animation. This has the considerable benefit of giving the project team an early opportunity to assess any issues that may be encountered as part of the offshore installation campaign. This approach allows the ROV operator to evaluate the potential for unforeseen impediments that may cause unnecessary delay, or at worst render the operation unfeasible. Being able to assess the installation operations before the physical interface check is completed during the traditional Site Integration Testing (SIT) also allows the equipment provider time to make any required design changes before manufacturing is completed. In order to support this process, a workflow has been implemented, encompassing procedure descriptions, storyboards, mission recordings, and reporting of discovered issues. This workflow enables iterative refinement of the simulation results and a pipeline of work output.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".