Running Fairings for Deepwater Drilling in the Gulf of Mexico - A Cost-Benefit Approach to Deciding the Faired Length
Bibliographic record
Abstract
Abstract The decision to run fairings on drilling risers is critical in terms of the additional cost to run fairings versus downtime cost from suspended operations due to current conditions causing excessive flex-joint angles. Making an informed decision, enhanced by actual predicted current conditions for a drilling program, is a valuable capability in planning to maximize drilling uptime and minimize downtime costs. This paper presents an innovative model which has been developed as a rational decision tool for determining the fairing requirements to mitigate predicted loop current events for proposed drilling programs in the Gulf of Mexico. Introduction The Fairing Optimization Model provides an innovative approach to fairing length requirements based on an evaluation of the cost and benefits of running fairings for a planned drilling program. The model has been applied to several rigs under contract to ChevronTexaco. It provides the operator with a systematic approach to decide on limiting loop current conditions beyond which VIV(Vortex Induced Vibrations) suppression fairings will be required for a range of water depths in the Gulf of Mexico and to decide on the optimum number of fairings to run for a series of proposed drill sites. This model combines a loop-current eddy environmental prediction tool with results from an extensive analytical database of riser response. For a proposed drill-site, this model estimates the probability that a loop current eddy will adversely affect a proposed drill-site in terms of its severity and duration. An example model was developed for water depths ranging between 2,000ft and 9,000ft. The model clearly demonstrated that for a given drilling scenario and environmental forecast there exists an optimum (zero or non-zero) length of fairings below which cost of downtime exceeds the cost of running fairings and above which the cost of running fairings exceeds that of likely downtime. Methodology. The flowchart showing the steps taken to achieve an optimized fairing solution is given in Figure 1. The main steps to achieve an optimized solution are as follows:Riser Response AnalysisEddy PredictionFaired Length Optimization Riser Response To obtain an accurate representation of the riser responses in the field, it is important to model the riser according to the drilling contractor's operating philosophy. This entails using the actual riser properties, tensions, buoyancy distribution and mud weights that the contractor would use for a given drilling program. Once this data is collected, a load case matrix can be set up to encompass various water depths, top tensions, mudweights, and even vessel offsets. This allows for an extensive database of riser response to be created to emulate most drilling scenarios. The inclusion of a tension that represents the operating strategy of the contractor and varied vessel offsets is imperative because these two parameters are the most common methods used to mitigate VIV aside from auxiliary devices. An increased tension will damp out VIV motions and moving the vessel downstream will improve the upper flex joint angle to a certain extent. However, moving the vessel too far downstream will adversely effect the lower flex joint angle.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".