Economic Recovery of Gulf of Mexico Shelf Reserves Using an Integrated Approach to Well Services
Bibliographic record
Abstract
Abstract Economic recovery of shelf reserves in Gulf of Mexico asset has been made more efficient by using a rig-less, through-tubing (RTT) completion equipment package. The package integrates all services and personnel needed for the completion and charges on a day rate-plus-material basis. The RTT approach has been used to repair wells that have developed sand-control issues and still have justifiable reserves to recover. The techniques can be used in abandonment of depleted zones and completing untapped zones. The equipment package is modular and adaptable to each well's needs, and all personnel concerned have experience in multiple disciplines. The added benefit is a single, simplified invoice; compared to multiple invoices as is the case when using discrete services. The equipment packaging and day rate-plus-materials (DPM) pricing structure allows for a more accurate estimation of cost and reduces unplanned variable costs. There is a lower delivery cost using dual-purpose equipment and multiple-discipline personnel, which has the added benefit of optimizing manpower and equipment needs while decreasing exposure to hazards. Based on the economic drivers of the project, new technology can be implemented, further improving either time savings, increasing reserve recovery, or both. All of the above factors allow for real-time cost-tracking, enabling decision-making based on the current status of the project. The primary focus of the paper is on remedial completions and workovers to install an economically viable form of sand control for the latter-day producing life of the wells. Case histories demonstrate how the application of this approach has proved to be the preferred method and a viable means to repair sand-control problems for producing zones, complete new zones, and abandon depleted zones for many wells in the Gulf of Mexico Shelf.
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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".