A Novel Delivery Method for Combined Scale Dissolver and Scale Squeeze Treatments in Non-Isolated Subsea Wells
Bibliographic record
Abstract
Abstract The Chestnut field produces from two subsea, non-isolated commingled wells tied back to the Hummingbird FPSO. A steep decline in production was observed in Q1 of 2014 in well 22/2a-11x which was attributed to the formation and deposition of barium sulphate scale in the well and confirmed through a new method developed for the determination of seawater breakthrough onset in commingled wells (Chen 2015). Following this, an elevated temperature barite dissolver treatment was designed so as to try and remove the scale and allow for a subsequent scale squeeze treatment to be applied. Deployment of the dissolver and scale squeeze treatments, however, presented several challenges, the main one being that the 22/2a-11x well cannot be mechanically isolated from the other well in the field for a treatment to be bullheaded. In addition, the common flowline was known to contain sand and the well's xmas tree design and vicinity to the FPSO meant that any chemical treatments needed to be delivered down the production riser; the limited deck space on the FPSO rendered this a particularly complex operation. A supply vessel had to be modified to accommodate mixing, storing and heating capabilities, with heated dissolver being transferred to the FPSO via a suitably rated hose over open water. A unique delivery approach was developed to allow the successful placement of the scale dissolver and scale squeeze treatments in well 22/2a-11x through the use of a non-aqueous liquid "plug" in the common flowline; the combined treatments led to a doubling in the well's production compared to oil rates prior to the intervention. This paper presents the difficulties associated with delivering these multistage treatments and the applied engineering solutions that enabled effective placement of both the scale dissolver and scale squeeze in this subsea well. In addition, lessons learned in the process as well as an evaluation of the placement strategy on the efficiency of the scale removal and squeeze treatments will be discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".