Mitigation of Mineral Scale Deposition in Well-Bore and Flow Lines with Eco Friendly and Less Aggressive Chemical
Bibliographic record
Abstract
Abstract With the onset of water production, mineral scale deposition appears in the oil and gas wells. The scale deposition in wellbores and flow lines is a universal challenge that has to be addressed with technical and economical effectiveness. Efforts are ongoing to effectively inhibit the scales or remove them through chemical or mechanical means. Kuwait Oil Company is planning to improve the production to 4.0 MM BOPD by the year 2020. In this pursuit, all the possible efforts are made to increase production including application of new technology in drilling, completion, well production and facilities. One of the key aspects of production improvement from individual wells is to avoid any obstruction in the wellbore, wellhead and flow lines that might affect the smooth flow of hydrocarbons. This includes the augmented steps on eliminating mineral deposition from wellbore and flow lines. The wells are suffering from frequent scale deposition in wellbore and flow lines. Usually these problems are mitigated by using strong acid. However, due to maturing of field the wells are generally completed with ESPs. When acids like HCl are used, these ESPs are corroded severely adding extra cost of workover and production loss. This challenge is driving the operators to use less aggressive chemicals that remain environmentally friendly and can maintain the integrity of submersible pumps, metallurgy of the flow lines and other components. To meet this challenge, various chemicals were evaluated through laboratory tests and case histories. The chemical composed of Glutamic acid was selected for the first pilot. The pieces of tubular and other well components suffering from scale deposition were tested in the lab and the results were found to be highly encouraging. Based on this a pilot campaign was initiated with a batch of eight wells to treat wellbore and flow lines. All the treatments were found highly successful. Due to this treatment, the daily production has been improved to 5,000 BOPD without any extra activity such as replacement of ESP or flow line tubing due to corrosion. The paper presents the technology evaluation process, lab testing and field trial results.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".