The Development of a Scale Management and Monitoring Program for a High-Temperature Oil Field During the Production-Decline Phase of the Life Cycle
Bibliographic record
Abstract
Abstract This paper presents field results from scale squeeze treatments carried out on platform wells within a high temperature (150C) field in the Norwegian sector of the North Sea. Scale control and the resulting squeeze treatments to production wells were highlighted as the most expensive item in the production chemical budget. The development of a cost-effective squeeze and monitoring policy has been critical to reducing the operating cost of this asset as the produced water cut rose. The decision to use both aqueous and emulsified scale inhibitor for treating these high temperature production wells was arrived at after an extensive series of laboratory tests including formation damage coreflood studies and an assessment of chemical retention at this elevated temperature. The field data from these wells will be presented comparing treatment lifetimes and clean up rates between conventional treatments and the novel emulsion technology A key factor to the success of such treatment is an understanding of chemical placement and the effectiveness of the treatment chemicals. Evaluation of residual chemical concentration or scaling ion chemistry has long been used in monitoring programs and more recently probes have been developed which increase the rate of evaluation/interpretation. All these monitoring methods prove that the chemical is present in the brine when sampled or that scale formation is not occurring at the point of brine analysis. This paper outlines the experimental methods developed to evaluate the suspended solids collected from the produced brine by environmental scanning electron microscope (ESEM) and the associated brine chemistry to evaluate the scale risk within the produced fluids. The combination of these methods has improved the integrated scale management program in terms of evaluating scale squeeze placement effectiveness, squeeze lifetime and provides the confidence t0 extend the period between scale squeeze treatments. Also, and in some cases treatments were stopped where brine analysis alone would have suggested further scale squeeze applications were required.
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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".