Achieving Extending Squeeze Life in Challenging Wells - A Non Conventional Approach
Bibliographic record
Abstract
Abstract Over the past 10 years significant improvements in "green" scale inhibitor chemistries have led to considerably increased use in certain regions, notably the Norwegian sector of the North Sea. However, the use of these more environmentally acceptable products can be at the cost of optimum performance. This was the case for the Varg field: an extensive Best-In-Class re-selection of available yellow / green polymeric inhibitors failed to achieve the required improvement in lifetimes. Modelling work conducted for one of the wells had also shown that one of the primary causes of the poor lifetimes was the lack of effective placement of the treatment chemical in the water-producing zones.1 More recent experimental work to be described in this paper has demonstrated that the scaling challenges on this field could be mitigated in part by adopting the less environmentally friendly, but better retaining, ‘red’ phosphonate chemical. Comparison of the predicted inhibitor return profile using laboratory derived data with the subsequent field return showed very good correlation in a well with no placement challenge. In a manner analogous to the polymer-based chemistries,1 application of the phosphonate inhibitor in a well with known placement issues gave less impressive return lifetimes. However the better retention properties meant that the treatment lifetimes remained acceptable despite the poor placement. When the placement issues were taken into account, the previously derived isotherm proved very effective at simulating the field case in this more challenging well. This paper therefore describes an alternative, more rigorous approach to simulating treatments in challenging wells rather than using history matched averaged field return isotherms. The paper then shows the impact on optimisation of future treatments when the different approaches are examined. This work therefore expands considerably on that previously described in SPE 114077.
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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 | 0.000 |
| 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".