Enhanced Scale Inhibitor Placement by Gravity Slumping In High-Permeability Horizontal Wells - Draugen Field, North Sea
Bibliographic record
Abstract
Abstract This paper examines the impact on scale squeeze life of water/scale inhibitor re-distribution during extended shut in periods for bullhead scale treatment in a high permeability reservoir. The Eclipse 100 reservoir simulator was used to examine water re-distribution (gravity slumping) during extended shut in periods for horizontal wells in the Draugen reservoir. The work shows that in certain cases involving long horizontal wells (>1000 ft) in high permeability sands (3-5D) with low vertical/horizontal permeability contrasts, extensive water re-distribution can occur during extended shut-in periods owing to density differences between the injected (aqueous) fluids and the formation fluids. Full field reservoir modelling was then carried out to identify candidate wells within the Draugen field which offered greatest potential for improved chemical placement based on these findings. Near wellbore placement modelling was then conducted to optimize squeeze return lifetimes using gravity re-distribution to improve placement deeper (lower) in the reservoir vs. convention scale squeeze design methods such as larger overflush. The work demonstrates that for selected cases, gravity re-distribution can be used to improve placement deeper (lower) in the near wellbore area. The modeling work also identifies limitations with the simple "radial" near wellbore models for such cases and identifies those wells in the Draugen field which would benefit from such treatments. An added benefit for low water cut wells was the potential to minimise post treatment lift issues associated with the injection of high volumes of water into the near wellbore for aqueous squeeze treatments, by allowing the injected aqueous treatment to sink away from the near wellbore area. New field treatments have therefore been designed based on the work described. The economic impact of the extended shut in times vs. improved squeeze treatments and deferred oil costs for this field case are also discussed following the field applications.
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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) | 0.004 | 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".