Application of Advanced Mass Spectroscopy Techniques for Improved Scale Management in Conventional and Sub-Sea Fields
Bibliographic record
Abstract
Abstract An essential part of any scale squeeze management strategy for any oilfield is the capability to accurately and precisely determine the residual scale inhibitor concentration in the produced fluids. This data in combination with ion analysis, suspended solids and productivity index is essential to determine the lifetime efficiency of scale squeeze treatments. In recent years the stricter environmental regulations in the North Sea, coupled with the development and operation of more complex fields in harsh scaling environments, has led to increased use of environmentally friendly polymeric scale inhibitors. The accurate and specific analysis of polymeric scale squeeze inhibitors is known to be difficult and has led to the development of a toolbox of advanced scale inhibitor analysis techniques based upon liquid chromatography with mass spectrometric detection (LC-MS). These methods offer the potential to improve scale management capability in conventional and sub-sea fields through improved scale inhibitor detection at low levels. In addition, mass spectrometric detection provides the ability to selectively detect chemical functional groups, contained within polymeric scale inhibitor molecular structures, which were previously not distinguishable. This is a distinct advantage for multiple scale inhibitor analysis capability in produced brines as certain chemical groups can now be used as tags without having to modify the chemistry of commercially available inhibitors. The ability to detect polymeric scale inhibitors at very low MIC <1ppm with improved confidence has the potential for significantly extending scale squeeze lifetimes. In addition, this has now allowed highly efficient polymers to be used in field situations where scale squeezing had either been stopped or the lifetime was significantly compromised because of the lack of confidence in the scale inhibitor return profiles and the interferences from background reservoir Phosphorus or topside scale inhibitors. Specific examples from North Sea fields, including both sub-sea and platform wells, will be presented where the scale management has been significantly improved through the application of the advanced LC-MS techniques. In addition, the use of the LC-MS techniques targeting specific chemical groups as molecular tags to enable multiple scale inhibitor detection for a range of quaternary amine acrylic co-polymers will be presented.
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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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".