Formulation of an Emulsified Thermal Acid Blend for SAGD Applications in Eastern Alberta
Bibliographic record
Abstract
Abstract Conventional emulsified acids composed of a strong mineral acid and an aromatic solvent, such as xylene, are commonly used to stimulate both water injection and production wells. When this system is properly applied, it is effective in dissolving organic and inorganic deposits, and in stripping off layered scales that may be deposited onto the inner surface of the tubing. Until recently, application of this system has been restricted to conventional reservoirs: however, with proper compatibility and corrosion testing, the emulsified acid system can be used to successfully stimulate thermal heavy oil reservoirs. Thermal heavy oil wells often exhibit significant calcite scaling on the long horizontal slotted liner, as well as an emulsion of low API oil dispersed in an aqueous mixture. Previous treatments using 1% HCl acid or 5% Acetic have addressed the issue with scaling. However, the issue with the heavy oil emulsion remained unresolved. By using a high temperature emulsified organic acid, both calcite scale and heavy organic deposits can be removed along the length of the slotted liner. 5% or 10% acetic acid emulsified in a 4:1 ratio with a modified wax and asphaltene solvent blend, in conjunction with a liquid organic acid corrosion inhibitor and an emulsifying surfactant, have proven to be an effective treatment in the remediation of scales and build up of organic deposits. Also, the blend is designed to maintain sufficient corrosion protection despite the high temperature environments that are characteristic of thermal heavy oil wells. This paper details the acid compatibility testing procedure, corrosion testing, and subsequent analysis that were required to formulate this specialized acid blend.
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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) | 0.000 | 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) | 0.001 | 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".