A Novel, Chemistry-Based Approach to Fluid Diversion in Hydrocarbon Based Paraffin Solvent Treatments
Bibliographic record
Abstract
Abstract Paraffin deposition is a commonly experienced problem throughout the petroleum industry, and especially in certain reservoir fluids found in the Western Canadian Sedimentary Basin (WCSB). As hydrocarbons are produced from the relatively high pressure and temperature found in the reservoir, fluids experience a thermal cooling, as well as significant pressure decreases. These alterations in the fluid thermodynamics can lead to the instability and eventual deposition of paraffins from the hydrocarbon matrix. As production continues, these paraffin deposits can result in significant flow impairment in downhole and surface facilities. Aromatic and aliphatic compounds are commonly used as remediation methods for the dissolution of these paraffins. However, one of the most significant challenges in ensuring an effective remedial treatment is maintaining optimal fluid placement. Given a lack of diversionary placement methods, fluids will preferentially take the path of least resistance. This path does not necessarily coincide with desirable solvent placement for optimum contact with the organic solids. Instead, expensive solvents can be rendered ineffective through a lack of contact. In order to counteract poor fluid placement, a variety of chemical and mechanical diversionary methods have been developed for use in acid or solvent treatments. Mechanical methods rely on tools or packers to force remediation fluids into the desired location. Chemical methods often rely on a viscosification to force remediation fluid from the path of least resistance into the desired areas. To date, the majority of chemical diversion methods have been utilized for acidization treatments, while hydrocarbon based solvents have largely relied on mechanical means of isolation. This paper will provide details on the development, laboratory testing, and case study of a novel chemical system intended to provide diversion for an aliphatic and aromatic based solvent. The use of a delayed viscosifying agent can be custom tailored for each individual wellbore scenario, allowing for optimal fluid placement.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".