An evaluation of the reduction of heat loss enabled by halloysite modification of oilwell cement
Bibliographic record
Abstract
Abstract The increasing reliance on steam-assisted gravity drainage (SAGD) to access unconventional bitumen deposits within the sub-Arctic necessitates the development of robust cement sheaths for oilwell cementing. Such cement sheaths can potentially increase the energy efficiency of the SAGD process by reducing heat loss while maintaining mechanical integrity upon prolonged exposure to cyclic thermal stress. Modifying oilwell cement by the inclusion of hydroxyethylcellulose-functionalized halloysite nanotubes (HEC-HNTs) within the cementitious matrix results in a high density of enclosed void space and disparate interfaces, which serve to scatter phonons and reduce thermal conductivity. In this study, we have systematically evaluated the influence of HEC-HNT loading on the thermomechanical properties of cement with and without the addition of calcium chloride as an accelerator and have correlated the reduction of thermal conductivity to the distinctive microstructure of the nanocomposite cement. The incorporation of HEC-HNTs in thermal cement reduces the thermal conductivity from 0.856 W m −1 ·K −1 to 0.206 W m −1 ·K −1 without substantially altering the compressive strength. Model systems mimicking SAGD oilwell cement sheaths have been prepared from umodified and modified (incorporating HEC-HNT) cement and subjected to cyclic thermal stress emulative of SAGD conditions. Cement sheaths constructed from the modified cement with CaCl 2 maintain a higher temperature gradient as compared to unmodified cement with CaCl 2 ; a 12 °C increased temperature differential between hot and cold surfaces is observed for a 4.5 cm thick sheath with a considerably shallower rate of increase in temperature. Aggressive thermal cycling (20 h at 250 °C followed by 4 h at 25 °C) for 20 days brings about a 20% reduction of compressive strength. The combination of additives facilitating thermal insulation and mitigating differential shrinkage provides an attractive means of oilwell cementing for SAGD applications wherein cyclic thermal stresses are operational and energy efficiency is of paramount importance. Extrapolating the considerably increased temperature differentials between hot and cold ends within model systems to entire wells portends significant energy savings and reduction in amounts of injected steam.
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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".