New Thermally Responsive Cement for Heavy Oil Wells
Bibliographic record
Abstract
Abstract Canada’s oil sands are one of the world’s largest hydrocarbon resources. The initial volume of crude bitumen in place is estimated to be approximately 260 billion cubic metres with 11 percent or 28 billion cubic metres recoverable under current economic conditions. Continually improving economics, bolstered by recent higher crude oil prices, has resulted in the International recognition of the vast potential of Canada’s oil sands. Based on publicly announced development plans through to 2015, over C$60 billion could be invested in numerous projects to develop the oil sands. Various factors have to be considered to select the proper cement for zonal isolation of thermal recovery heavy-oil wells. First the cement should be flexible enough to withstand the stresses which occur when casing expands during the heating up of the well. To reduce these stresses, the cement thermal expansion coefficient should be similar to the thermal expansion coefficient of the casing. Finally, cement mechanical properties should not degrade during the whole steam injection process, i.e. when it is subjected to extremely high temperatures (up to 350 degC) for extended periods of time. Specifically in Canada, the majority of the steam injection wells are drilled in shallow sandstone formations. This requires the cement to have high flexibility to resist the stresses. Moreover, during steam injection, a reaction between the sandstone formation and the cement sheath may occur, impacting the cement matrix and hence changing its properties. This paper describes the application of a new thermally responsive cement for zonal isolation of heavy oil wells in Canada. This system is designed to have excellent strength, flexibility and thermal properties even upon interaction with sandstone formations. It minimizes the mechanical stresses exerted on the cement sheath during steam injection, thus reducing the risk of loss of well integrity. The numerical simulations performed with these long-term material properties (six months of exposure to 350 degC) for typical Canadian heavy oil wells conditions predict reliable and durable zonal isolation under these extreme conditions. These simulation results are confirmed by several field applications in wells which have not leaked after months of steam injection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".