Effective Application of Solid Expandable Tubular During the Enhancement of Heavy Oil Recovery in China, Lessons Learned and Experience Shared
Bibliographic record
Abstract
As the traditional thermal recovery became less effective in exploring the heavy oil reservoirs, some newly developed techniques such as chemical flooding, SAGD and HDCS are demonstrating their advantage in the recovery process in China. However, the ever increasingly used new techniques often compromised severely the well integrity as the flow of extremely high temperature fluid or gas caused quick damage to casing, leaving the wellbore less reliable. This compromise requires urgently a workover strategy that would maximize the well’s life span and guarantee the effectiveness of new techniques. Solid expandable tubular (SET) was field-proven in casing patching activities, but its application in the heavy oil recovery has not been attempted due to severe temperature challenge. We made innovations on the traditional structure of SET and got valuable results. The tubular after expansion was integrated with the original casing as a whole and the rubber was removed in-between, the wellbore size was maintained utmost and the casing was further strengthened. Meanwhile the expansion cone was put outside the tubular which is a big step forward in SET structure. Indoors experiments demonstrated sound performance of the new structure in the simulative temperature of 350 ℃, the plan for the field application was optimized based on the lessons collected in this experiment. High temperature well applications by SET were carried out in Liaohe oilfield which is famous for its heavy oil resource in China, and the detailed process as well as the outcome were compared and analyzed, finally the conclusions were drawn as a result of the whole study. We expect our work will help expand this enabling technology to better facilitate the enhancement of heavy oil recovery and maintain solid well integrity during the heavy oil production. Key words : Solid expandable tubular; Heavy oil recovery; China
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".