Effect of Dynamic Loading on Wellbore Leakage for the Wabamun Area CO2 Sequestration Project
Bibliographic record
Abstract
Abstract To permanently remove CO2 from the atmosphere large scale injection of CO2 from stationary sources such as coal fired power plant and heavy oil production into brine filled formation is seen as one of the most viable options. One of the main risks identified with storing CO2 into the subsurface is the potential for leakage through existing wells penetrating the cap rock. The wellbore system has several components which can fail and create leakage paths such as type and placement of wellbore casing and cements, completion method, abandonment and wellbore expansion or contraction by changes in temperature and pressure. Of the 1000 wells in the study area near Lake Wabamun, Alberta 95 wells penetrated the immediate cap rock above the proposed Nisku injection formation and was identified as potential leakage pathways. The leakage risk of these wells was evaluated based on the knowledge of well design, current well status and historical regulation’s in the area. For the subset of 27 well studied on only 4 wells were identified as wells requiring work over which was less of a problem than anticipated. To evaluate the risk of creating leakage paths by thermal and pressure changes caused by CO2 injection, a three dimensional finite-element model was built which used elasto-plastic material models for cement and formation. Multi-stage simulations for casing-cement and cement-formation interactions with temperature enabled elements were conducted. Because of the uncertainty on cement properties in old wells, a parametric study of cement properties was conducted. The simulation results indicated that thermal cooling might reduce near-wellbore stresses which will increase risk of integrity loss in casing-cement and cement-formation. The parametric study reviled that the risk of debonding and tensile failure will increase with increasing Young’s modulus and Poisson’s ratio of the cement under dynamic loading conditions. In addition, low mechanical cement strength will increase risk of shear failure in the cement.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".