Mitigating Gas Migration Using Foamed Cement on Shallow Thermal Wells in Northeast Alberta
Bibliographic record
Abstract
Abstract A foamed cement solution was designed and implemented to cement shallow intermediate casing strings in a heavy oil play in Northeast Alberta after conventional area-specific cementing solutions could not prevent surface casing vent flows. Analysis of the challenging well parameters that led to flowing gas identified why conventional solutions were not able to solve the issues. Foamed cement was pursued as a better technical solution and ultimately led to its successful placement in the field. The two primary challenges for cementing these wells was first ensuring full cement annular coverage around the pipe in a large hole that was deviated at 45° right from surface, and secondly to prevent gas flow through optimization of slurry compressibility, gel strength and viscosity as very little hydrostatic pressure and low well temperatures were present. The process of introducing foamed cement involved lab testing to obtain desired cement properties, computer simulations to verify expected pressures and calculate nitrogen concentrations for each section of the wellbore, and finally operational procedures to ensure jobs were completed successfully. Analysis of the conventional job design methodology and the results in the field that continually led to well failures will be described. The advantages of foam cementing will be reviewed leading to the new project design consisting of lab testing and simulation outputs. Next, the foam job design procedure was created to ensure rates and pressures would be sufficient to place the cement effectively while not inducing losses due to the higher viscosity of foamed cement and relatively low fracture gradient. Several cement jobs were analyzed for key success metrics during the pumping phase, including observations and challenges with areas for future improvement. Results of conventional cemented wells will be compared to those cemented with foamed cement looking at economics, operational complexity and ultimately well integrity. Several key conclusions are made to suggest foam cementing solutions should become a standard practice in the area and not remain a last resort. This project introduced foam cementing to very shallow thermal wells which have not typically been treated with foamed cement. Significant technical & operational hurdles were overcome to confirm proper well control and ensure the energized cement could be pumped safely and effectively. The resulting key learnings and suggested best practices will be shared.
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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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".