Effects of microannulus geometry and slurry particle size on squeeze cementing effectiveness
Bibliographic record
Abstract
Leakage in hydrocarbon wells often results from the formation of microannular gaps along cement-casing and cement-formation interfaces, ultimately compromising well integrity. Squeeze cementing, a common remedial operation, involves pumping a thin cement slurry under pressure into these gaps to restore integrity. However, despite its widespread use, the success rate of squeeze cementing remains relatively low, requiring successive attempts before leakage is eliminated. This is largely due to significant uncertainties regarding the geometry of microannuli, slurry behavior and evaluation methods. Izadi et al. (2024) coupled a physically based numerical model of cement invasion into realistic microannuli geometries with the leakage prediction model from Trudel and Frigaard (2023), validated against leakage data from British Columbia, Canada. Here we advance the physical modeling component. The first objective is to investigate the effects of eccentricity and cement expansion, interpreted respectively as drivers of variability and mean microannulus gap width. The second objective is to explore the role of particle size and consequent pore blockage during squeeze operations, through a simplified blockage model. Initially, we study variations in microannuli geometry using microfine cement, where pore blockage is assumed minimal. Our findings challenge the accuracy of conventional leakage flow models that assume a uniform microannulus geometry and calculate flow using a cubic-law model. This is most evident in the changes in leakage values resulting from assumed cement expansion. Changes in gap width variability due to uncontrolled casing eccentricity further widens leakage prediction confidence intervals. Finally, we introduce pore blockage effects within these scenarios. We investigate the competing effects of pore blockage and reductions in mean gap width, both affecting leakage, highlighting the interplay between the stoppage mechanism and the microannulus geometry. • Invasion of slurry into microannulus surrounding perforation. • Stochastic distribution of microannuli thicknesses. • Stochastic well leakage model used to analyze well operations. • Leakage rate distributions predicted before and after squeeze cementing. • Effects of expanding cements, eccentricity and cement particle size.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".