Fatigue-Based Tubular Connection Performance for a CSS Operation
Bibliographic record
Abstract
Abstract The Cold Lake heavy oil development, located in northeast Alberta, Canada, began commercial operation in 1985 and uses a thermal recovery process called cyclic steam stimulation (CSS). During steaming and production cycles, the dilation and re-compaction that occur within the reservoir cause the overburden to deform much like the motion of flexing a thick telephone book. At weak overburden layers, shear slip plane(s) can form due to excessive shear stress. Over multiple steaming/production cycles, the cyclic flexing and associated shear slip may lead to overburden casing fatigue failures. In this paper, a multi-scale geomechanics modeling methodology is presented to predict the onset of casing and connection failures due to CSS-induced ultra low cyclic fatigue (ULCF). The modeling methodology consists of building a global model of single or multiple pads, a next level submodel of near-well formation and cement, and a final submodel of casing and connection. To predict the ULCF life, an algorithm based on the concept of cyclic void growth is incorporated into the casing/connection submodel. It provides the capability to predict the number of steam cycles to failure using the concepts of demand (load) and capacity (resistance). A sensitivity study of connection offset to shear slip plane suggested that fatigue life could be extended by placing the connection away from shear slip planes. A series of parametric studies were also conducted to characterize the impact of threaded connection design on fatigue life. Several design scenarios were studied including upset pin, oversized coupling, special clearance coupling, and truncated-length coupling. By selectively reducing the coupling length (truncated) or outer diameter (special clearance), the fatigue life could be prolonged. Based on these promising results, new connection design concepts are being considered for CSS operations in Cold Lake.
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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".