A New Criteria to Predict Stuck Pipe Occurrence
Bibliographic record
Abstract
Abstract Stuck pipe is one of the main problems in drilling oil and gas reservoirs. It usually occurs in high pressure wells and leads to tremendous delays and costs in Iran, every year. Even if different techniques and guidelines have been developed to reduce the probability of occurrence of this phenomenon and these have saved drilling industry millions of dollars, they suffer from exclusive prediction of this event. The reason is that some of these techniques such as sag register incorporate one drilling parameter such as mud weight only. In this paper, mud logging and daily reports of 75 wells in one of Iranian Southwest oil fields were studied. The performance of wells that did not experience stuck pipe was compared with the performance of those that led to stuck pipe. Mud weight, yield point, plastic viscosity, initial gel strength, Marsh funnel viscosity, dial reading at 600 rpm, solid content, temperature, washout and the period that pumps do not need maintenance were employed to introduce a new parameter called Reducing Stuck Index (RSI). It was found that RSI is proportional to the mud weight, initial gel strength; yield point, solid content and temperature and also inverse of plastic viscosity, Marsh funnel viscosity and dial reading at 600 rpm to the power of 0.3. For this field, the comparison of RSI of the current well with those of drilled wells predicted the probability of occurrence of stuck pipe very well. Monitoring RSI helps the driller to know whether the drilling process results in stuck pipe. If the situation is leading to stuck pipe, the drilling parameters can be managed in such a way that RSI lies in the safe range and stuck pipe is prevented.
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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".