Use of Downhole Permanent Pressure Gauge Data to Diagnose Production Problems in a North Sea Horizontal Well
Bibliographic record
Abstract
Abstract Permanent downhole pressure gauges are increasingly being installed in new wells in the North Sea and in other new developments around the world. Their reliability has greatly improved and they now can operate for several years. They provide a record of everything that is happening to the well and, in the long term, they will replace production tests for well and reservoir monitoring. The main difference with production tests, however, is that rate variations are not controlled, which can make the interpretation difficult. The paper illustrates how the availability of three years' worth of pressure data from a permanent downhole pressure gauge was key to understanding and explaining a tenfold loss of productivity in a North Sea horizontal gas well. Four million pressure measurements were processed and analyzed both in the conventional way, one flow period at a time, and by deconvolution, using increasing durations of pressure records from the start of production. Interpretation identified progressive changes in gas relative permeability followed by decreases in the well length, suggesting water invasion of the well zone. This points out to the need for continuous monitoring of the interpretation of permanent gauge data, which is possible by deconvolution, to identify changes in well-reservoir behavior as soon as they occur and thus avoid potentially irreversible productivity problems.
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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".