Horizontal Screen Failures in Unconsolidated, High-Permeability Sandstone Reservoirs: Reversing the Trend
Bibliographic record
Abstract
Abstract Horizontal screen failures can be serious, resulting in expensive remedial operations including early abandonment, in the extreme case. Globally, screen failures in horizontal wells completed in loose unconsolidated sandstone reservoirs have become common. Consequently, from completion and longevity perspectives, a high percentage of horizontal wells have not achieved the desired result: sand-free, high sustained-productivity producers. Individual companies have performed studies in this direction, and some are still ongoing. From preliminary data available, however, it has been possible to observe trends and determine the failure mechanisms. Failure categories highlighted in this paper include wells with significant impaired productions or those completely plugged, representing an overall failure rate of almost 20%. This paper suggests several levels of screen failure: screen collapse or complete plugging, partially plugged screens (poor performing wells) and those producing unacceptable amounts of sand. Other failures include improper installation and economic failures where fixing the problem is possible but costly. Some wells exhibited ‘’early mortality’’, producing sand at production onset. The study further categorized possible causes of screen failures into three major areas: ➣Screen plugging caused by high-pressure drops across screens, hot spots of localized production, fines and dirty sand.➣Incorrect procedures, materials or equipment selection including trouble installing the screens, corrosion in low spots due to standing acid, generalized corrosion from acids, improper cleanup, ineffective mud removal, ineffective sand control, inappropriate screen selection and erosion.➣Poor reservoir understanding in the areas of grain size distribution, sanding up due to water production, open annular areas due to higher than expected rock strength. This paper reviews various applications of soft rock completions in horizontal service, along with benefits and shortfalls. The performance characteristics of the various screens relative to each other from the perspective of flow capacity, plugging and erosion resistance are examined. Recommendations based on ‘’best practices’’ being adopted to combat screen failure problems in high permeability reservoirs are also showcased.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".