Efficient Alternative to Control Sand Production in Wells with Oil/Water Contact at the Wellbore
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Bibliographic record
Abstract
Abstract Sand production has proved to be a severe and often costly problem in many wells in the Oriente basin of Ecuador. Sand production has a negative impact over the productivity and lifting cost when it accumulates as sand plugs in the tubing, the surface flowlines or the surface pipes or vessels, and also when eroding the stages of the electric submersible pumps, shortening their run lives. Traditional techniques used to control sand production, such as conventional screens or gravel packs have been tried by Alberta Energy Company (AEC) in Ecuador resulting in impaired productivities of up to 75%, and therefore, are considered inefficient. Other techniques are not effective because of the broad grain size distribution, and also because the production of AEC in Ecuador typically comes from moderately thin and clean reservoirs, with bottom aquifers in the well. AEC and the majority of operators in Ecuador have not yet been able to control sand production without substantially reducing the oil production. This paper presents an efficient and economic alternative to control sand production. It consists of a filter that is run in front of the perforations and that once properly packed, can virtually stop the sand without affecting the production of fluids. The completion is simple and significantly less expensive than comparable techniques. The proposed methodology has been tested so far in six AEC producers in Ecuador at flow rates up to 3000 bfpd, controlling the sand without affecting the total flow rate or the flowing pressure. A significant part of the success is attributable to a new procedure, introduced here, to naturally pack the screen. This work summarizes the experience of AEC Ecuador in techniques to effectively control the sand production and it is supported by an extensive amount of field data. The results obtained here have served to demonstrate that designs customized to fit specific reservoir conditions can help maximize the well's productivity and to optimize the completion costs.
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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 it