Feasibility study formulation for the applicability of rigless temporary ESPs
Bibliographic record
Abstract
Abstract Electrical submersible pumps (ESPs) are a well-known artificial lift technology used in the oil and gas industry to enhance production. One of the major requirements to implement ESPs is the need for a rig to install or replace failed pumps frequently. Temporary rigless ESPs (TRL ESPs) are a new technology that is being developed and tested in many parts of the world. The main advantage of this technology is its much lower installation cost compared to the conventional ESPs because it is deployable through wireline. The main drawback of this technology is the low volumes of fluids it can lift from the wellbore compared to the conventional ESPs. Therefore, it is mainly used as a temporary replacement on top of a failed ESP awaiting a workover job. The feasibility and applicability of the utilization of such technology is studied in this paper using actual field data from more than 500 wells from two fields. The added value of using TRL ESPs is to supplement the lost production volumes from the wells with failed pumps during the waiting time for workover and hence reducing the number of needed backup wells. It was found that using TRL ESPs will reduce the number of needed backup wells over a three-year period by 17–25% based on the actual historical data. Overall, the main outcome of this study is the formulation and development of the predictive model and feasibility study of the TRL ESPs using the actual field data.
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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 | 0.001 | 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".