Bibliographic record
Abstract
Abstract In the production well of a Steam Assisted Gravity Drainage (SAGD) injector-producer well-pair, Direct-to-SAGD (D-SAGD) reservoir steam chamber development and electrical submersible pump (ESP) deployment requires only a single workover, effectively performing the jobs in parallel. This is an improvement over the traditional approach where reservoir steam chamber development and ESP deployment occur sequentially, each requiring a dedicated workover. The D-SAGD completion not only eliminates all costs associated with one workover, but also minimizes the heat energy dissipation that would otherwise occur over several days of steam injection downtime associated with pulling the completion string and installing the artificial lift system, along with decreased time, and increased safety, among other attendant benefits. Traditionally, an initial completion is performed on the production well to install monitoring instrumentation and a steam injection string, then steam injection occurs through both the injection and production wells for approximately 90 to 120 days. Once the reservoir temperature has reached a predetermined midpoint temperature between the wells, a fall-off test is performed by halting steam injection in both the production and injection wells and monitoring the completion's heat energy distribution profile throughout the length of the liner from heel to toe as the well cools back down toward its steady state temperature. If the results of the fall-off test are satisfactory, then subsequently a second workover is performed to install the ESP into the production well. Lastly, steam injection in the injector well is resumed, and the ESP operation begins. Given that the single D-SAGD workover achieves both the deployment of instrumentation and the ESP prior to steam chamber development, this implies that the ESP is required to withstand the large temperature and pressure fluctuations inherent to the combination of steam chamber development and fall off testing, all prior to being powered on for production to begin. This represents an unprecedented challenge for ESP seal sections. Among several other novel challenges, if the internal oil volume contraction induced by the deep temperature drop of the fall off test exceeds the capacity of the seal section to compensate for it, then the seal and motor may flood with wellbore fluid prior to the first attempt at turning it on. This paper discusses the unique challenges associated with the D-SAGD completion as it relates to ESP reliability. A SAGD-spec ESP remaining downhole for several months at unprecedented bottom hole pressure and temperature, and withstanding the associated fall-off test is a meaningful deviation from the conventional SAGD application, and this paper will detail the considerations associated with achieving ESP reliability in a D-SAGD completion that is comparable to that achieved in the conventional SAGD completion.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.012 |
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".