Fiber Optics Application for Downhole Monitoring and Wellbore Surveillance; SAGD Monitoring, Flow Regime Determination and Flow Loop Design
Bibliographic record
Abstract
Abstract Effective Steam Assisted Gravity Drainage (SAGD) operation relies on subcool management to reduce the risk of steam breakthrough. Monitoring of several parameters is performed to assure uniform development of steam chamber and heating of reservoir. This paper discusses the application of Distributed Acoustic Sensing (DAS), a monitoring platform to achieve reliable reservoir and wellbore surveillance in SAGD projects. In this study, a comprehensive review of DAS deployment in oil and gas industry was performed including vertical seismic profiling, hydraulic fracturing, well/pipe integrity and flow profiling applications. Then, SAGD flow monitoring was investigated in detail. To utilize DAS in SAGD projects, knowing completion designs are necessary. Therefore, various SAGD completion designs and corresponding flow regimes were discussed as well. Finally, four flow loop designs were proposed to accurately simulate the complex wellbore hydraulics of the SAGD producer using DAS recordings. This work started with an overview of DAS systems in downhole monitoring including real time high resolution vertical seismic profiling, hydraulic fracturing characterization and optimization, well and pipe integrity, leak detection and assessing completion effectiveness. Then, flow profiling including flow rate, flow fractions and flow regimes determinations using DAS were discussed with focus on SAGD monitoring. Completion designs directly impact on SAGD monitoring and DAS recordings, more specifically on flow regimes inside the tubing and annulus. Therefore, various completion designs with their tubing and screen sizes were presented and corresponding flow regimes were determined in both tubing and annulus. It was observed that flow regimes vary with type of completion design, liquid flow rate, steam breakthrough locations and tubing/screen sizes. Eventually, four flow loop designs were proposed based on the discussions for future DAS application. This paper discusses existing completion designs and possible flow regimes in SAGD projects. Consequently, novel designed flow loops are introduced for DAS deployment to better understand the complex wellbore hydraulic of the well and measure the key parameters in optimizing the production operation. This study is a design stage for future quantitative measuring of flow profiling using DAS systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".