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Record W4416822679 · doi:10.2118/230259-ms

Field Implementation of a New Inflow Control Device Design in Surmont I SAGD

2025· article· W4416822679 on OpenAlexaff
Matthew French, Alex Colleaux, Marco Melo Llanos, Mazda Irani

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsInflowFlashingSteam drumSteam injectionSteam-assisted gravity drainageTemperature controlLimitingFlow (mathematics)ThermalOil field

Abstract

fetched live from OpenAlex

Abstract Inflow Control Devices (ICDs) are increasingly employed in Steam-Assisted Gravity Drainage (SAGD) operations to improve steam chamber conformance, delay steam breakthrough, and enhance bitumen recovery. More recently, Inflow Control Devices (ICDs) incorporating internal flashing—a phenomenon where water vaporizes due to localized pressure drops inside the ICD tool, mostly at the Vena contracta—have gained attention for their potential to further optimize steam and fluid control. Industry designs often aim to increase the extent of flashing, assuming this leads to improved performance. However, this approach may result in over-choking, which restricts flow unnecessarily and can negatively impact oil production. This paper introduces the EQUALIZER Dart ICD, a novel steam-sensitive flow control device designed to restrict the production of steam and low-subcool liquids while allowing higher mobility of oil-phase fluids. By preferentially limiting flow from zones with high steam saturation or low subcool, the EQUALIZER Dart ICD helps retain steam energy within the reservoir, directs heat to colder regions, minimizes sandface erosion, and supports the growth of a more uniform steam chamber. This approach enhances thermal efficiency, promotes bitumen mobilization, and may accelerate overall production rates. A central concept presented is sandface subcool, defined as the temperature difference between actual reservoir temperature and saturation temperature at the sandface, based on localized pressure. When sandface subcool approaches zero, the likelihood of steam flashing increases, which may lead to steam coning and early steam breakthrough. The EQUALIZER Dart ICD contributes by increasing upstream backpressure, thereby raising sandface subcool to just above zero. Importantly, this study challenges some operators practice of maximizing subcool (to combat vapor returns), showing that excessive increases can be counterproductive and reduce flow performance. This paper presents the first field implementation of the EQUALIZER Dart ICD in the Athabasca McMurray oil sands reservoir, specifically within the Surmont I SAGD operation. Field production data was analyzed using a newly developed modeling tool, the Eushaw Dynamic Simulator (EDS), which captures both micro- and macro-scale flow behavior. At the micro scale, the model was calibrated using nozzle-level pressure drop data matched against CFER flow loop experiments. This calibration was then integrated into full well-pair simulations to evaluate field-scale performance. Results demonstrated improved well conformance; however, early oil production was impacted by cold-toe conditions. To mitigate this issue, alternative ICD configurations and completion strategies are proposed for future brownfield applications. Additionally, a novel diagnostic chart is introduced, leveraging Distributed Temperature Sensing (DTS) data to monitor ICD performance and steam chamber development throughout the production lifecycle.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.013
GPT teacher head0.300
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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