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Record W2923053499 · doi:10.2118/0419-0066-jpt

Effects of Completion Design on Thermal Efficiency in SAGD

2019· article· en· W2923053499 on OpenAlexaboutno aff
Judy Feder

Bibliographic record

VenueJournal of Petroleum Technology · 2019
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsInjectorCompletion (oil and gas wells)Steam-assisted gravity drainagePetroleum engineeringSteam injectionWellboreThermalOil sandsReservoir simulationOil in placeEnvironmental scienceAsphaltGeologyEngineeringPetroleumMechanical engineeringMaterials scienceMeteorologyGeography

Abstract

fetched live from OpenAlex

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 193357, “SAGD Circulation Phase: Thermal Efficiency Evaluation of Five Wellbore Completion Designs in Lloydminster Reservoir,” by Daniel Ayala Rivas, SPE, and Ian Gates, SPE, University of Calgary, prepared for the 2018 SPE Thermal Well Integrity and Design Symposium, Banff, Alberta, Canada, 27–29 November. The paper has not been peer reviewed. During the circulation (startup) phase of steam-assisted gravity drainage (SAGD), high-quality steam injected through the injector and producer wells heats the reservoir between the wells. The viscosity is thus lowered, making fluids mobile at approximately 50 to 100°C and creating interwell fluid communication. This paper uses a simulation model to evaluate and compare the thermal efficiency of five different completion design cases during the SAGD circulation phase in the Lloydminster formation in the Lindbergh area in Alberta, Canada. The results show that completion-design configuration affects the heat transfer and thermal efficiency of the circulation process. Introduction The SAGD process is the most commonly used thermal method of in-situ recovery for extracting heavy oil and bitumen resources in Alberta and can yield recovery factors of greater than 60%. The technique requires two parallel horizontal wells, a producer and an injector, known as a well pair. The horizontal producer well is placed approximately 3 m above the oil/water contact (OWC) or above the bottom of the reservoir, and the injector well is placed above the horizontal producer well. Most SAGD well pairs are placed 5 m apart, which corresponds to approximately 50 kPa of hydrostatic head from the injector to the producer. The lateral section of the well pair is approximately 700–1200 m in length. The SAGD thermal method usually consists of two phases, the circulation phase and the full SAGD, or production, phase. After the circulation phase, the well pair is converted to the production phase, during which steam is injected through both tubing strings of the injector well in a dual-completion design while bitumen or heavy oil and condensed steam are produced through the producer well using natural or mechanical lifting. Constant steam injection causes the steam chamber to grow and expand in the reservoir. Variations in thermal efficiency during the circulation phase result from factors such as tubing size, well trajectory, well length, completion configuration, reservoir properties, and operating parameters. To the authors’ knowledge, no published study has determined the thermal efficiency of different completion designs during the circulation phase of a SAGD well pair in a Lloydminster formation. A previous study used a discretized thermal reservoir-wellbore modeling simulator to history match field data obtained from a SAGD well pair in the Lloydminster area. Operating Strategies and Reservoir Model The complete paper discusses SAGD operating strategies and development of well and completion designs in pilot and commercial operations.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.008
GPT teacher head0.233
Teacher spread0.225 · 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 designSimulation or modeling
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".

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Citations1
Published2019
Admission routes1
Has abstractyes

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