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Record W4389002313 · doi:10.2118/217423-ms

Flow Control Device and Liner Floatation: Key Technology Driver in Extreme Extended Reach Shallow Steam Assisted Gravity Drainage Wells

2023· article· en· W4389002313 on OpenAlexaffabout
Hossein Izadi, Morteza Roostaei, M. Mahmoudi, John C. Stevenson, Aubrey Tuttle, G. Bustamante, Sh Rhein, Colby Sutton, Rashid Mirzavand, Jada Leung, Vahidoddin Fattahpour

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPetroleum engineeringSteam-assisted gravity drainageDrillingDirectional drillingSteam injectionWell controlFootprintOil wellMultiphase flowDrillOil productionDrainageFlow (mathematics)Environmental scienceEngineeringGeologyMechanical engineeringOil sandsMaterials scienceMechanics

Abstract

fetched live from OpenAlex

Abstract Pursuing more cost-effective well construction and reduced surface footprint has prompted Western Canadian operators to explore extreme extended reach drilling (ERD) wells. However, this endeavor faces a critical challenge: most heavy oil reserves are relatively shallow, resulting in the unwrapped reach ratio (the total horizontal length when projected on the horizontal plane to true vertical depth (TVD)) of more than seven. Therefore, to drill ERD wells, two crucial technical challenges must be tackled: successful liner installation, and efficient steam distribution along these long laterals to enhance production. This paper delves into the solutions for these challenges and a case study showcasing the recent drilling of a steam-assisted gravity drainage (SAGD) extreme ERD well. While floating liners are a known method for extending well reach, they are uncommon in SAGD wells. However, some companies have started exploring the use of floating liners in SAGD projects due to their potential to greatly expand lateral well length, reducing footprint and increasing the oil recovery from any one well pair. By floating the liner using plugged flow control devices (FCDs), gentler running procedures can be employed to achieve TD without risking the integrity of the liner. Moreover, utilizing FCDs in floating liners improves steam conformance and oil production while reducing the cumulative steam oil ratio (cSOR) during the production phase. Modeling results can enhance our capabilities in planning shallower SAGD wells with longer productive sections in the future, with (as described herein) horizontal liner lengths of 1700m and true vertical depths of 240m. The modeling results show that floating liners using plugged FCDs reduce torque by an average of 22% and bottom hole torque by 28%, while also decreasing drag by 16% on average, and bottom hole drag by 17%. These findings indicate that floating liners with plugged FCDs offer a promising solution for SAGD and CSS extreme ERD wells limited by liner installation forces. Furthermore, wells with FCDs in uplifted cases displayed a remarkable upswing of 57%, while concurrently, cSOR demonstrated a noteworthy decrease of 18%. Uplifted cases are identified when wells were completed or retrofitted with FCDs and showed increased oil production compared to neighboring wells. The successful implementation of floating liners with dissolvable or meltable plugs on FCDs enhances confidence in future SAGD extreme ERD wells. The implementation of FCDs in extreme ERD well designs could contribute to reduced greenhouse gas (GHG) emissions, aligning with efforts to combat climate change and minimize environmental impacts. The study's findings elaborated on driving paradigm shifts in the development of heavy oil resources as technology advances, while considering economic factors.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.212
Teacher spread0.192 · 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 designBench or experimental
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

Citations2
Published2023
Admission routes2
Has abstractyes

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