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Record W2139522170 · doi:10.2118/153128-ms

Assessment of SAGD Well Configuration Optimization in Lloydminster Heavy Oil Reserve

2012· article· en· W2139522170 on OpenAlexaffabout
M. Sadegh Tavallali, Brij Maini, T. Harding, Bashir Busahmin

Bibliographic record

VenueSPE/EAGE European Unconventional Resources Conference and Exhibition · 2012
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsSAIT PolytechnicTotal (Canada)University of Calgary
Fundersnot available
KeywordsPetroleum engineeringLimitingOil reservesGeologyEnvironmental scienceProcess (computing)Displacement (psychology)Oil wellPetroleumComputer scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Large quantity of heavy oil resources are present in variety of complex thin reservoirs in Lloydminster area which are situated in east-central Alberta and west-central Saskatchewan. Primary depletion and waterflooding are the principal recovery techniques. Although these techniques work, the recovery factors remain low and large volumes of oil are left unrecovered when these methods have been exhausted. Because of the large quantities of sand production, many of these reservoirs end up with a network of wormholes that makes most of the displacement type enhanced oil recovery techniques inapplicable. Because of these high conductivity channels, only gravity drainage based techniques have a good chance of success. Among the applicable methods in Lloydminster area, SAGD has not received adequate attention, mostly due to the notion that heat loss in thin reservoirs would make the process uneconomical. While this may be true, the limiting reservoir thickness for SAGD under varying conditions has not been established. These reservoirs contain light oil with sufficient mobility. Therefore the communication between the SAGD well pairs is no longer a hurdle. This opens up the possibility of increasing the distance between the two wells and introducing elements of steamflooding into the process in order to compensate for the small thickness of the reservoir. The main objective of this study was to evaluate the effect of well configuration on SAGD performance and develop a methodology for enhancement of the SAGD performance through optimizing the well configurations for Lloydminster type of reservoir. A new well configuration was able to significantly improve the application of SAGD in thin reservoirs of Lloydminster. It provided high RF at reasonable cSOR. The effects of some common Lloydminster reservoir characteristics, which are problematic for the SAGD process (such as initial gas saturation, bottom water, and gas-cap) were investigated for the most promising well configuration.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.029
GPT teacher head0.270
Teacher spread0.242 · 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".

Quick stats

Citations24
Published2012
Admission routes2
Has abstractyes

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