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Record W4239063099 · doi:10.2118/03-08-02

Artificial Lift-A Major Unresolved Issue for SAGD

2003· article· en· W4239063099 on OpenAlexaboutno aff
K.E. Kisman

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2003
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsArtificial liftGas liftPetroleum engineeringLift (data mining)InletSteam injectionEngineeringHead (geology)Mechanical engineeringEnvironmental scienceMechanicsComputer scienceGeology

Abstract

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Abstract Lower-pressure SAGD may be required because of thief zones, or to improve the SOR, emissions, and water use. Simple 3D simulation examples representing real-world conditions illustrate the need for low steam-trap subcool values. A low mixed subcool value is needed to minimize local subcool values along the well pair and maximize steam chamber development. Lower pressures magnify the need for low subcool values. For low mixed subcool values, there is zero or very low liquid head available above a bottomhole pump. However, a high average head is required, much higher than the minimum head, due to SAGD flow instabilities. Using typical field values, a simple analysis shows that a standard bottomhole pump configuration cannot provide low subcool values for lower steam chamber pressures. A lift system designed to provide low subcool values at lower pressures is a two-stage lift system called ELift. This was used at Gulf's Surmont SAGD pilot for three years. A simulation example of the two-stage lift system is provided showing excellent conditioning of fluids prior to the pump inlet. This allows the use of standard pumps, and extends pump service life, in addition to providing the benefits of lower-pressure operation and improved recovery performance with low mixed subcool values. Introduction Steam-assisted gravity drainage (SAGD) is now used in large commercial operations as well as pilot operations. However, one of the major issues that has not yet been resolved is the issue of artificial lift for lower-pressure SAGD operations. The main focus of this paper is to summarize why lower-pressure SAGD is important, describe the impact of steam-trap control and unstable SAGD flow on artificial lift requirements, and describe a lift system which, in principle, meets the requirements for SAGD lift at lower pressures. Reasons for Lower-Pressure SAGD Operations Lower-pressure SAGD may be required because of the presence of thief zones. Associated gas sands and/or water sands in the upper part of the McMurray formation are common features of the Athabasca oil sand deposit, and may constitute thief zones to SAGD operations. The upper gas and water sands are generally under-pressured at virgin conditions, and gas production operations have further lowered the pressure. When SAGD steam chambers achieve hydraulic communication with associated thief zones, the pressure in the steam chamber must be close to that in the overlying thief zone, and artificial lift will generally be required. There is extensive information on this topic from several gas/bitumen hearings and in decision reports by the Alberta Energy and Utilities Board(1). Even when thief zones are absent, lower-pressure SAGD may be required to improve the steam-oil ratio (SOR). Reduced SOR provides savings in natural gas consumption, reduced emissions per unit of production (specific to Kyoto regulations), and reduced usage of valued water resources. Because reduced SOR also reduces water handling requirements, it provides important savings in the separation and water-recycle facilities. A SAGD plant is mainly designed with regard to steam-generation/water-handling capacity. Once a plant is built, with relatively minor modifications it will provide increased oil rates as the SOR declines.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.208
Teacher spread0.199 · 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

Citations17
Published2003
Admission routes1
Has abstractyes

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