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Record W4240344883 · doi:10.2118/2009-190

Partial SAGD Applications in the Jackfish SAGD Project

2009· article· en· W4240344883 on OpenAlexaffabout
P. Li, A. Stroich, A. Vink, K. Nespor, S. Bhadauria, M. P. McCormack

Bibliographic record

VenueCanadian International Petroleum Conference · 2009
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsDevon Energy (Canada)
Fundersnot available
KeywordsPetroleum engineeringComputer scienceEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

Abstract With SAGD operations, it is often inevitable to have shut-in time and turnaround periods because of facility, operation, and supply issues. During these shut-in periods, the gravity drainage of cooling bitumen and steam condensate continuously raises the liquid level over the production well. Therefore, the producer downhole temperature keeps decreasing. This situation makes the restart more difficult. Sometimes even if there is no shut-in, the production well also becomes cold after it is converted from circulation to Full SAGD. This paper classifies the SAGD operation modes into three categories, including Full SAGD, Semi-SAGD, and Partial SAGD. In Partial SAGD, the injector return is shut-in while steam injection continues in the long tubing or in the short tubing and annulus of the injector. The producer is operated with the appropriate steam injection rate to the long tubing. Numerical simulation results associated with Partial SAGD effect are presented. In addition, Partial SAGD applications in Jackfish SAGD project are also discussed. Introduction Up to the end of 2008, the number of commercial Steam-Assisted Gravity Drainage (SAGD) projects in Alberta has increased to 18 and 13 of them are on production (ERCB, 2008). As more projects come on stream, there is increased opportunity to gain valuable experience and improve SAGD performance. The typical SAGD process uses two parallel horizontal wells. The upper well is the steam injector and the lower well is the bitumen producer. It is common that the producer is completed with two tubing strings; a short tubing (ST) string landed at the heel and a long tubing (LT) string landed at the toe. For the injector, there are different completion designs. In the Jackfish project, dual tubing completions for both injector and producer are used and this completion style is considered in this paper. Operations at a SAGD project are often interrupted artificially by a number of issues associated with facility and material supply. During these shut-in periods, the steam chamber inside the reservoir becomes smaller. Cooling bitumen and steam condensate continuously raise the liquid level above the producer. Sometimes, even though there is no shut-in, either the whole horizontal section or just part of the producer becomes cold so that no effective production occurs. Figure 1 shows a typical producer response in the Jackfish SAGD project under these circumstances. Wells with dual tubing completions have the flexibility to adjust the injection and production to remedy this situation. This paper will describe and classify the options which are available to make the adjustment. Reservoir simulations with discretized well bore models are conducted to investigate the effect of some adjustments on SAGD performance. Field cases from the Jackfish SAGD project are also presented to illustrate the application result. Classification of SAGD Operation Modes Full SAGD mode is started after the steam circulation period. The SAGD operation modes can be classified into three major categories based on the steam injection and bitumen production options. The three categories are Full SAGD, Semi-SAGD, and Partial SAGD.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.990
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.027
GPT teacher head0.274
Teacher spread0.247 · 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 designObservational
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

Citations6
Published2009
Admission routes2
Has abstractyes

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