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Record W2023388822 · doi:10.2118/09-01-08-da

A New Process Combining Cyclic Steam Stimulation and Steam-Assisted Gravity Drainage: Hybrid SAGD

2009· article· en· W2023388822 on OpenAlexaffabout
G. Coskuner

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2009
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsHusky Energy (Canada)
Fundersnot available
KeywordsSteam-assisted gravity drainageOil sandsPetroleum engineeringAsphaltSteam injectionDrainageGeologyMaterials science

Abstract

fetched live from OpenAlex

Abstract A new thermal recovery scheme is proposed that utilizes Steam-Assisted Gravity Drainage (SAGD) well pairs as well as Cyclic Steam Stimulation (CSS) wells placed in between the SAGD well pairs. The wells are operated in CSS mode until the steam chambers are in contact with each other and then switched to SAGD operation. It is shown that the new process recovers greater amounts of bitumen with lower injected steam in shorter operation time than is achieved with SAGD, Fast-SAGD and CSS. Introduction Alberta's major oil sands deposits, with an estimated 1.7 trillion bbls of bitumen-in-place, account for approximately 40% of the world's bitumen resource(1). The estimated remaining recoverable bitumen from this resource is 170 billion bbls, which dwarfs the remaining conventional reserves of crude oil in Alberta by more than two orders of magnitude(2). While shallow oil sands reserves can be extracted by mining, most of these reserves (82%) are accessible through in situ thermal processes only(2). Two commercially-applied in situ production methods are Steam-Assisted Gravity Drainage (SAGD) and Cyclic Steam Stimulation (CSS). These methods are technically effective but can be rendered uneconomic due to steam requirements. Although the first commercially applied thermal recovery process was CSS, there are a number of commercial and smaller SAGD projects under way at present in Alberta(3). The main attraction of SAGD compared to CSS is that higher recoveries in excess of 50% can be obtained because of the efficiency and effectiveness of the gravity drainage process. However, a challenge for SAGD is to try to promote the lateral and downward expansion of the steam chamber(4). Recently, a new process called Fast-SAGD has been proposed to overcome this problem(5–10). Fast-SAGD Process In the Fast-SAGD process, additional single offset horizontal wells are drilled in between and parallel to the SAGD well pairs. The offset wells are placed at the same elevation as the SAGD producers and can be 50 to 80 m away from the SAGD well pairs. The concept relies on operating the SAGD wells until the steam chamber reaches the top of the formation and then starting a CSS operation at the offset wells at considerably higher pressure than the SAGD wells. The purpose of injecting steam into the offset CSS well is to accelerate growth and propagation of the steam chamber laterally. Once the inter-well area between the SAGD well pairs is heated enough, ideally when the two steam chambers come into contact, the offset well is converted into a producer and the SAGD operation continues. Authors of Fast-SAGD articles reported the results of thermal numerical simulations to initially analyze the response in a Cold Lake-type reservoir and later in Athabasca- and Peace River-type reservoirs(5–10). Their numerical models were generic, two dimensional (2D) homogeneous layer cake models. Results reported were quite impressive in these idealized models where bitumen production rates increased significantly and energy efficiency, as measured by steam-oil ratio (SOR), was better compared to conventional SAGD. Given the encouraging results, it was suggested that a field test should be carried out.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.221
Teacher spread0.215 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations33
Published2009
Admission routes2
Has abstractyes

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