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Record W2246874931 · doi:10.2118/174463-ms

Steam Injection Schemes for Bitumen Recovery from the Grosmont Carbonate Deposits

2015· article· en· W2246874931 on OpenAlexaffabout
Qiuyue Song, Zhangxin Chen, S.M. Farouq Ali

Bibliographic record

VenueSPE Canada Heavy Oil Technical Conference · 2015
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPetroleum engineeringSteam injectionCarbonateInjectorPetrophysicsSteam-assisted gravity drainageGeologyOil in placeEnhanced oil recoveryAsphaltPorosityEnvironmental sciencePetroleumOil sandsGeotechnical engineeringEngineeringMaterials scienceMechanical engineering

Abstract

fetched live from OpenAlex

Abstract The hydrocarbon resources in the Grosmont carbonate deposits in Alberta are over 400 billion barrels. Pilots have been carried out in Grosmont since 1974, but hitherto a commercial recovery scheme remains elusive. This study addresses oil recovery techniques from the Grosmont carbonate deposits, using numerical simulation for several steam-based recovery schemes. Selected simulation results were further analyzed and compared with those from the classical analytical model. Given the extremely heterogeneous nature of the deposits (karsted, fractured, and high variability in formation properties) and high oil viscosity (2-11 million cp at 20 °C), a typical geological model of Grosmont, with representative petrophysical and geological characteristics, was used to examine several steam injection schemes, using a dual porosity/dual permeability model in CMG STARS. The schemes tested included: single vertical well cyclic, single horizontal well cyclic, steam assisted gravity drainage and steamfloods involving five-spot, nine-spot, seven-spot patterns and the vertical well injector-horizontal well producer arrangement. The dominant feature of all steam injection schemes was a high steam-oil ratio, although the oil recovery was high in most cases. Experiments showed that the steam-oil ratio of steamfloods can be improved by reducing the steam injection rate and closing certain perforation intervals at critical points in the production life of the well. As a result of optimization, a pattern steamflood case achieved a steam-oil ratio of 8 m3/m3 and recovery factor of 41%. The best horizontal well CSS case, for which the well location is chosen to avoid steam channelling into the top water, gave a good response with a steam-oil ratio as low as 7 m3/m3 and a recovery factor of 18%. The recovery factors of the two processes are comparable considering the fact that the wells in the former were perforated into Grosmont C and D members of the model while the latter targets only the Grsomont C member. SAGD cases have similar steam-oil ratio but smaller oil recovery. Simulation results were analyzed in the light of dynamic fluid flow, thermal efficiency and drive mechanism and were compared with results from classic analytical methods. Affected by the high fracture vertical permeability and severe heterogeneous formation properties, steam override and oil gravity flow occur in all processes. Uneven steam zone and limited drainage area make it difficult to achieve optimal performance of processes including SAGD, seven-spot pattern steamflood and horizontal well CSS. Early steam breakthrough happened in the pattern steamfloods. A combination of vertical steam injectors and a horizontal producer provided the most uniform formation heating and production of the mobilized oil by both gravity flow and viscous drive, thus achieved the same recovery performance faster than horizontal well CSS and delayed steam breakthrough.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.609

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.218
Teacher spread0.198 · 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 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

Citations2
Published2015
Admission routes2
Has abstractyes

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