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Record W2006714365 · doi:10.2118/169070-ms

Solvent Enhanced Steam Drive

2014· article· en· W2006714365 on OpenAlex
R.E. Hedden, Marco Verlaan, Vaclav Lastovka

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE Improved Oil Recovery Symposium · 2014
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsShell (Canada)
Fundersnot available
KeywordsPetroleum engineeringSolventSteam-assisted gravity drainageEnhanced oil recoveryEnvironmental scienceAsphaltChemistryWaste managementMaterials scienceOil sandsGeologyEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract In recent years the addition of a hydrocarbon solvent (usually in the range of C4 to C20) to Cyclic Steam Stimulation (CSS) or Steam Assisted Gravity Drainage (SAGD) operations in heavy oil (bitumen) reservoirs has become an attractive process. We extend the idea of solvent addition to steam to a Vertical well Steam Drive (VSD), and investigate the recovery mechanisms, impact on the ultimate recovery and oil steam ratio. The process is studied in core flooding experiments and a CT scanner was used to monitor the saturation distribution over time. These results are history matched using Shell's in-house numerical reservoir simulator MoReS. The simulations show that the dominant recovery mechanism is facilitated through the formation of a solvent bank. Accurate modeling and understanding of the recovery mechanism enables optimal design of the solvent co-injection process in a vertical well steam drive. This allows a comparison between a VSD and a CSS development using solvent addition to steam and selection of the best development option for a given reservoir.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.747
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.004
GPT teacher head0.198
Teacher spread0.195 · 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