MétaCan
Menu
Back to cohort
Record W2897417187 · doi:10.25103/jestr.091.23

Feasibility Study on Steam and Gas Push with Dual Horizontal Wells in a Moderate - Depth Heavy Oil Reservoir

2016· article· en· W2897417187 on OpenAlex

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

VenueJournal of Engineering Science and Technology Review · 2016
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSteam injectionSteam-assisted gravity drainagePetroleum engineeringEnvironmental scienceEnvironmental engineeringWaste managementEngineeringOil sandsAsphaltMaterials science

Abstract

fetched live from OpenAlex

Non-condensable gas (NCG) with steam co-injection makes steam assisted gravity drainage less energy-intensive as well as reduces greenhouse gas emission and water consumption. Numerous studies have shown that the technology called steam and gas push (SAGP) is feasible for heavy oil and bitumen. However, most of these studies have focused on shallow heavy oil reservoirs and only a few works have investigated moderate-depth heavy oil reservoirs. In this study, laboratory experiments and numerical simulations were conducted to study shape change, steam chamber expansion, and temperature change after co-injecting NCG with steam into an actual moderate-depth heavy oil reservoir. Results showed that after co-injecting NCG with steam, the transverse expansion rate of the steam chamber accelerated, vertical expansion slowed down, thermal utilization increased, and oil-steam ratio improved. In addition, the injection parameters of SAGP were also optimized via numerical simulation, which indicated that SAGP could effectively improve development effect and recovery for moderate-depth heavy oil reservoirs.

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)0.001
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 score0.778
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.261
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