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Record W7000784531

Geotechnical Centrifuge Experiments to Improve Understanding of Sand Production from Heavy Oil Reservoirs

2021· dissertation· en· W7000784531 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2021
Typedissertation
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCentrifugeFlow (mathematics)Oil sandsErosionOil productionCompletion (oil and gas wells)Production rate
DOInot available

Abstract

fetched live from OpenAlex

Since the 1990’s, Cold Heavy Oil Production with Sand (CHOPS) has been a common practice in Western Canada where sand can be easily mobilized from weakly cemented sandstones. The more sand produced, the greater the oil recovery, with recovery factors of 10% being typical. In recent years, operating companies have enhanced recovery in reservoirs previously operated using CHOPS by applying thermal and/or chemical methods; however, effective implementation of these methods requires an improved understanding of sand production mechanisms. Numerous field-based, numerical, and laboratory modelling studies have been completed to better understand the shape of the voids that form within heavy oil reservoirs during CHOPS, sand transport mechanisms, and CHOPS impact on production rate. The objective of this research was to design and implement a laboratory testing system to investigate these subjects. A purpose-built geotechnical centrifuge model was used for this research, with a sandpack of dense, uncemented sand representing the reservoir. The results demonstrate that the predominant sanding mechanism is the development of a cone-shaped cavity at the top of the sandpack, both with stiff (steel) and compliant (clay) caprock. The results also demonstrate that erosion channels may develop around the cavity, in cases where flow rates near the top of the sandpack are greater than flow rates at depth; however, with the presence of a flexible caprock and uniform radial flow, this effect can be nullified. In addition, the results for one of the experiments, in conjunction with numerical modelling, suggest that a wormhole may form during seepage in the upper part of the reservoir where in-situ stresses are relatively low, though it might collapse once seepage is ceased. Such wormholes may have been a major cause of the high flowrates observed during the tests after sand production, enhanced to some extent by dilation-induced increase in hydraulic conductivity in the near-well and near-cavity areas. Moreover, results obtained using two-phase fluid saturations (water and oil) suggest that capillary pressures increase the effective strength of the sandpack, which reduces the tendency of sand failure as was observed in deep perforated zones in experiments conducted using single-phase oil saturation. The practical implication of this work is the suggestion that it may be possible to improve the effectiveness of enhanced recovery operations if heated fluids/solvents are injected into the deeper, less disturbed part of the reservoir in order to avoid premature breakthrough (production) of injected fluids.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.185
Teacher spread0.175 · 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 designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

Explore more

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