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Record W2073149330 · doi:10.2118/170141-ms

Investigation of Post CHOPS Enhanced Oil Recovery of Alkali Metal Silicide Technology

2014· article· en· W2073149330 on OpenAlexaboutno aff
Paul H. Krumrine, Michael Lefenfeld, Greg A. Romney

Bibliographic record

VenueSPE Heavy Oil Conference-Canada · 2014
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsAlkali metalEnhanced oil recoveryMaterials scienceChemical engineeringPetroleum engineeringOil fieldSilicideChemistrySiliconMetallurgyGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Alkali metal silicides have ability to enhance oil recovery in a variety of light, medium and heavy oil reservoirs. These chemicals, which include the silicides of sodium (Na), potassium (K) and lithium (Li), are free-flowing granules or very fine powders that are applied downhole in hydrocarbon dispersions. When introduced into a formation through an appropriate non-aqueous carrier fluid, these materials rapidly react with the water in the reservoir pore space, releasing hydrogen gas and heat, and converting into alkali silicates. The silicide-water reaction combined with the flooding process provides multiple mechanisms in the reservoir to enhance oil recovery. Enhanced oil recovery mechanisms include: energy addition through the generation of hydrogen; oil viscosity reductions due to hydrogen solubilization, temperature increase and solvent dilution from the carrier fluid; interfacial tension reduction due to in-situ surfactant generation from interaction of the crude oil organic acids in the reservoir oil with the alkalinity from the produced silicates; and potential improvement of water wettability in carbonate reservoirs. This one chemical combines the effects of thermal, drive energy and chemical mechanisms. In this work, a field-scale numerical simulation study was conducted to investigate the feasibility of cyclically injecting an alkali metal silicide into the wormhole structures of a post CHOPS (cold heavy oil production with sand) reservoir. The Computer Modeling Group's (CMG) STARS simulator was used to perform the simulations; the model consists of six vertical wells with wormhole structures developed using proprietary wormhole growth models that are based on actual field production histories from a representative CHOPS field in Canada (the Lloydminster, Alberta and Saskatchewan region). Multiple simulation cases were run to investigate the effects of injected cycle volume, cycle time, injection rate and silicide concentration. A sensitivity analysis was performed on parameters affecting the slurry model and dispersion rates of the silicide in the reservoir. The preliminary economics of the process were calculated and used to identify an optimized and cost-effective injection strategy, which can subsequently be used as a basis to design a field trial application. The study results showed that the cyclic injection of sodium silicide in a post CHOPS reservoir can in fact improve the recovery of oil in place. The study shows that the predominant recovery mechanism is likely the pressure maintenance of the reservoir that provides energy for continued oil production. This, coupled with secondary oil viscosity reductions, enable the cyclic injection of silicide to increase production for an additional 5 to 10 years, thereby adding 25 to 50% to recoverable reserves under favorable economics. This paper discusses the impacts of the in situ generation of heat, hydrogen and alkali silicate for post CHOPS augmentation and summarizes the key findings of the simulation study and economic modeling.

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 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: Empirical
Teacher disagreement score0.300
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.193
Teacher spread0.184 · 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.

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

Citations4
Published2014
Admission routes1
Has abstractyes

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