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Record W1974882527 · doi:10.2118/2005-062

The Effect of Initial CO2 Content for Recovery Optimization and Sequestration

2005· article· en· W1974882527 on OpenAlexafffund
Serhat Canbolat, M. Polikar

Bibliographic record

VenueCanadian International Petroleum Conference · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of Alberta
FundersNatural Resources Canada
KeywordsContent (measure theory)Environmental scienceChemistryMathematics

Abstract

fetched live from OpenAlex

Abstract Carbon dioxide (CO2) emissions are increasing due to the hydrocarbons produced increasingly around the world. This is contrary to the Kyoto protocol which states that the signators have agreed to reduce such emissions. This work looks at one such scenario where CO2 is injected prior to steam flooding in a heavy oil reservoir. Field applications have established that CO2 can be an efficient oil-displacing agent for both heavy and light oils as long as they are mobile at reservoir conditions. Using steam with horizontal injection-production well pairs is another recovery method for non-mobile heavy oils. This process can result in relatively higher oil production rates as compared to other steam-based processes not using horizontal wells. However, the higher production rates are associated with excessive energy requirements, CO2 generation, and postproduction water treatment. For understanding and analyzing the effect of CO2 gas storage prior to steam flooding and optimizing recovery by varying the spacing between the horizontal injectors, a series of simulations were carried out. Unlike traditional sequestration of CO2, which is usually limited to exhausted reservoirs, the CO2 is injected, at high pressure, from horizontal well pairs into the heavy oil reservoir. This is done prior to the steam flood to enable viscosity reduction by swelling and to store the anthropogenic CO2, which is the main cause of global warming. To enable diffusion of the injected gas around the well bore, the system is shut in for some time. Then, steam flooding is conducted using the horizontal steam well pairs (SWP). For the heavy oil field model used in this study, which had no gas, the optimum injection rate with respect to distance, recovery and cumulative water-oil ratio (CWOR) was found to be 100 sm3/day/well. An analysis of the results obtained showed that the performance of the wells at the optimum steam injection rate, both with and without CO2 injection prior to the steam flood, were similar. In particular, over the 20-year life of the project, the recoveries were essentially the same. However, during the production period, when CO2, was injected, the CWOR decreased, resulting in an environmentally and economically attractive process. Moreover, 100% of the CO2was stored, which resulted in a reduction in the amount of water that needed to be treated. The sequestration results showed that, after producing to the economic limit, 40 to 50 times the reservoir pore volume (PV) can be employed for sequestration purposes, depending on the amount of residual fluids. Given the volume of oil contained in heavy oil reservoirs, this represents a huge sink for future CO2 sequestration, and an opportunity not only to tap into a huge energy source for the future, but also an opportunity to reduce greenhouse gas emissions. Introduction Heavy oil and bitumen represent a huge amount of natural resources; the world's total estimated original oil in place (OIP) in these forms is approximately 6 trillion barrels, which corresponds to six times the conventional oil reserves.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.021
GPT teacher head0.268
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

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 designObservational
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

Citations0
Published2005
Admission routes2
Has abstractyes

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