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Record W1991018128 · doi:10.1016/j.egypro.2014.11.553

Evaluation of CO2 storage capacity in Devonian hydrocarbon reservoirs for emissions from oil sands operations in the Athabasca area, Canada

2014· article· en· W1991018128 on OpenAlexafffundabout
Alireza Jafari, Stefan Bachu

Bibliographic record

VenueEnergy Procedia · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsAlberta Innovates
FundersNatural Resources CanadaSuncor Energy Incorporated
KeywordsOil sandsDevonianFossil fuelEnvironmental sciencePetroleum engineeringGreenhouse gasGeologyWaste managementGeochemistryEngineeringAsphalt

Abstract

fetched live from OpenAlex

Geological Storage of CO 2 has been identified by the provincial Alberta government as the major component of its strategy for reducing greenhouse gas emissions in the province. The issue of reducing atmospheric CO 2 emissions is particularly important for oil sands plants, whose emissions in 2013 were in the order of 55 Mt CO 2 eq. Unfortunately, the oil sands operations are located near the shallow edge of the Alberta basin, which is not suitable for CO 2 storage. However, CO 2 storage in deep Devonian oil and gas reservoirs located westward of the oil sands operations may constitute a solution for storing CO 2 from these operations. The volumetric CO 2 storage capacity in 1225 oil and gas reservoirs in 13 different Devonian formations in an area covering approximately 126,000 km2 was estimated using information from reserves and production databases. The CO 2 storage capacity has been calculated by reservoir type and by production stage. The aggregate CO 2 storage capacity in oil and gas reservoirs in the Devonian sedimentary succession in the study area is in the order of ∼700 Mt. However, most of the reservoirs have small storage capacity, and only 9 oil reservoirs and 10 gas reservoirs have CO 2 storage capacity greater than 5 Mt each, for a cumulative total of ∼447 Mt CO 2 . The strength of underlying aquifers was evaluated by performing material balance calculations for these 19 oil and gas reservoirs and it was found that they do not have a significant effect in reducing the CO 2 storage capacity of these reservoirs. The CO 2 storage capacity in the study area is bound to be greater if one considers the fact that, once the infrastructure, including pipelines, is built to bring CO 2 to any of these very large reservoirs, then smaller reservoirs in the same oil or gas field can be accessed with relatively minimal extra costs. The aggregate CO 2 storage capacity in the fields where the 19 very large oil and gas reservoirs are found has been considered as well, raising the CO 2 storage capacity in these fields to ∼491 Mt CO 2 . The storage capacity in oil reservoirs in the study area can be further increased by using CO 2 in enhanced oil recovery. Although 705 oil pools have been identified as being technically suitable for CO 2 -EOR, only 12 oil reservoirs have remaining oil in place greater than 60 million barrels that would economically justify implementation of CO 2 -EOR. Assuming various incremental recovery factors and net CO 2 utilization factors, the additional amount of CO 2 that may be stored in these 12 oil reservoirs varies between 31 and 412 Mt CO 2 , thus increasing the CO 2 storage capacity in these oil reservoirs. This evaluation shows that the potential CO 2 storage capacity in oil and gas reservoirs in Devonian strata west of the Athabasca oil sands area in Alberta is significant and has the potential to reduce the carbon footprint of the oil sands operations for several decades until other technological advances for reducing CO 2 emissions will come into being.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.626

Codex and Gemma teacher scores by category

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 science0.0000.000
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 head0.034
GPT teacher head0.248
Teacher spread0.213 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations5
Published2014
Admission routes3
Has abstractyes

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