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Record W2049878243 · doi:10.2118/03-09-02

Evaluation of the CO2 Sequestration Capacity in Alberta's Oil and Gas Reservoirs at Depletion and the Effect of Underlying Aquifers

2003· article· en· W2049878243 on OpenAlexaboutno aff
Stefan Bachu, J Shaw

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon sequestrationAquiferEnhanced oil recoveryPetroleum engineeringFossil fuelEnvironmental scienceCarbon dioxideGroundwaterGeologyWaste managementGeotechnical engineeringChemistry

Abstract

fetched live from OpenAlex

Abstract Geological sequestration of CO2 is an immediately available means of reducing CO2 emissions into the atmosphere from major point sources, such as thermal power plants and the petrochemical industry, and is particularly suited to landlocked Alberta. Trapping CO2 in depleted hydrocarbon reservoirs and through enhanced oil recovery (EOR) will likely be implemented first because the geological conditions are already well known and the infrastructure is partially in place. Assuming that the volume occupied by the produced oil and gas can be backfilled with CO2, the ultimate theoretical CO2 sequestration capacity in Alberta's gas reservoirs not associated with oil pools is estimated to be 11.35 Gt. The sequestration capacity in the gas cap of oil reservoirs is 865 Mt of CO2, but this additional capacity will become available sometime in the more distant future after both the oil and gas have been produced from these reservoirs. The theoretical ultimate sequestration capacity at depletion in oil pools in single drive and primary production is only 615 Mt of CO2. Depending on the strength of the underlying aquifer, water invasion has the effect of reducing the theoretical CO2 sequestration capacity of depleted reservoirs by 60% on average for oil pools and 28% on average for gas pools, if the reservoir is only allowed to be repressurized back to its initial pressure. Weak aquifers have no effect on reservoir CO2 sequestration capacity. If other factors are taken into account, such as reservoir heterogeneity and CO2 mobility and buoyancy, then the effective ultimate CO2 sequestration capacity at depletion in hydrocarbon reservoirs in Alberta is estimated to be 9,860 Mt for nonassociated gas pools and 242 Mt for oil reservoirs currently in single drive and primary production. However, most reservoirs have a relatively small CO2 sequestration capacity, rendering them largely uneconomic. In addition, shallow reservoirs are inefficient because of low CO2 density, while very deep reservoirs may be too costly because of the high cost of CO2 compression, and also inefficient in terms of the net CO2 sequestered. If only the largest reservoirs in the depth range of approximately 900 m to 3,500 m are considered, each with an ndividual capacity greater than 1 Mt CO2, then the number of reservoirs in Alberta suitable for CO2 sequestration in the shortto- medium term drops to 565 non-associated gas reservoirs and 22 oil reservoirs in single drive or primary production, with a practical CO2 sequestration capacity of 2,660 and 115 Mt of CO2, respectively. This practical capacity of Alberta's oil and gas reservoirs for CO2 sequestration may provide a sink for CO2 captured from major point sources that is estimated to last for a few decades. Introduction As a result of anthropogenic CO2 emissions, atmospheric concentrations of CO2, a greenhouse gas, have risen from pre-industrial levels of 280 ppm to the current level of more than 360 ppm, primarily as a consequence of fossil-fuel combustion for energy production. This has led to climate warming and weather changes.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.655

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.024
GPT teacher head0.247
Teacher spread0.223 · 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 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

Citations136
Published2003
Admission routes1
Has abstractyes

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