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Record W2061795178 · doi:10.2118/2004-151

Modelling of Convective Mixing in CO2 Storage

2004· article· en· W2061795178 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCanadian International Petroleum Conference · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsConvective mixingMixing (physics)ConvectionEnvironmental scienceMaterials scienceMeteorologyPhysics

Abstract

fetched live from OpenAlex

Abstract Accurate modeling of the fate of injected CO2 is necessary if geological storage is to be used at large scale. In one form of geological storage of CO2, the gas is injected into an aquifer that has a sealing cap rock forming a gas cap beneath the cap rock. The diffusion of CO2 into underlying formation waters increases the density of water near the top of the aquifer bringing the system to a hydro-dynamically unstable state. Instabilities can arise from the combination of an unstable density profile and inherent perturbations within the system, e.g. formation heterogeneity. If created, this instability causes convective mixing and greatly accelerates the dissolution of CO2 into the aquifer. Accurate estimation of rate of dissolution is important for risk assessments because the timescale for dissolution is the timescale over which the gaseous CO2 has a chance to leak thorough the cap rock or any imperfectly sealed wells. We describe a new 2-D numerical model developed to study the diffusive and convection mixing in geologic storage of CO2. Effects of different formation parameters are investigated in this paper. Results reveal that there are two different time scales involved. The first time scale is the time to start the instability and the second one is the time to achieve ultimate dissolution. Depending on system Rayleigh number and the formation heterogeneity, the convective mixing can greatly accelerate the dissolution of CO2 in an aquifer. Two field scale problems were studied. In the first, based on the Nisku aquifer, more than 60 percent of the ultimate dissolution was achieved after 800 years while the computed timescale for dissolution in the same aquifer in the absence of convection was orders of magnitude larger. In the case of the Glauconitic sandstone aquifer, there was no convective instability. Results suggest that the presence and strength of convective instability should play an important role in choosing aquifers for CO2 storage. Introduction The use of technologies to capture and store CO2 is rapidly emerging as a potentially important tool for managing carbon emissions. Geologic storage, which we define as the process of injecting CO2 into geologic formations for the explicit purpose of avoiding atmospheric emission of CO2, is perhaps the most important, near-term, option. Geologic storage promises to reduce the cost of achieving deep reductions in CO2 emissions over the next few decades. While the technologies required to inject CO2 deep underground are well established in the upstream oil and gas sector, with such methods as CO2-EOR and Acid Gas disposal, methods for assessing and monitoring the long term fate of CO2, and for assessing the risk of leakage are in their infancy. Assessments of the risk of leakage of CO2 from a storage formation may need to analyze leakage mechanisms and their likelihood of occurrence during the full time period over which mobile free-phase CO2 is expected to remain in the reservoir. Once dissolved, risk assessments may well ignore the leakage pathways resulting from the very slow movement of CO2-saturated brines.

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.201
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0040.000

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 head0.027
GPT teacher head0.238
Teacher spread0.211 · 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