MétaCan
Menu
Back to cohort
Record W2318748352 · doi:10.7122/439486-ms

Fast Modeling of Local Capillary Trapping during CO2 Injection into a Saline Aquifer

2015· article· en· W2318748352 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

VenueCarbon Management Technology Conference · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of Calgary
FundersNational Energy Technology LaboratoryOffice of Fossil EnergyUniversity of Texas at AustinU.S. Department of Energy
KeywordsAquiferCapillary actionEnvironmental scienceSalinePetroleum engineeringHydrology (agriculture)GeologyGroundwaterGeotechnical engineeringGeographyMeteorologyAnesthesia

Abstract

fetched live from OpenAlex

Abstract When CO2 migrates upwards under buoyancy in the subsurface saline aquifer and encounters local capillary barriers (regions of rock with large capillary entry pressure), CO2 would accumulate beneath these small barriers, and these accumulations are called local capillary trapping (LCT). LCT benefits storage because locally trapped CO2 has a much larger saturation than residual gas, and such trapped gases cannot escape from the formation even if leakage conduits (fractures or fault) in the seal develop during the long-term storage of CO2. Thus predicting and maximizing LCT is valuable in design and risk assessment of geologic storage projects. Modeling LCT is computationally expensive and may even be intractable by using a conventional reservoir simulator. In this work, we decouple the problem into two parts: permeability-based flow simulation and capillary entry pressure-based local capillary trapping phenomenon. The connectivity analysis originally developed for characterizing well-to-reservoir connectivity is adapted to the flow simulation by means of a newly defined edge weight property between neighboring grid blocks, which accounts for the multiphase flow properties, injection rate, and buoyancy effect. Then the connectivity was estimated from shortest path algorithm to predict the CO2 migration behavior and plume shape during injection. A geologic criteria algorithm is developed to estimate the potential LCT only from the entry capillary pressure field. The latter is correlated to a geostatistical realization of permeability field. The extended connectivity analysis shows a good match of CO2 plume computed by the full-physics simulation. We then incorporate it into the geologic algorithm to quantify the amount of LCT structures identified within the entry capillary pressure field that can be filled during CO2 injection. Several simulations were conducted in the reservoirs with different level of heterogeneity (measured by the Dykstra-Parsons coefficient) under various injection scenarios. We demonstrate the reservoir heterogeneity affects the optimal injection rate in maximizing the LCT during injection. Both the geologic algorithm and connectivity analysis are very fast; therefore, the integrated methodology can be used as a quick tool to estimate LCT. It can also be used as a potential complement to the full-physics simulation to evaluate the total safe storage capacity.

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 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 score0.193
Threshold uncertainty score0.545

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)0.0000.000

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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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