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Record W4389002169 · doi:10.46690/ager.2024.01.02

Impact of CO2 solubility on design of single well tracer tests to evaluate residual saturation during carbon capture and storage

2023· article· en· W4389002169 on OpenAlexfundno aff
Masra Awag, Eric Mackay, Saeed Ghanbari

Bibliographic record

VenueADVANCES IN GEO-ENERGY RESEARCH · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsnot available
FundersEnergi SimulationMinistry of Education, Libya
KeywordsTRACERResidualSaturation (graph theory)DissolutionSolubilityCarbon dioxideSoil scienceChemistryMaterials sciencePetroleum engineeringEnvironmental scienceGeologyMathematics

Abstract

fetched live from OpenAlex

Single-well tracer technique have been well applied in many petroleum industry and environmental applications. However, these tests have not been well developed for CO2 geological storage purposes to evaluate residual CO2 saturation during the appraisal phase of site investigation, due to the challenges occurring from the complex phase behaviour. In this study, two single-well tracer tests are numerically modelled to quantify the residual gas saturation. Our study addresses the design of an alternative single well tracer test sequence, which involved a single pass of the tracer saturated water over the residually trapped zone, thereby reducing the amount of CO2 dissolution into the tracer solution. A one-dimensional numerical modelling of the tracer propagation and partitioning with homogenous properties was used for the calculations of the difference in tracer breakthrough times during water withdrawal from the tests. Model sensitivity variations were applied to analyse the impact of reservoir and treatment design parameters on the residual gas saturation. The residual gas saturations calculated reflect the input values, including the effect of hysteresis, to within 10% accuracy. It was found that changing the CO2 saturated water volume injected after CO2 made the CO2 front to travel to different distances from the well, and thus the tracer had different size of residually trapped zones to travel through when it is back produced and encounters different residual gas saturations, and therefore affected the residual gas saturation calculations. The modelling also shows that optimal injection of CO2-saturated water to prevent the dissolution of the residually trapped CO2 and establish the residually trapped zone was challenging to achieve, and therefore using the fluid withdrawal method was more robust to establish the residually trapped zone. This is because of the dependency of solubility on pressure. The numerical models may be used to design, optimise, and interpret the field tests. Document Type: Original article Cited as: Awag, M., Mackay, E., Ghanbari, S. Impact of CO2 solubility on design of single well tracer tests to evaluate residual saturation during carbon capture and storage. Advances in Geo-Energy Research, 2024, 11(1): 6-19. https://doi.org/10.46690/ager.2024.01.02

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.059
GPT teacher head0.393
Teacher spread0.334 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

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