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Record W4416851306 · doi:10.1016/j.ijggc.2025.104519

Benchmarking CO₂ storage simulations: Results from the 11th Society of Petroleum Engineers Comparative Solution Project

2025· article· en· W4416851306 on OpenAlexafffund
Jan M. Nordbotten, Martin A. Fernø, Bernd Flemisch, Anthony R. Kovscek, Knut‐Andreas Lie, Jakub Wiktor Both, Olav Møyner, Tor Harald Sandve, Etienne Ahusborde, Sebastian Bauer, Zhangxin Chen, Holger Class, Chaojie Di, Didier Yu Ding, D. J. Element, Éric Flauraud, Jacques Franc, Firdovsi Gasanzade, Yousef Ghomian, Marie Ann Giddins, Christopher P. Green, Bruno Ramon Batista Fernandes, George Hadjisotiriou, Glenn Hammond, Hai Huang, D. Kachuma, Michel Kern, Timo Koch, P. Krishnamurthy, Kjetil Olsen Lye, David Landa-Marbán, Michael A. Nole, Paolo Orsini, Nicolas Ruby, Pablo Salinas, Mohammad Sayyafzadeh, Jakob Torben, A.P.L. Turner, Denis Voskov, Kai Wendel, AbdAllah A. Youssef

Bibliographic record

VenueInternational journal of greenhouse gas control · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsBP (Canada)
FundersNatural Sciences and Engineering Research Council of CanadaTotalNorges ForskningsrådEquinorDeutsche ForschungsgemeinschaftAlberta InnovatesU.S. Department of Energy
KeywordsBenchmarkingPetroleumBenchmark (surveying)

Abstract

fetched live from OpenAlex

The 11 th Society of Petroleum Engineers Comparative Solution Project (shortened SPE11 herein) benchmarked simulation tools for geological carbon dioxide (CO 2 ) storage. A total of 45 groups from leading research institutions and industry across the globe signed up to participate, with 18 ultimately contributing valid results that were included in the comparative study reported here. This paper summarizes the SPE11 results. A comprehensive introduction and qualitative discussion of the submitted data are provided, together with an overview of online resources for accessing the full depth of data. A global metric for analyzing the relative distance between submissions is proposed and used to conduct a quantitative analysis of the submissions. This analysis attempts to statistically resolve the key aspects influencing the variability between submissions. The study shows that the major qualitative variation between the submitted results is related to thermal effects, dissolution-driven convective mixing, and resolution of facies discontinuities. Moreover, a strong dependence on grid resolution is observed across all three versions of the SPE11. However, our quantitative analysis suggests that the observed variations are predominantly influenced by factors not documented in the technical responses provided by the participants. We therefore identify that unreported variations due to human choices within the process of setting up, conducting, and reporting on the simulations underlying each SPE11 submission are at least as impactful as the computational choices reported.

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)0.023
metaresearch head score (Gemma)0.037
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 score0.023
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.037
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.021
GPT teacher head0.290
Teacher spread0.269 · 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

Citations13
Published2025
Admission routes2
Has abstractyes

Explore more

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