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Record W4413897447 · doi:10.2118/226771-ms

A Case History: Different Paths, Same Destination – Two Modelling Approaches for the Corrib Gas Field

2025· article· en· W4413897447 on OpenAlexaff
F. Nieuwland, Peter Colleran, B. Tournemine, Antoine Veillerette, H. De Koningh, C. Coulombe, S. Wybar, Roma Maguire

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsLakeland College
Fundersnot available
KeywordsField (mathematics)Computer scienceNatural gas fieldEngineeringMathematicsNatural gas

Abstract

fetched live from OpenAlex

Abstract This paper compares two independent subsurface models developed by the Corrib JV partners, Vermilion Energy Ireland (operator) and Nephin Energy (non-operating partner). The models were built to investigate a static-dynamic GIIP discrepancy of 0.1–0.4 Tcf for development opportunities and long-term field optimization. Corrib is located 70 km west of Ireland at 350 m water depth. It is a faulted anticline with four-way dip closure, with the top structure crest at 3,300 m subsea. The Triassic Sherwood Sandstone reservoir is developed by six subsea wells tied back to Bellanaboy Bridge onshore gas terminal via a 95km pipeline. Production was brought onstream in 2015, reaching a plateau rate of 350 mmscf/d before declining to approximately 100 mmscf/d today. The static GIIP range is 1.1–1.4 Tcf. Nine years of production data demonstrate a dynamic connected GIIP of 1 Tcf. In 2021, ocean bottom cable (OBC) seismic was reprocessed for image quality in the Sherwood and Carboniferous horizons ahead of a series of major gas plant upgrades and possible infill and deeper horizon drilling. The significant improvement in seismic image quality gave a new top structure map and allowed for detailed fault mapping. The Sherwood reservoir consists of a high net-to-gross sequence of low-sinuosity braided river bars, playa, and sandflat facies in a dryland fluvial environment. Permeability varies significantly, with upper A/B/C sands (1–100 mD) exhibiting better reservoir quality than the deeper D to I sands (0.1–10 mD). Dynamic data has proven global communication between all wells. Reservoir performance is monitored using wellhead/downhole pressure data, pressure transient surveys, and well tests. Each JV partner's 3D static model adopted a "back to basics" approach, incorporating a core and well data-driven static model. Vermilion's model includes additional concepts such as paleo-flow and paleo-gas below the GWC. At high level, both partners estimate similar static GIIP range above the GWC with some differences in how GIIP, permeability and vertical connectivity are distributed. History-matched reservoir simulation models inform performance analysis and forecasting. Nephin's history match requires pore volume reduction in poorer E+ sands, suggesting limited contribution from these facies. In Vermilion's history match the paleo-gas is immobile and gas contribution from the D+ sands is reduced by reduction in pore volume, permeability and vertical connectivity. Both models come to a similar dynamic connected GIIP. There has been no water breakthrough after 9 years production. In Vermilion's model this is represented by the immobile paleo-gas preventing aquifer movement. Nephin's model uses a degraded aquifer. Despite the differences, both models highlight similar reservoir risks and yield comparable production forecasts. The paper demonstrates how integrated geological and dynamic modelling by two separate subsurface teams supports a robust understanding of Corrib's long-term production potential.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.348

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.094
GPT teacher head0.240
Teacher spread0.146 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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