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Record W7130444685 · doi:10.56952/igs-2025-0207

An advanced geomechanics study to minimize the drilling risks and optimize the placement of new wells for a natural gas and hydrogen storage project in a Southern North Sea depleted gas reservoir

2025· article· W7130444685 on OpenAlexaff
Zhi Fang, Steve Hayhurst, Colin Derby, Mark Cullen, Heikki Jutila, K. M. Howell

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsGeomechanica (Canada)
Fundersnot available
KeywordsGeomechanicsCasingOverpressureDrillingMeasurement while drillingNatural gasOverburdenOffshore geotechnical engineeringNatural gas fieldOffshore drilling

Abstract

fetched live from OpenAlex

Sixteen high angle wells were proposed to redevelop Rough, a depleted offshore gas field, for natural gas and subsequent hydrogen storage in the Southern North Sea. Kicks, losses and pack off were considerable concerns for wellpath planning and drilling operations due to the overpressure in an overburden interval and the severe depletion in the targeted reservoir section. An advanced geomechanics study was performed to assess the drilling risks by predicting the fracture gradient more accurately for individual well trajectories. It adopts Kirsch equations and incorporates elaborated field stress assessments, rock mechanical property estimation and the impact of pressure depletion based on historical drilling and testing data. It showed that the drilling risks are significantly influenced by both wellbore azimuth and the stress path factor (SPF). Wellbores towards the minimum horizontal stress (Shmin) directions are more favorable than those towards other orientations with a potential of reducing one conventional casing string. SPF 0.6 would diminish the drilling window for the wells towards the maximum horizontal stress (SHmax) directions in the depleted reservoir. The geomechanics study results were combined with dynamic reservoir modelling and the well placement was ultimately optimized for delivering the most efficient storage system with minimised well operational risks.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 head0.021
GPT teacher head0.270
Teacher spread0.248 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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