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Record W2002766377 · doi:10.2118/70133-pa

Multiple Proppant Fracturing of Horizontal Wellbores in a Chalk Formation: Evolving the Process in the Valhall Field

2001· article· en· W2002766377 on OpenAlexaff
Mark Norris, L. Bergsvik, Chris Teesdale, B. A. Berntsen

Bibliographic record

VenueSPE Drilling & Completion · 2001
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsSchlumberger (Canada)
Fundersnot available
KeywordsPetroleum engineeringCoiled tubingDirectional drillingCompletion (oil and gas wells)DrillingLogging while drillingProductivityWell stimulationWellboreOil fieldReservoir engineeringGeologyEngineeringPetroleumMechanical engineering

Abstract

fetched live from OpenAlex

Summary Oil production from this chalk field has been improved significantly over the last 3 years using multiple proppant fractures placed from horizontal completions. Following early successes, the engineering effort focused on increasing value through engineering innovation and increased productivity. This paper describes, through case histories and field data, advances made in the design and execution of these completions over 13 wells in the Valhall field. Wellbore completion activities and stimulation are performed now as a stand-alone process. Using specialized large-diameter coiled-tubing (CT) equipment allows ongoing drilling operations to be performed concurrently. This has reduced daily spread costs significantly while bringing wells on production in a much-reduced time frame. This lower cost environment also has allowed innovative field procedures to be developed resulting in further improvements such as proppant plugs for isolation between stimulation zones, novel bottomhole assemblies (BHA's) for perforating, and treatments using recycled proppant to minimize waste. Productivity is the driver for economic success. Treatmentdesign requirements have evolved through laboratory testing to account for longer-term downhole-operating conditions below the bubblepoint while also improving initial conductivity. Field data to date through production logging operations have confirmed the hydrocarbon contribution from each fracture. This is used to validate the effectiveness of each treatment. Normalized well productivities continue to improve and the challenge is to maintain the rate of evolution through the improved application of new and existing technologies.

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 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 score0.017
Threshold uncertainty score0.313

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 head0.013
GPT teacher head0.232
Teacher spread0.219 · 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 teacher head, 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

Citations8
Published2001
Admission routes1
Has abstractyes

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