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Record W2792691070 · doi:10.2118/189775-ms

Liner-Deployed Inflow Control Devices ICD Production Results in MacKay River SAGD Wells

2018· article· en· W2792691070 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE Canada Heavy Oil Technical Conference · 2018
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsSchlumberger (Canada)Petro-Canada
Fundersnot available
KeywordsInflowPetroleum engineeringCompletion (oil and gas wells)Well controlOil wellEnvironmental geologyEnvironmental scienceDrawdown (hydrology)Permeability (electromagnetism)DrillingEngineeringGeologyHydrogeologyMetamorphic petrologyAquiferGeotechnical engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Ever since horizontal drilling became prominent decades ago, it has been the goal of oilfield operators to find an effective mechanism for controlling the toe-to-heel flux into the production liner to delay and/or reduce the inflow of unwanted fluids such as water, gas and steam, in order to maximize sweep efficiency and oil production/recovery. Inflow Control Devices (ICDs) are basically flow restrictors installed along the completion string to alter the pressure drawdown on the reservoir by choking back the high permeability/high mobility zones while allowing more influx from the lower permeability/lower mobility zones. In steam assisted gravity drainage (SAGD) production wells the primary goal is to operate at lower subcool while minimizing live steam production. The pace of ICD technology adoption has accelerated amongst the operators since its benefit was made prominent in the Surmont field (Stalder 2012). PetroChinaCanada (formerly known as Brion Energy) recognized the technical opportunity and commenced implementation of an ICD technology trial at its MacKay River asset. The technology selection, ICDs sizing and performace prediction was conducted in 2013 (Becerra et al). In 2014 two SAGD production wells, each located on different pads, were selected to evaluate if ICDs could have a beneficial impact on performance. The purpose of this paper is to present preliminary results of the two ICD producer wells which, as of November 2017, have shown superior performance to their non-ICD neighboring wells after about 6 months of production.

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.

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)0.001
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 score0.320
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.018
GPT teacher head0.255
Teacher spread0.237 · 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