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Record W2984156012 · doi:10.2118/198695-ms

SAGD Circulation Strategy Utilizing Flow Control Devices

2019· article· en· W2984156012 on OpenAlexaff
J. Batias, J. D. Ortiz, Kristian Nespor

Bibliographic record

VenueSPE Thermal Well Integrity and Design Symposium · 2019
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsProcess (computing)Petroleum engineeringComputer scienceSoftware deploymentFlow (mathematics)Flow control (data)Oil fieldCompletion (oil and gas wells)AsphaltProcess engineeringEngineeringTelecommunicationsMaterials science

Abstract

fetched live from OpenAlex

Abstract For ConocoPhillips, technology is a key driver and development accelerator to continuously improve its SAGD operations. The deployment of conventional Flow Control Device (FCD) technology in Surmont has allowed ConocoPhillips to realize shorter circulation times and higher oil production rates. These benefits have been realized while ensuring liner and well integrity. Optimizing the well start-up process in SAGD has been a challenge at Surmont and in the industry in general. SAGD well start-up involves heating bitumen through a mostly conductive process to allow the SAGD mechanism to initiate. A recent breakthrough in the circulation strategy for wells equipped with FCDs at Surmont was developed and implemented by the ConocoPhillips Technology and Operation teams. This new approach has been possible by integrating FCD characterization and erosion testing with complex engineering principles such as convective heating, sand control, reservoir multiphase flow and wellbore flow dynamics. ConocoPhillips commenced the implementation of the new strategy in the field between 2015 and 2016 with great success. Benefits of this circulation strategy by fully utilizing the FCD technology are numerous, including a reduction of circulation duration, substantial increase in early time oil and liquid production and accelerated well ramp-up. The paper begins by presenting the concept of this new circulation strategy. Then, details on various SAGD mechanisms and associated FCD physics are explained. Finally, field data is presented to illustrate the successful implementation of this strategy along with an analysis of the operating results.

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 score0.255
Threshold uncertainty score0.723

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 head0.015
GPT teacher head0.218
Teacher spread0.204 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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