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Record W2076447823 · doi:10.2118/157922-ms

Elimination of Surface Casing Vent Flow and Gas Migration in the Lloydminster Area

2012· article· en· W2076447823 on OpenAlexaffabout
Kevin G. Macedo, Jason Schneider, Chuck Sylvestre, Qasim Masroor

Bibliographic record

VenueSPE Heavy Oil Conference Canada · 2012
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsHusky Energy (Canada)
Fundersnot available
KeywordsCasingPetroleum engineeringDrillingEnvironmental remediationCementWellboreProcess (computing)Service (business)CloggingEnvironmental scienceMining engineeringEngineeringBusinessComputer scienceMechanical engineeringMaterials science

Abstract

fetched live from OpenAlex

Abstract There are many areas in the Western Canadian Sedimentary Basin that present challenges with surface casing vent flows (SCVFs). Substantial resources have been invested in understanding the causes of these SCVFs, developing remediation processes for wells impacted by SCVFs and creating products to prevent SCVFs from occurring. Despite these efforts, SCVFs remain an issue in the industry. The first priority of the energy company and service company is to operate in a safe manner with high regard for the environment. A secondary goal is to be cost efficient to maximize production. In order to satisfy these goals and priorities, working together to understand the challenges becomes critical. A clear understanding of the challenges provides an opportunity for the service company to tailor cement blend performance with the goal of eliminating the presence of SCVFs and reducing the costs associated with the remediation process. This paper presents a case study in the Celtic field, located approximately 80 kms northeast of Lloydminster, Saskatchewan, Canada. A higher frequency of SCVFs was observed in the wells when increased bottom circulating temperatures, influenced by a nearby active steam chamber, were reported while drilling. At the elevated temperatures, cement blend modifications were made to allow for adequate placement with the new wellbore parameters. The cement blend underwent a review and optimization process with respect to the new wellbore parameters. Findings showed that a substantial difference between the circulating and gas formation temperatures created ideal conditions for SCVFs to occur. The prolonged setting of the cement at low temperatures was believed to be the main challenge to overcome. A unique cement additive was used to accelerate the setting of the slurry at relatively low temperatures while ensuring it would still be pumpable in a high temperature environment. After incorporating the new additive into the cement blend, the operating company immediately saw an elimination of the SCVF in subsequent wells. This paper will review the steps taken to reduce and eliminate SCVF issues in the Celtic area, some parameters and characteristics of a well that impact SCVF, and steps that can be taken in the cement blend design to mitigate SCVF issues.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.189
Teacher spread0.174 · 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

Citations7
Published2012
Admission routes2
Has abstractyes

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