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Record W4253974329 · doi:10.2118/2006-078

Laboratory Testing of Novel Sealant for Leaky Wells

2006· article· en· W4253974329 on OpenAlexaffabout
O. Bibic, M. Polikar, J. Boyd

Bibliographic record

VenueCanadian International Petroleum Conference · 2006
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsUniversity of AlbertaEncana (Canada)
Fundersnot available
KeywordsSealantPetroleum engineeringComputer scienceForensic engineeringGeologyMaterials scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

Abstract Many abandoned gas wells in western Canada leak gas to the surface. This paper presents the results of an experimental study to determine the possibility of using an asphalt-in-water emulsion as sealant for these abandoned leaky wells as a more efficient and cost-effective alternative to the conventional cement grout barrier. A second application of this process would be to hinder the water flow from water producing formations. The asphalt-in-water emulsion used in the experiments had asphalt particles with an average particle size of around 4 µ m and a 60 percent internal phase concentration. The emulsion exhibited a pseudo-plastic behaviour. Its viscosity ranged from 60 cp at a shear rate of 60 rpm to 145 cp at a shear rate of 6 rpm. The emulsion was found to be stable, even though it settled with time. Its original properties were retained after agitation and settling had occurred. Core flow experiments were performed in order to simulate injection in the near-wellbore region. The cores were prepared using silica sand with a 60- to 80-mesh size. The resulting cores had a porosity range of 25 to 32 percent and a permeability range of 2.5 to 9 Darcy. Experiments were performed under varying injection pressure conditions. In each case, solid plugs were formed and their length in the porous medium increased as a function of the injection pressure. In order to extend the length of the plugs, several anionic surfactants were tested as pre-flush solutions for conditioning the surface of the sand grains. This resulted in increasing the emulsion penetration into the cores. The basic mechanism of the process is to pressure up the emulsion next to a formation, forcing the emulsified asphalt to enter the porous medium and to form a flexible sealing plug. We surmise that the plug is formed through a combination of two pore blocking mechanism: one by blocking the pores by the larger-than-pore droplets, and the other by adsorbing onto the sand grain surfaces. The experimental results have shown that the asphalt-in-water emulsion can be successfully used to seal a gas or water producing formation. The study concludes with recommendations for field application and suggests ways for further research to improve the process. Introduction Proper well abandonment is the final and critical step in the process of natural gas and oil exploitation. Depleted oil and gas wells produce small non-economic amounts of gas, often the result of gas migration either through the cracks, fractures and voids in the formation along the outer wall of the casing, or between the original cement and the formation. The gas may escape to the atmosphere by flowing around the surface casing or migrate into shallow aquifers. The current procedures for well abandonment involve placing a cement plug over the production zone and maintaining a column of water from the top of the plug to the surface. Sometimes, these procedures may not seal off all of the producing zones and remedial well abandonment treatments are needed.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.016
GPT teacher head0.200
Teacher spread0.184 · 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 designBench or experimental
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

Citations1
Published2006
Admission routes2
Has abstractyes

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