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Record W4389002289 · doi:10.2118/217422-ms

Biomineralization – A New Solution for Surface Casing Vent Flow

2023· article· en· W4389002289 on OpenAlexaboutno aff
John Griffin, Richard Bean, Randy Hiebert

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsCasingPetroleum engineeringAnnulus (botany)DrillingGeologyWellboreCloggingLost circulationGeotechnical engineeringDrilling fluidMining engineeringEnvironmental scienceEngineeringMaterials scienceMechanical engineeringComposite materialArchaeology

Abstract

fetched live from OpenAlex

Abstract A new solution to the increasingly important issue of surface casing vent flow (SCVF), a biocementation process involving the squeezing of biomineralizing fluids was utilized on a Canadian well. Initially developed by the United States Department of Energy (DOE) for the purpose of sealing leaks in carbon sequestration wells, this technology has been utilized in over 100 oil and gas wells across the United States and Canada to seal and repair damaged cement, restore wellbore integrity, and prevent the unwanted flow of hydrocarbons up the production and surface casing annular. The following paper represents a case study detailing a risk-based approach and field deployment assessing the technology's effectiveness on a well in Alberta. Abandonment operations which began on a well in Alberta, Canada in 2020 consisted of a series of zonal isolation plugs and cement retainer squeezes to eliminate surface casing vent flow. In March of 2023, with the vent flow still persistent at approximately 1 m3/day with 154 kPa build pressure, nonroutine abandonment operations began. The two previous cement retainer squeezes were drilled out down to the Mannville formation so new logs could be run. Biomineralization was identified as a viable solution to address SCVF on the well after initial analysis of the well indicated the presence of small aperture channels in the cemented annulus. In July 2023, the well was prepared for an annular squeeze utilizing biomineralization technology, and treatment commenced. Biomineralizing fluids were injected in intervals over the course of 48 hours, reducing injectivity by forming crystalline calcium carbonate, which has a similar chemical composition to limestone, to seal leakage pathways and eliminate gas flow. Over the course of treatment, 219 L of biomineralizing fluids were pushed into leakage pathways, with the injection rate reduced from 0.776 lpm to 0.026 lpm, constituting a 97% reduction. The injection rates, pressures, and total volumes at the conclusion of treatment indicated successful sealing of micron-sized channels. Vent monitoring technology confirmed this via a steady reduction in flow over the course of treatment, and the total elimination of flow and bubbles at surface just seven days later. Biomineralization technology has been used as a solution for sealing and repairing micro annuli and other channels in annular cement by several operators to eliminate surface casing vent flow in Canada.

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: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.062
GPT teacher head0.330
Teacher spread0.268 · 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
Published2023
Admission routes1
Has abstractyes

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