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Record W4229799154 · doi:10.2523/97944-ms

Optimized Abandonment Procedures Improved Success and Results in Central California Heavy-Oil Field

2005· article· en· W4229799154 on OpenAlexaboutno aff
Dana Glessner, M. B. Cook E. W. Dean, Mark Haire, Daniel Bour

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsAbandonment (legal)CitationLibrary scienceComputer scienceArchaeologyGeographyPolitical science

Abstract

fetched live from OpenAlex

Optimized Abandonment Procedures Improved Success and Results in Central California Heavy-Oil Field D. Glessner; D. Glessner Chevron Search for other works by this author on: This Site Google Scholar M. Dean; M. Dean Consultant Search for other works by this author on: This Site Google Scholar M. Haire; M. Haire Halliburton Search for other works by this author on: This Site Google Scholar D. Bour D. Bour Halliburton Search for other works by this author on: This Site Google Scholar Paper presented at the SPE International Thermal Operations and Heavy Oil Symposium, Calgary, Alberta, Canada, November 2005. Paper Number: SPE-97944-MS https://doi.org/10.2118/97944-MS Published: November 01 2005 Cite View This Citation Add to Citation Manager Share Icon Share MailTo Twitter LinkedIn Get Permissions Search Site Citation Glessner, D., Dean, M., Haire, M., and D. Bour. "Optimized Abandonment Procedures Improved Success and Results in Central California Heavy-Oil Field." Paper presented at the SPE International Thermal Operations and Heavy Oil Symposium, Calgary, Alberta, Canada, November 2005. doi: https://doi.org/10.2118/97944-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Thermal Operations and Heavy Oil Symposium Search Advanced Search Abstract This case-history paper presents the development background and detail of optimized procedures followed to plug and abandon wells in a cyclic-steam well in central California. Improvements that resulted in the success are detailed and explained.Abandonment processes included identification, using tilt-meter events, of holes in casing and/or casing parting. Temperature surveys and/or radioactive surveys confirmed and located depth of the hole in the casing. Specific procedures were then followed to abandon the well below the part, at the part, and then above the part in the casing. Inspection and testing of the casing were also conducted to help ensure that additional holes were not present in the casing before the abandonment was complete. In the rare instances that additional holes were found, they were squeezed off separately with cement. Key to the success of this procedure was squeezing thixotropic cement instead of setting balanced plugs across zones of interest. This method allowed for short turn-around times to resume operations and helped ensure that the cement remained where it was originally placed. Keywords: placement, perforation, cement chemistry, plug, cement, cement slurry, consultant, cement formulation, slurry, procedure Subjects: Casing and Cementing, Casing design, Cement formulation (chemistry, properties), Completion Installation and Operations Copyright 2005, SPE/PS-CIM/CHOA International Thermal Operations and Heavy Oil Symposium You can access this article if you purchase or spend a download.

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)0.003
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.009
GPT teacher head0.250
Teacher spread0.242 · 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".

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Citations1
Published2005
Admission routes1
Has abstractyes

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