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Record W4243279496 · doi:10.2118/119478-pa

Frac-Fluid Recycling and Water Conservation: A Case History

2009· article· en· W4243279496 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSPE Production & Operations · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic shortageEnvironmental scienceProduced waterEnvironmental engineeringFracturing fluidWater scarcityEnforcementPetroleum engineeringWaste managementEngineeringGeographyAgricultureArchaeology

Abstract

fetched live from OpenAlex

Summary Shallow-gas fracturing is very prevalent in western Canada. Several thousand wells are typically drilled and completed in the shallow- gas fields every year. All these wells are typically hydraulically fractured. Before 1999, after testing for microtoxicity, the flowback fluid was allowed to be land farmed in southeastern Alberta. In that year, the Alberta Energy and Utilities Board began more stringent enforcement of Guide 58, which required that flowback fluid be disposed in a disposal well. At that time, one operator typically had a project of 300 to 400 wells with an average of 5 fracs per day during spring/sum- mer. When the fluid could no longer be land farmed, attempts were made to recycle the flowback fluid. The chemistry of the surfactant-gel fluid was insensitive to the water quality, which made the recycling concept successful. Several cost advantages were achieved, which will be detailed in the paper. These included freshwater costs, transportation costs, disposal costs, and chemical costs. An additional advantage that was realized involved a 50% reduction in the freshwater requirements for a project—a significant additional benefit because several years of drought conditions have caused water shortages in the area. This paper will detail the chemistry of the fracturing gel, its field application, the optimized recycling operation, and the details on cost advantages achieved, as well as future direction for further reduction in freshwater usage on a project basis.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.674
Threshold uncertainty score0.999

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)0.0020.000

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 head0.012
GPT teacher head0.207
Teacher spread0.195 · 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