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Record W4245852460 · doi:10.2523/iptc-11891-ms

Post-Frac Analysis Based on Flowback Results Using Chemical Frac-Tracers

2008· article· en· W4245852460 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Petroleum Technology Conference · 2008
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsOncolytics Biotech (Canada)
Fundersnot available
KeywordsTRACERFracturing fluidFracture (geology)ChemistryHydraulic fracturingPetroleum engineeringMineralogyGeologyGeotechnical engineeringPhysics

Abstract

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Abstract Chemical frac tracing is used to evaluate flowback and cleanup efficiencies. The technique utilizes a family of unique, environmentally-friendly, fracturing fluid compatible chemical tracers to quantify segment-by-segment recovery for individual fracturing treatments and stage-by-stage recovery for multi-stage fracturing treatments. These chemical tracers with their unique chemical characteristics are mixed at a known concentration into frac fluid stages as the frac fluid is pumped downhole. Upon flowback, samples are collected and analyzed for tracer concentration. With the use of the mass balance method the flowback efficiency for each stage is calculated. These precise flowback calculations yield a more accurate assessment of cleanup efficiency. This paper presents several case histories in which the technique was implemented. Results and fracture flowback prognoses are presented. The results are also used to assess post-frac performance as a function of flowback efficiency. Introduction Chemical Frac Tracers Chemical frac tracers, CFT's, are used to precisely calculate flowback and hence flowback efficiency and to evaluate fracture cleanup. Various chemical tracers with unique chemical characteristics are mixed at a known concentration and injected according to a pre-determined design throughout the frac fluid stages, such as the pad and the propping laden fluid stages. The characteristics of these tracers are unique. They do not react with each other, the formation or the tubular. They do not degrade with temperature or time, do not self-concentrate, and do not react with frac fluids. These tracers are detectable at low concentrations of 50 ppt (parts per trillion). They are also environmentally safe to handle, pump downhole and dispose. They are soluble in water, and unlike polymers, do not concentrate upon leakoff. Upon flowback, samples are collected and analyzed for tracer concentration. With the use of the mass balance method, flowback of each frac fluid stage is calculated, and hence flowback efficiency for each stage of frac fluid injected. The precise flowback calculation for each frac fluid stage yields the fracture cleanup efficiency. Chemical frac tracing can also be used as a means to understand vertical communication between zones. Under this scenario, one chemical tracer is injected into each zone. Each zone is flowed back individually after a period of shut-in allowing the flow of fluid within the formation. Samples are collected and analyzed for tracer concentrations. If zones are communicating vertically under static conditions, the tracer from one zone can flow into other zones and hence will be detected accordingly.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.236
Teacher spread0.224 · 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