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Record W2787713105 · doi:10.14288/1.0362574

An investigation into the controls and variability of the flowback water inorganic geochemistry of the Montney Formation, Northeastern British Columbia and Northwestern Alberta, Canada

2018· article· en· W2787713105 on OpenAlexaboutno aff
Jennifer Nicole Owen

Bibliographic record

VenuecIRcle (University of British Columbia) · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyGeochemistryHydrology (agriculture)Physical geographyGeographyGeotechnical engineering

Abstract

fetched live from OpenAlex

The Montney Formation is the principal unconventional hydrocarbon reservoir currently being developed in Canada. The flowback water from 31 wells located on 9 well pads was sampled over time and analyzed for major ions, key minor ions, and δ¹⁸O and δ²H isotopes. The injected hydraulic fracturing fluids and produced waters, if available, were analyzed for the same parameters. The results of the study are used to compare the flowback water chemistry between wells and investigate the variables that have a significant influence on the chemistry. When comparing the flowback water chemistry between multiple wells, consideration must be given to the length of the flowback period, as the major ion concentrations typically increase over time. The dominant influence on the increasing concentrations is mixing between hydraulic fracturing fluid and formation water. Cl and stable water isotopes were used as conservative tracers to calculate the increasing proportions of formation water. These proportions were used with geochemical models to determine that mixing explains the Na and K concentrations, while mixing with ion exchange is influencing Ca, Mg, and Sr concentrations. Sulfate concentrations are influenced by pyrite oxidation and sulfate reduction. The rate of increase of the major ions varies between wells, although it is often, but not always, similar between wells completed at the same site, due to similarities in reservoir properties and well completion. The inconsistency is due to the many variables that may impact the flowback water chemistry. A multiple regression analysis identified shut-in time as an important variable, with longer shut-in correlating to higher concentrations. The chemistry of hydraulic fracturing fluids and formation waters were found to be important variables for some ions. The minor ions included in the study are Ba, B, and Li. Ba concentrations are likely related to barite dissolution/precipitation and are highest where sulfate concentrations are low. B and Li concentrations are both dominantly influenced by mixing and may vary due to differences in formation water chemistry. Overall, the results are expected to contribute to the growing knowledge on flowback water chemistry and its use in investigating the processes occurring in the reservoir during hydraulic fracturing.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.003
GPT teacher head0.133
Teacher spread0.130 · 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".

Quick stats

Citations3
Published2018
Admission routes1
Has abstractyes

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