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Record W2614502852 · doi:10.2118/179019-pa

Minimize Formation Damage in Water-Sensitive Montney Formation With Energized Fracturing Fluid

2017· article· en· W2614502852 on OpenAlexafffund
Bing Kong, Shuhua Wang, Shengnan Chen

Bibliographic record

VenueSPE Reservoir Evaluation & Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFracturing fluidTight gasPetroleum engineeringHydraulic fracturingGeologyFluid dynamicsWell stimulationGeotechnical engineeringReservoir engineeringMechanicsPetroleum

Abstract

fetched live from OpenAlex

Summary Slickwater has been widely used for hydraulic fracturing because it is inexpensive and able to carry proppants into the fracture (Schein 2005; Palisch et al. 2010). This fluid, however, is unsuitable for water-sensitive formations, such as the Montney formation. This is because water saturation around the fractures increases, and the clay swells when water leaks into the matrix, both of which hinder the flow of natural gas from the matrix into the fractures. N2- or CO2-energized water-based fracturing fluids have been widely used in water-sensitive formations because they can minimize fluid leakoff during fracturing and help achieve higher-load fluid recovery during flowback (Burke and Nevison 2011; Barati and Liang 2014). In this paper, multiphase numerical simulations are applied to study the formation-damage mitigation in the Montney tight reservoir with energized fracturing fluid. A simulation model is built and history-matched with flowback and early production data gathered from a typical Montney tight gas well. The behavior of the multiphase fluid leakoff and flowback is studied. Sensitivities of the foam quality of the fracturing fluid on the load fluid recovery are analyzed, as is the well productivity after stimulation. Statistical analysis to study the performance of energized fracturing in the water-sensitive Montney formation is conducted on the stimulation and production data of more than 5,000 Montney wells. We found that multiphase fracturing fluid has less dynamic fluid leakoff compared with that of a single-phase fracturing fluid (i.e., water). The major fluid leakoff occurs during the static leakoff period between the end of the stimulation processes and the start of the flowback. The gas phase penetrates deeper and faster into the reservoir matrix compared with the liquid phase, which contributes to the increased flowback volume of the fracturing fluid. Formation damage caused by fracturing-fluid leakoff can affect both early and long-term production. In addition, N2 foam leads to the highest-load fluid recovery in the Montney formation, which is 1.6 times that of CO2 foam. This work provides critical insights into understanding the performance of using energized fracturing fluid to mitigate formation damage in tight formations.

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 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)0.001
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 score0.165
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.246
Teacher spread0.229 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations16
Published2017
Admission routes2
Has abstractyes

Explore more

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