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Record W2486791521 · doi:10.2118/174461-pa

Application of a Novel Hyperbranched-Polymer Fracturing-Fluid System in a Low-Permeability Heavy-Oil Reservoir

2016· article· en· W2486791521 on OpenAlexaff
Yueliang Liu, Huazhou Li

Bibliographic record

VenueSPE Production & Operations · 2016
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
FundersChina Scholarship Council
KeywordsMaterials scienceShearing (physics)PolymerFracturing fluidHydraulic fracturingSwellingPermeability (electromagnetism)Composite materialPetroleum engineeringGeologyChemistry

Abstract

fetched live from OpenAlex

Summary Hydraulic fracturing can be used for stimulating low-permeability heavy-oil reservoirs. It is challenging to achieve a high degree of fracturing-fluid flowback, as well as a low degree of formation damage, in low-permeability heavy-oil reservoirs. This research investigates the application of a novel hyperbranched-polymer fracturing fluid in low-permeability heavy-oil reservoirs. Such hyperbranched polymer is characterized by Fourier-transform infrared (FTIR) spectrophotometry. It has numerous end groups and possesses a 3D spherical molecular structure with many branches. Laboratory tests are conducted to evaluate the thermal stability and shearing resistance, reversible-crosslinking performance, salinity tolerance, static-filtration performance, gel-breaking performance, and sand-carrying performance. The degrees of core damage are evaluated through conducting coreflooding experiments, where the cores are treated with two kinds of gel-breaking fluids formed by hyperbranched-polymer fracturing fluid and guar fracturing fluid, respectively. Laboratory tests show that the hyperbranched-polymer fracturing fluid has good rheological characteristics, a high swelling ratio, a high proppant-carrying performance, and good thermal stability and shearing resistance. After being sheared for 90 minutes under 170 s−1 at 150°C, it can still reverse to gel with high strength because of its good reversible-crosslinking performance. This fracturing fluid exhibits a high-salinity tolerance. Furthermore, the hyperbranched polymer has a high swelling ratio. Field applications in some wells in China show that the friction loss of this fracturing fluid during fracturing is approximately 30 to 50% of that of the normal guar fracturing fluid. Thus, it has an ultralow friction-loss feature. As for the same reservoir, hyperbranched-polymer fracturing fluid has a higher flowback ratio compared with the guar fracturing fluid. Besides, its cost is approximately 75% of that of normal guar fracturing fluid, making it a clean and cost-effective system. The fracturing fluid prepared with hyperbranched polymer possesses outstanding technical advantages and good cost effectiveness, implying a promising application in the large-scale fracturing stimulation of low-permeability heavy-oil reservoirs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.441
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2016
Admission routes1
Has abstractyes

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