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Record W2057779536 · doi:10.2118/149272-ms

Case Studies: Impact of high Salt Tolerant Friction Reducers on Fresh Water Conservation in Canadian Shale Fracturing Treatments

2011· article· en· W2057779536 on OpenAlexaboutno aff
Javad Paktinat, Bill O’Neil, Michael Tulissi

Bibliographic record

VenueCanadian Unconventional Resources Conference · 2011
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHydraulic fracturingPetroleum engineeringOil shaleFracturing fluidBrineDirectional drillingShale gasVolume (thermodynamics)GeologyEnvironmental scienceMaterials scienceChemistryDrilling

Abstract

fetched live from OpenAlex

Abstract Tight low permeability shale reservoirs must be stimulated to produce commercially viable gas quantities. This requires large volumes of slick water frac fluids to be successfully pumped at high rates into the shale formations. Friction reducers (FR’s) are used for stimulating shale reservoirs mainly to overcome tubular friction pressure and establish high pumping rates. Slickwater fracturing, also known as water frac, is the process where polyacrylamide type polymers are used to reduce tubular friction pressure. Currently, fracturing fluid volume and proppant requirements have increased significantly with the advent of horizontal shale stimulation. Depending on the shale play, it is not uncommon to drill over 1,500 meters of lateral section to maximize Reservoir Stimulated Volume, SRV. (Mayerhofer et al., 2008). Several commonly practiced technologies, such as multi-stage fracturing of horizontal wells have increased frac volume requirements per well to a point that has created concerns by regulatory agencies. At the same time, restrictions limiting fresh water usage and environmental concerns surrounding flowback fluids have created a demand for chemicals that perform in high concentration brines. Several water treatment methods are being used in the industry to remove impurities from flowbacks for reuse as frac water for fracturing. However, most treatments do not remove dissolved salts from the water requiring either development of a brine tolerant friction reducer or distillation to maintain high performance. This study presents experimental and case studies of various cationic and anionic FR’s of similar molecular weight in high brine flowback conditions of Montney produced water and a Horn River source well. Actual produced water and finger print water analyses of Montney and Horn River shale reservoirs were used as a brine source to evaluate friction reducers. A dynamic friction loop flow apparatus was used as the main tool to evaluate the rheological properties and the friction reduction contributions of FRs in high concentration brine waters. Field data collected for two case histories document the ability of the high brine tolerant friction reducers to perform at a level consistent with traditional products used in fresh water. This confirms the experimental data obtained from dynamic friction loop investigations. Results obtained from this study can be used to optimize slickwater frac treatments where produced water is used as the main source of frac water. This paper examines the following: Comparison studies of new brine tolerant friction reducer with conventional FR’s used in the oilfield.Experimental data illustrating the performance of newly developed FR’s in high concentration brine from post fracture flowbacks.Cost advantage of using less polymer, while reducing fresh water and disposal of the flowbacks.Case studies of wells treated with the new friction reducers show performance in brines similar to those achieved with conventional FR’s when used in fresh water.

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)0.002
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 score0.271
Threshold uncertainty score0.546

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0060.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
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 head0.044
GPT teacher head0.260
Teacher spread0.216 · 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

Citations29
Published2011
Admission routes1
Has abstractyes

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