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Record W1993910178 · doi:10.2118/144210-ms

High Brine Tolerant Polymer Improves the Performance of Slickwater Frac in Shale Reservoirs

2011· article· en· W1993910178 on OpenAlexaboutno aff
Javad Paktinat, Bill O’Neil, Carl Aften, Micheal Hurd

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOil shaleHydraulic fracturingFracturing fluidPetroleum engineeringBrineTight oilShale gasWorkoverLimitingEnvironmental engineeringEnvironmental scienceGeologyEngineeringWaste managementChemistryMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Shale reservoirs of North America require a large volume of frac fluid at high pumping rates to allow maximum contact with the reservoir rock to extend the drainage radius. In the early stages of shale play development, these tight low permeability reservoirs were subjected to different types of fracturing techniques to achieve desirable, pre-determined frac designs and post frac cleanups. Crosslinked borate, zirconate, and linear frac fluid systems were attempted with below par post frac performance. However, gas production was improved when a slickwater frac containing a predominantly low dosage friction reducer and surfactant was used. Slickwater is becoming the most popular fracturing fluid in recent years. Today, the industry has adopted slickwater systems as the workhorse of stimulating shale reservoirs due in part to its availability, low cost, and rapid well clean up. With the advent of the horizontal and multi-lateral shale fracturing techniques of up to 40 stages, shale frac fluid requirements have increased volume of up to 900,000 bbls of slickwater per well. In areas like Pennsylvania and western Canada where disposal wells are not an option, recycling and re-using of produced water is becoming an economical alternative method of reducing demands for fresh water while eliminating disposal costs of produced water. Simultaneously, most producing states and provinces are adopting restrictions or limiting the use of fresh water for fracturing proposes. Fresh water consumption issues and environmental regulations surrounding the flowback waters and its disposal have created a challenge for the industry and operators. Operators are adopting means of water treatment to manage water needs by utilizing chemical and mechanical methods of removing unwanted solids and impurities from the flowback water. These techniques, however, do not remove dissolved salts and hardness from the flowback water. In fact, examination of field recycled water shows that most treatments not only increase overall salinity but also increase their multivalent ionic content. This paper examines the merits of utilizing new high brine tolerant polymers in multivalent high brine waters. Horn River and Marcellus flowback and production waters were analyzed to determine their salinity. Both synthetic brine and produced water representing Horn River production water were then used as a brine source for this investigation. The objective was to utilize high molecular weight water internal based polyacrylamides as the new friction reducers to examine performance under hostile high brine conditions. Field case studies validate the experimental results which are presented in this study. Test results show that the new high brine tolerant friction reducers significantly improve performance of slickwater fracturing. Experimentally, several friction reducers were tested to evaluate their performance. This study was conducted mainly through using a 50 liter capacity friction loop through one quarter inch stainless steel pipe at a Newtonian Reynolds number of 50,000. Field and experimental results presented in this study show that the new friction reducers exhibits significant performance improvement when produced water is used in shale fracturing treatments. Trends in core flow behavior are also presented.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.192
Teacher spread0.182 · 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 designBench or experimental
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

Citations14
Published2011
Admission routes1
Has abstractyes

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