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Record W1987343650 · doi:10.2118/2009-056-ea

Benefits of Quality Hydrocarbon Fracturing Fluid Recycling

2009· article· en· W1987343650 on OpenAlexaboutno aff
JH Edwards, R. Tudor, D. W. Jones

Bibliographic record

VenueCanadian International Petroleum Conference · 2009
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCitationQuality (philosophy)PopularityComputer scienceOperations researchLibrary scienceEngineeringPolitical sciencePhysicsLaw

Abstract

fetched live from OpenAlex

Abstract In these times of budget conscious oil and gas companies, finding solutions to save money without compromising output is always on the minds of management. The idea of reusing fracturing fluid flowback has gained popularity over the years. However, care must be taken to properly recycle these fluids to allow for multiple reuses without major destabilization of the fracturing system. Hydraulic fracturing is used for stimulating the production of wells, in particularly gas wells. Fracturing can be performed using either hydrocarbon based fluids or water based fluids. Due to issues such as water blockages and swelling of formation clays, the use of hydrocarbon based fluids for fracturing remains popular despite the cost difference. In general successful fracturing fluids must be gelled (increase in viscosity) and broken (decrease in viscosity). Completion companies use three main chemical components to gel and break a hydrocarbon fracturing fluid: gellant, activator and breaker. Recycling fracturing fluid flowback will involve the removal of these completion chemicals as well as other contaminants. This paper will look at a case study which shows the economic benefits of employing a high quality hydrocarbon fracturing fluid recycling process; and the resulting successful performance on the overall production of using such fluids. Introduction Fracturing of formation to increase the production is a practice that has been done since the 1950's. A fluid is injected into the formation at a rate and pressure great enough fracture the rock. Once the fracture is initiated fluid is continued to be pumped to propagate the fracture. A proppant such as sand, ceramic spheres or similar product is added to the fluid and will be left in the fracture to enable the production to increase due to a relative permeability difference with the formation. Chemicals are added to the fluid to enhance the characteristics of friction, viscosity, leakoff and other variables. These chemicals that increase the viscosity are added to greatly increase the viscosity during the pumping and then decrease after the pumping to aid in the placement of the proppant and then to recover the fracture fluid. The choice of fluids is dependent on economics and formation compatibilities. Fracturing with water, although less expensive, has associated problems of water phase trapping and fracture permeability reductions1,2. In Canada, hydrocarbon based fracture fluids have become the preferred product in deeper, lower permeability gas zones. The basic chemicals added to these fluids are gallant, activator and breaker. These chemicals will work together to increase the viscosity of the base hydrocarbon from 10 cP to well over 400 cP, and then break the density back to 10 cP range. The time to break and the maximum viscosity are based on the loadings of the chemicals, and the temperature of the formation being stimulated (Fig. 1). The cost of hydrocarbon fracture fluid is dependent on the quality, but all follow the cost of crude. During the last few years the process of recycling fracture hydrocarbons has become an economical decision.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

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

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 head0.243
Teacher spread0.226 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

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