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Record W2090043699 · doi:10.2118/1215-0083-jpt

Technology Focus: Water Management (December 2015)

2015· article· en· W2090043699 on OpenAlexaboutno aff
Syed A. Ali

Bibliographic record

VenueJournal of Petroleum Technology · 2015
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHydraulic fracturingProduced waterDirectional drillingResidual oilPetroleum engineeringEnvironmental scienceDrilling fluidWater qualityFracturing fluidGeologyWaste managementDrillingEngineering

Abstract

fetched live from OpenAlex

Technology Focus Horizontal drilling followed by multistage fracturing is the most prevalent mode of hydrocarbon extraction from shales. Hydraulic fracturing of a well encompasses, on average, approximately 30 fracturing stages, with each stage using approximately 3,800 bbl of fresh water, equating to approximately 114,000 bbl for each well. The need for such vast amounts of fresh water in hydraulic fracturing significantly affects water availability and sourcing and the cost and logistics of accessing and trucking the water to the wellsite. Furthermore, regulations designed to protect communities and the environment from potential sources of contamination are becoming increasingly stringent. Approximately 10–30% of the fresh water injected into a well during fracturing treatments returns to the surface along with various amounts of formation water, henceforth referred to as produced water. Thus, in the interest of conservation and sustainability, it is highly desirable to maximize any opportunity to reuse the produced water for subsequent fracturing treatments. Produced water usually contains residual hydrocarbon; high levels of total dissolved solids (TDS), including sodium, calcium, magnesium, barium, and other salts; suspended solids; and residual production chemicals. Reclaiming produced water as the base fluid for hydraulic fracturing not only helps to alleviate the industry’s dependence on fresh water but also lowers the overall cost of the fracturing operations. Conventional fracturing-fluid systems require fairly low TDS to achieve stable rheology, so produced water requires extensive treatment before it can be used for fracturing. There have been attempts to develop fluids that can be prepared with produced waters that contain a limited amount of TDS, typically less than 30,000 ppm. However, several operating areas, including the Haynesville, Marcellus, and Bakken shales and west Texas areas, have produced waters with much higher salinity (TDS concentrations greater than 150,000 ppm). An ideal solution would be to reuse the high-TDS produced water in subsequent fracturing treatments with minimal filtration to remove the suspended solids. In response, a growing group of chemical suppliers, researchers, and service companies are on a mission to develop fracturing fluids using high-TDS produced water as a base fluid that provides a stable rheology. The papers featured this month deal with the formulation of stable fracturing fluid from high-TDS produced water. I urge you to look at OnePetro, the SPE online library, and download papers. You will find updates on best practices, case studies, new fluid formulations, and much more. JPT Recommended additional reading at OnePetro: www.onepetro.org. IPTC 18142 Slickwater Chemistry Concerns and Field Water Management in Tight Gas by David Langille, Shell Canada, et al. SPE 173371 Chemical Compatibility of Mixing Utica and Marcellus Produced Waters: Not All Waters Are Created Equal—A Case Study by F.B. Woodward, Shell Exploration & Production, et al. SPE 173324 The Freshwater Neutral Challenge: The Need for Protection, Reduction, Innovation, and Conservation by R. Greaves, Southwestern Energy, et al. SPE 173372 Overcoming Obstacles for Produced Water in Bakken Well Stimulations by Darren D. Schmidt, Statoil, et al.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.745
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.222
Teacher spread0.215 · 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 designNot applicable
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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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