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Record W2953334854 · doi:10.1111/gwat.12917

Conventional Oil—The Forgotten Part of the Water‐Energy Nexus

2019· article· en· W2953334854 on OpenAlexafffundabout
Jennifer C. McIntosh, Grant Ferguson

Bibliographic record

VenueGround Water · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Saskatchewan
FundersGlobal Water FuturesU.S. Environmental Protection Agency
KeywordsProduced waterBrackish waterEnvironmental sciencePetroleum engineeringEnhanced oil recoveryVolume (thermodynamics)GroundwaterOil productionEnvironmental engineeringFossil fuelSaline waterAquiferSalinityGeologyWaste managementGeotechnical engineeringEngineeringOceanography

Abstract

fetched live from OpenAlex

The impacts of unconventional oil and gas production via high-volume hydraulic fracturing (HVHF) on water resources, such as water use, groundwater and surface water contamination, and disposal of produced waters, have received a great deal of attention over the past decade. Conventional oil and gas production (e.g., enhanced oil recovery [EOR]), which has been occurring for more than a century in some areas of North America, shares the same environmental concerns, but has received comparatively little attention. Here, we compare the amount of produced water versus saltwater disposal (SWD) and injection for EOR in several prolific hydrocarbon producing regions in the United States and Canada. The total volume of saline and fresh to brackish water injected into depleted oil fields and nonproductive formations is greater than the total volume of produced waters in most regions. The addition of fresh to brackish "makeup" water for EOR may account for the net gain of subsurface water. The total amount of water injected and produced for conventional oil and gas production is greater than that associated with HVHF and unconventional oil and gas production by well over a factor of 10. Reservoir pressure increases from EOR and SWD wells are low compared to injection of fluids for HVHF, however, the longer duration of injections could allow for greater solute transport distances and potential for contamination. Attention should be refocused from the subsurface environmental impacts of HVHF to the oil and gas industry as a whole.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.819
Threshold uncertainty score1.000

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)0.0050.001

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 head0.005
GPT teacher head0.161
Teacher spread0.157 · 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; both teacher heads agree on what is shown here.

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

Citations28
Published2019
Admission routes3
Has abstractyes

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