MétaCan
Menu
Back to cohort
Record W3119340436 · doi:10.3390/app11020697

Well-Doublets: A First-Order Assessment of Geothermal SedHeat Systems

2021· article· en· W3119340436 on OpenAlexaff
SeyedBijan Mahbaz, Ali Yaghoubi, Alireza Dehghani-Sanij, Erfan Sarvaramini, Yuri Leonenko, Maurice B. Dusseault

Bibliographic record

VenueApplied Sciences · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsGeothermal energyGeothermal gradientGeomechanicsEnvironmental scienceGeothermal heatingRenewable energyPetroleum engineeringGeologyGeotechnical engineeringEngineeringGeophysics

Abstract

fetched live from OpenAlex

Renewable and sustainable energy sources can play an important role in meeting the world’s energy needs and also in addressing environmental challenges such as global warming and climate change. Geothermal well-doublet systems can produce both electrical and thermal energy through extracting heat from hot-water aquifers. In this paper, we examine some potential challenges associated with the operation of well-doublet systems, including heat conductivity, chemical, and mechanical issues. In these systems, geomechanics issues such as thermal short-circuiting and induced seismicity arise from temperature and pressure change impacts on the stress state in stiff rocks and fluid flow in fractured rock masses. Coupled chemical processes also can cause fluid channeling or formation and tubular goods plugging (scaling) with precipitates. Mechanical and chemical disequilibrium conditions lead to increased production uncertainties; hence risk, and therefore coupled geo-risk assessments and optimization analyses are needed for comparative commercialization evaluations among different sites. The challenges related to heat transfer processes are also examined. These studies can help better understand the issues that may arise during the operation of geothermal well-doublet systems and improve their effectiveness, subsequently reducing associated costs and risks.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.709
Threshold uncertainty score0.993

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)0.0080.000

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 head0.018
GPT teacher head0.279
Teacher spread0.262 · 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.

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

Citations25
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueApplied SciencesSame topicCO2 Sequestration and Geologic InteractionsFrench-language works237,207