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Record W2328689660 · doi:10.1071/aseg2012ab411

Fracture delineation and monitoring of geothermal and coal seam gas areas using magnetotellurics

2012· article· en· W2328689660 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueASEG Extended Abstracts · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsMagnetotelluricsGeothermal gradientGeologyCoal miningAquiferPetroleum engineeringCoalGeothermal energyFluid dynamicsFracture (geology)Mining engineeringGeophysicsPetrologyElectrical resistivity and conductivityGroundwaterGeotechnical engineering

Abstract

fetched live from OpenAlex

SummaryNew ways of energy production through the use of coal seam gas plays and geothermal hot dry rock and hot sedimentary aquifer systems pose challenges in identifying and monitoring fluid in the subsurface. We propose the use of the magnetotelluric (MT) method to image static and dynamic fluid distributions in the subsurface exhausting the contrast in electrical conductivity between resistive host rock and conductive fluid-filled, porous rock. Base line MT measurements provide reference transfer functions and inverse models to characterise the electrical conductivity distribute on which is linked with bore hole and other geophysical data to obtain knowledge about fluid distribution at depth. The reference models are used to accurately forward model fluid injection or extraction temporally and spatially. This work shows results from fluid injections at a hot dry rock system at Paralana, South Australia, and its applicability to other geothermal and coal seam gas systems.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.363

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 head0.023
GPT teacher head0.260
Teacher spread0.238 · 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