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The role of fractures in flow partitioning during minewater geothermal energy extraction

2020· article· en· W3011614210 on OpenAlexaboutno aff
Michael Chandler, Julian Mecklneburgh, E. H. Rutter

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCoal Properties and Utilization
Canadian institutionsnot available
Fundersnot available
KeywordsGeothermal gradientBoreholeHeat exchangerGeothermal energyGeothermal heatingEnvironmental scienceFlow (mathematics)Coal miningGeologyPorous mediumPetroleum engineeringCoalPorosityGeotechnical engineeringWaste managementEngineeringMechanicsGeophysicsMechanical engineeringPhysics

Abstract

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<p>The UKGEOS Glasgow research field site comprises a network of 12 boreholes into flooded coal mines, and is designed to observe how warm water moves around the abandoned mine workings over time <em>(Monaghan et al., 2018)</em>. Minewater geothermal projects involve the redevelopment of abandoned mining areas into large volume, low temperature resources and use heat pumps to drive heating for homes, industry or agriculture. This technique has proven potential as a renewable, decarbonised heat source providing reliable heating, cooling and heat storage with stable pricing to former mining areas.</p><p>Flow through minewater systems is partitioned between flow through the mine voids, through fractured media, and through porous media. This heterogeneity in flow is crucial to the development of models to predict the efficacy of minewater geothermal systems, as water flowing through the fractured material should absorb more heat than that flowing directly through the mine voids. This heat exchange then goes on to control the rate at which heat can be sustainably extracted from the minewater system.</p><p>The majority of fluid flow has generally been assumed to be through the mine voids. However, the proportion of fluid flow through the porous wallrocks is very sensitive to the fracture populations that they contain, due to the shallow nature of these mine workings leaving them under low stress.  Geothermal tests at the Gaspé mines in Québec demonstrate this clearly, with high wallrock conductivities (10<sup>-6</sup>-10<sup>-4</sup> m.s<sup>-1</sup>) attributed to mine-blasting <em>(Raymond & Therrien, 2008)</em>. Coal mining in the Glasgow area was predominantly carried out using the Pillar & Stoop or Longwall methods, which lead to very different damage states in the wallrocks, and so the effect of these fracture populations is expected to have a large effect on flow partitioning.</p><p>Here, relationships between in-situ stress, fracture population and permeability were determined from well-core samples of the Glasgow Main Coal and underlying mudstone and sandstone strata, in order to characterise how flow may be partitioned within different regions of these mine-workings.</p><p>Stress-dependent permeability and storativity were measured using the osciallting pore-pressure method, and elastic tensors were determined using an array of ultrasonic transducers. Axial fractures were then generated within these samples under low triaxial stress states, and the change in permeability with induced fractures then measured at a single stress state, with the newly developed fracture population characterised through the changes in the elastic tensor.</p><p><em>Monaghan, A. A., Starcher, V., Dochartaigh, B. É. Ó., Shorter, K., & Burkin, J. (2018)</em>. <strong>UK Geoenergy Observatories : Glasgow Geothermal Energy Research Field Site - Science infrastructure.</strong> http://nora.nerc.ac.uk/id/eprint/521444/%0A</p><p><em>Raymond, J., & Therrien, R. (2008)</em>. L<strong>ow-temperature geothermal potential of the flooded Gaspé Mines, Québec, Canada.</strong> Geothermics. https://doi.org/10.1016/j.geothermics.2007.10.001</p>

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 score0.117
Threshold uncertainty score0.157

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 head0.005
GPT teacher head0.177
Teacher spread0.172 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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