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Record W1867553985 · doi:10.1190/geo2014-0091.1

Energy-based hydraulic fracture numerical simulation: Parameter selection and model validation using microseismicity

2015· article· en· W1867553985 on OpenAlexafffund
Neda Boroumand, David W. Eaton

Bibliographic record

VenueGeophysics · 2015
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaMicroseismic Industry Consortium
KeywordsFracture toughnessMicroseismFracture (geology)MechanicsHydraulic fracturingGeologyStress (linguistics)Materials scienceWork (physics)Strain energy release rateGeotechnical engineeringComposite materialThermodynamicsSeismologyPhysics

Abstract

fetched live from OpenAlex

ABSTRACT We have investigated the use of an energy-based numerical algorithm and its ability to simulate growth of a single planar hydraulic fracture by matching modeled dimensions to those inferred from a microseismic map. The energy-based microseismic fracture model accounts for the various physical processes expressed as a balance between the work expended (input/injected energy) and work done (output/lost energy) during growth of a vertical, 3D, laterally symmetric, planar, ellipsoidal, and tensile (mode I) fracture. These canonical fracture models provide a simple but useful proxy for more complex fracture networks that occur in reality. The tensile fracture is positioned in a three-layer geologic medium defined by elastic, material, and stress properties. Fracture half-length, half-width, half-height, and effective crack-opening pressure were computed using a time-stepping algorithm that solved energy balance equations using a Lagrangian formulation. Two parameters are adjusted to calibrate the fracture model to microseismic data; observed upward growth is fit by adjusting stress-barrier contrasts, and fracture length is fit by altering an empirical parameter, fracture toughness. In the case of a symmetric model with equivalent stress and material properties above and below the fracture, an increase in fracture toughness results in a corresponding increase in modeled net pressure and fracture width profile. In the case of a model with different stress states in the layers above and below the injection level, fracture height growth is enhanced in the layer with lower in situ stress. In both cases, net work is minimized in response to trade-offs between creation of new fracture surface area and fracture volume. Our primary objective was to incorporate microseismic observations into a geomechanical simulation of hydraulic fracture growth. Our approach is novel; it explains hydraulic-fracture behavior from an energy-balance perspective using the spatial-temporal evolution of microseismicity to constrain and validate the model.

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: none
Teacher disagreement score0.599
Threshold uncertainty score0.604

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 head0.020
GPT teacher head0.243
Teacher spread0.223 · 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".

Quick stats

Citations12
Published2015
Admission routes2
Has abstractyes

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