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Record W1993411808 · doi:10.2118/124690-ms

Numerical Simulation of Seismicity Induced by Hydraulic Fracturing in Naturally Fractured Reservoirs

2009· article· en· W1993411808 on OpenAlexaff
Xueping Zhao, R. P. Young

Bibliographic record

VenueAll Days · 2009
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGeologyHydraulic fracturingInduced seismicityGeotechnical engineeringSlippageGeomechanicsShear (geology)Fluid dynamicsFracture (geology)MechanicsPetrologySeismologyEngineeringStructural engineering

Abstract

fetched live from OpenAlex

Abstract The problem of the interaction between hydraulic and natural fractures is of great interest for energy resource industry because natural fractures can significantly influence the overall geometry and effectiveness of hydraulic fractures. Based on the tri-axial fracturing lab experiments presented in other publications and fluid stimulation in the field, a 2D discrete element model with fully dynamic and hydromechanical coupling is validated to simulate fluid injection into a reservoir containing a natural fracture by comparing modeling geometries of hydraulic fractures and induced seismicity with actual results in laboratory and field data. At the lab scale, the numerical model simulated a series of fracturing experiments on rock blocks with pre-fractures with different orientation, and the model captured three interaction types (crossing, dilating, and arresting) between induced fractures and pre-fractures and also illustrated three types of crossing depending on the differential stresses and orientations of pre-fractures. Furthermore, seismic mechanisms obtained from the model confirmed that hydraulic fractures were arrested by shear slippage of the pre-fracture. In the field scale, the calibrated model simulated the stimulation conducted in the tight gas reservoir at Dowdy Ranch field, USA. The model produced the scope and orientation of induced fractures similar to results obtained from the actual recorded microseismicity, and a similar seismic magnitude range. Moreover, the model showed deformation and cracking occurring ahead of the fluid pressure front and hydraulic fractures were arrested by the dilation of the fault. At the same time, the leakage of large fluid volume through the fault area was qualitatively predicted by the 2D model. These confirmed that the effective half-length is shorter than the created fracture half-length deduced from microseismic locations, which is the case during the multistage fracturing treatment in the Bossier formation. In addition, from the modeling results, it was concluded that the horizontal principal stresses with a ratio no less than 2 may be enough to cross a natural fracture with a single hydraulic fracture. Therefore, the validated model can help examine in detail the micromechanism behind the failure, and the relationship between the induced seismicity and the fluid front through direct observation of the model. Introduction Hydraulic fracturing and seismic monitoring are established techniques to improve the production of hydrocarbons from unconventional oil and gas reservoirs (Pearson 1981; Maxwell and Urbancic 2001; Sharma et al. 2004; Le Calvez et al. 2006), enhance geothermal energy in hot dry rock (Sasaki 1998; Norio et al. 2008), and facilitate slurry waste re-injection operations(Warpinski et al. 1999). Due to ubiquitous natural fractures, the problem of the interaction between hydraulic and natural fractures is of great interest for the energy resource industry because natural fractures can significantly influence the overall geometry and effectiveness of hydraulic fractures. A considerable amount of research has been carried out in the past few decades trying to understand the complexity and mechanics of hydraulic fractures in fractured reservoirs. Blanton (1986) conducted scaled laboratory experiments on naturally fractured Devonian shale and hydrostone under different angles of approach and states of stress. These experiments show that hydraulic fractures crossed pre-fractures only under high differential stress and high approaching angles, while at low differential stress and angles of approach the existing fracture opened, diverting the fracturing fluid and preventing the induced fracture from crossing, at least temporarily. Beugelsdijk et al. (2000) also performed laboratory experiments on Portland cement blocks to analyze complex hydraulic fracture geometry as a function of horizontal stress difference, stress regime, flow rate and discontinuity pattern. Many field work took in naturally fractured formations reveal that effects of natural fractures on fracture propagation are enhanced fluid leakoff, premature screenout, arrest of the fracture propagation, formation of multiple fractures, fracture offsets, high net pressures (Britt and Hager 1994; Vinod et al. 1997; Rodgerson 2000; Azeemuddin et al. 2002; Sharma et al. 2004).

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.248
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), 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

Citations36
Published2009
Admission routes1
Has abstractyes

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