Numerical modeling of seismicity induced by fluid injection in naturally fractured reservoirs
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Bibliographic record
Abstract
ABSTRACT 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. Microseismic monitoring provides a unique tool to monitor the evolution of fracturing around the treated rock reservoir, and seismic source mechanisms can yield information about the nature of deformation. We performed a numerical modeling study using a 2D distinct-element particle flow code (PFC2D) to simulate realistic conditions and increase understanding of fracturing mechanisms in naturally fractured reservoirs, through comparisons with results of the geometry of hydraulic fractures and seismic source information (locations, magnitudes, and mechanisms) from both laboratory experiments and field observations. A suite of numerical models with fully dynamic and hydromechanical coupling was used to examine the interaction between natural and induced fractures, the effect of orientation of a preexisting fracture, the influence of differential stress, and the relationship between the fluid front, fracture tip, and induced seismicity. The numerical results qualitatively agree with the laboratory and field observations, and suggest possible mechanics for new fracture development and their interaction with a natural fracture (e.g., a tectonic fault). Therefore, the tested model could help in investigating the potential extent of induced fracturing in naturally fractured reservoirs, and in interpreting microseismic monitoring results to assess the effectiveness of a hydraulic fracturing project.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it