Role of Fluid Diffusivity in the Spatiotemporal Migration of Induced Earthquakes during Hydraulic Fracturing in Unconventional Reservoirs
Bibliographic record
Abstract
Hydraulic-fracturing-induced earthquakes exhibit an intricate pattern in spatiotemporal migration with respect to stage completions of fracturing horizontal wells. The underlying physical mechanisms remain uncertain. This paper investigates two field cases to quantify the effects of fluid diffusivity on the spatiotemporal migration of induced earthquakes during fracturing stimulation in shale reservoirs. First, the double-couple component approach is employed to determine the focal mechanisms of mainshock events. The relation plot of earthquake magnitude–fault size as well as the spatial distribution of induced events are used together to characterize the fault distribution. Then, the tight rock analysis and triaxial compression experiments are conducted to determine the distinctive petrophysical and geomechanical properties of stimulated formations in both cases. The hydraulic diffusivity of fracturing fluids is then estimated from the spatiotemporal evolution of the seismicity fronts with respect to the fracturing sites. Finally, a poroelastic modeling and numerical simulation are performed to evaluate the time-dependent pore pressure diffusion and poroelastic stress perturbation during fracturing stimulations. Results suggest that the subvertical N–S-trending faults and NE45°-trending hydraulic fractures generate the fracture and fault networks in the M w 3.6 and M w 3.4 cases, providing geological evidence to account for the spatial distribution of induced earthquakes within the networks. The shear stress gradient G is calculated to be 0.21 MPa/km for the M w 3.6 case and −0.08 MPa/km for the M w 3.4 case, indicating downward and slightly upward shear growth. The observed seismicity migration defines the hydraulic diffusivity of 0.15 m 2 /s for the M w 3.6 event and 2 m 2 /s for the M w 3.4 event. The poroelastic simulation characterizes the time-dependent pore pressure and poroelastic stress changes, matching well with the spatiotemporal migration of induced earthquakes during and after fracturing stimulations. The increasing pore pressure is the first-order factor in fault reactivation. Different time lags between stage completions and induced earthquakes indicate distinctive fluid diffusivity within the hydraulic fracture and seismogenic fault networks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".