Exploring possible causative mechanisms for earthquakes triggered by hydraulic fracturing: examples from the Montney Basin, BC, Canada.
Bibliographic record
Abstract
The Dawson-Septimus area near the towns of Dawson Creek and Fort St. John, British Columbia, Canada has experienced a drastic increase in seismicity in the last ~ 6 years, from no earthquakes reported by Natural Resources Canada (NRCan) prior to 2013 to a total of ~ 200 cataloged events in 2013 – 2019. The increase follows the extensive horizontal drilling and multistage hydraulic fracturing activity that started to extract shale gas from the unconventional siltstone resource of the Montney Formation. In addition to hydraulic fracturing, ongoing wastewater disposal in the permeable sandstones and carbonates located stratigraphically above and below the Montney formation may also be contributing to elevated seismicity in the region. Earthquakes occur in close spatial and temporal proximity to hydraulic fracturing wells, at distances up to ~ 10 km. The expected diffusion time scales in the low-diffusivity siltstone rock units and the temporal and spatial scale of seismic activity beg questions about the possible processes controlling the location and timing of earthquakes. Here, we investigate the causative mechanisms for two of the largest events in the Montney Basin, British Columbia: the August 2015 M4.6 earthquake near Fort St. John, and the November 2018 M4.5 earthquake near Dawson Creek. Both events are thought to have occurred within the crystalline basement, ~2 km below the injected shale units (Montney formation). We use a finite-element 3D poroelastic model to calculate the coupled evolution of elastic stress and pore pressure due to injection at several hydraulic fracturing stages. Initially, we consider a simple layered model with differing hydraulic parameters based on lithology. Subsequently, also considering the seismicity distribution for each sequence, we introduce hypothetic hydraulic conduits connecting the injection intervals with the crystalline basement, where the respective mainshock occurred. We test a range of permeability values (10-15 m2– 10-12 m2) commonly implemented for fault zones. Our results show that, for both cases, the poroelastic stress perturbation may be not sufficient to trigger events in the basement. Instead, a scenario with a high-permeability (10-13 m2– 10-12 m2) conduits connecting the Montney formation to the fault responsible for the mainshock could better explain the relationship between the hydraulic stimulation and the timing of the two M > 4 earthquakes. For the 2018 M4.5 event, aftershock distribution can be mainly attributed to earthquake-earthquake interaction via static Coulomb stress transfer from the mainshock slip. In addition to the modeling of single well/event sequences, future work will include the long-term poroelastic effect due to multiple disposal wells located in the region.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".