Nearest-Neighbour Distance Analysis of Induced and Natural Seismicity within the Western Canada Sedimentary Basin
Bibliographic record
Abstract
Over the past decade, parts of western Canada have seen a rise in clustered seismic activity coinciding with the growing use of a hydrocarbon reservoir stimulation technique known as hydraulic fracturing. This recent upsurge has the potential to increase the local seismic hazard, particularly in affected areas characterized by a sparser tectonic environment. It is therefore critically important to assess and characterize the space, time and magnitude distributions of induced earthquakes from a statistical standpoint, in order to develop a better understanding of triggering processes and improve forecasting models. In this study, the nearest-neighbour distance method was used to analyze the distribution of space-time inter-event distances across the Western Canada Sedimentary Basin from a regional perspective. Additionally, the epidemic type aftershock sequence model and the Gutenberg-Richter relation were used to compare the structuring and magnitude scaling of several seismic clusters induced by different human operations. The results demonstrate that a transformation in the regional distribution of inter-earthquake distances occurred after 2009, where an emergent subpopulation of abnormally tightly clustered events became distinguishable from both natural and prior-induced seismicity. Several distinctions were also revealed between earthquake clusters occurring near different anthropogenic operations, including a higher proportion of tightly clustered events near hydraulic fracturing treatments which were largely swarm-like in nature.
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 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 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".