Insights into downhole array spectra of hydraulic-fracturing induced seismicity in the Horn River Basin, British Columbia
Bibliographic record
Abstract
Hydraulic fracturing underpins tight shale gas exploration but can induce seismicity. During stimulations, operators carefully monitor the spatio-temporal distribution and source parameters of seismic events to be able to respond to any changes and potentially reduce the chances of fault reactivation. Downhole arrays of geophones offer unique access to (sub) microseismic source parameters and can provide new insights into the processes that induce seismicity. For example, variations in stress drop might indicate changes in the seismic response to injection (e.g. pore pressure variations). However, borehole arrays of geophones and the high frequencies of small events also present new challenges for source characterization. Stress drop depends on the corner frequency, a parameter with great uncertainty that is sensitive to attenuation, especially for (sub-) microseismicity. Here, we explore the behavior of microseismic spectra measured along borehole arrays and the effect of attenuation on estimates of corner frequency. We examine a dataset of over 90,000 microseismic events recorded during hydraulic fracturing in the Horn River Basin, British Columbia. We only see clear phase arrivals for events Mw > -1 and restrict our initial analysis to a subsample of Mw> 0 events that vary in space and time. Our first observation is that some stations in the borehole array show an unexpected increase in the displacement energy from the low frequency to the corner frequency in the P and SH phases as well as high-frequency energy spikes inconsistent with a smooth Brune source model. A shorter time window that only captures the direct arrival results in a flatter low frequency plateau and reduces the amplitude of the pulses but compromises the resolution. The spikes may be caused by high frequency coda energy. We also find that corner frequency estimates decrease with decreasing station depth along the array in both the P and SH phases, a likely result of high frequency attenuation along the downhole array. The findings suggest Brune corner frequencies of moment magnitudes < 0.5 may not be resolvable even with downhole arrays at close proximity. Our results will eventually contribute to a better characterization of microseismic source parameters measured in borehole arrays.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".