Characteristics of fluid‐induced resonances observed during microseismic monitoring
Bibliographic record
Abstract
Abstract Three groups of resonances are observed during a two‐stage hydraulic experiment recorded by 12 three‐component geophones. The injected fluid is composed of a slurry of mostly water and proppant plus some supercritical nitrogen. Resonance characteristics are estimated using an autoregressive model. Three resonance models are investigated: fluid‐filled cracks, nonlaminar fluid flow, and repetitive events in terms of anticipated resonance frequencies, quality factors, and amplitudes. The observed resonances are very stable and positively correlated with either the slurry flow or the nitrogen injection rate, which is in contradiction with the repetitive events and fluid‐filled crack models, respectively. Resonances obtained by numerical simulations of an unstable jet agree with the main characteristics of most observed resonances. Our observations suggest that variations in resonance frequencies are mainly driven by variations in fluid flow, whereas quality factors are more sensitive to the fluid composition through variations in nitrogen injection rate. This study also suggests that resonance frequencies and quality factors can provide complementary information for real‐time monitoring of fluid injection into reservoirs, for hydraulic stimulations, geothermal operations, carbon capture, and storage or fluid movement during volcano eruptions.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".