The Microvibe, a broad band, light-weight and cost effective seismic source for near surface imaging
Bibliographic record
Abstract
For shallow environmental and engineering surveys in generally unconsolidated sediment to depths of a few meters to several hundred metres high resolution seismic reflection surveys require heavy and expensive vibration sources such as a Minivib(TM). It weights 9 tons and costs approximately $400K. Best practice for optimized characterization of shallow surficial properties multi-component acquisition is required and this necessitates multiple passes and recording with the Minivibe - landstreamer system with the source being set in various horizontal and vertical directions. To provide a cheaper and lighter seismic source we have developed the Microvibe (180 kg and ~$30k) uses a suite of lighter electromagnetic transducers that can provide multicomponent seismic signal in a single pass. The Microvibe consists of forty tactile transducers, twenty per direction, on a solid concrete block mounted on a steel skid plate. This vibrator can provide various types of sweeps from 20 Hz up to 800 Hz with a power up to 2000 watts, for each direction, providing ~25% of the power provided by an IVI Minvib. To compensate for the reduced power level, we increase the time length of the sweep. The Microvibe provides higher frequency ranges than any known land seismic source available on the market. The Microvibe is coupled with an in-house built landstreamer array designed for use along paved or gravel roads. The landstreamer is built with 3 kg metal sleds connected using straps or low stretch ropes. The receiver spacing can vary from 0.75 m to 3 m. Receiver set-up is customized depending on the near-surface velocities and the targeted depths of observation. Each sled is equipped with a 3-component (3-C) geophone unit constructed in-house with 30 Hz omni-directional geophone elements oriented in three orthogonal directions: one vertical and two horizontal, in-line (parallel to the survey direction) and cross-line (perpendicular to the acquisition direction). The Microvibe - landstreamer combination allows data acquisition with shaking in vertical and horizontal directions in one pass to capture P-wave and S-wave seismic reflection sections. In order to demonstrate the value of this new geophysical tool, examples will be presented from a ground water example in the Vars - Winchester esker of southeastern Ontario. The system is also very efficient for evaluating the soft soil response for earthquakes and for locating neo-tectonic faults or buried tunnels.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.006 |
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".