Passive seismic investigations of subaquatic permafrost
Bibliographic record
Abstract
Large quantities of organic carbon are known to be sequestered within subaquatic permafrost as gas hydrates. Therefore, knowledge of the extent and thaw rate is of critical importance to our understanding of global climate change. Investigations of sub-aquatic permafrost have focussed on its physical characteristics via drilling or probing, and through the limited application of geophysical methods. Active seismic methods have been most widely employed, especially for petroleum exploration, but recently passive methods have been used to investigate the seabed using ambient noise. The Horizontal-to-Vertical Spectral Ratio (HVSR) method has previously been shown to accurately determine permafrost thaw depth below the sea floor in marine and lacustrine environments, based on the collection of seismic data over a period of weeks. In this study, we test the use of short-term seabed HVSR seismic surveys and explore possibilities for optimizing the method in a wide variety of subaquatic environments. The method was successfully used in a thermokarst lake, a lagoon and river channels of the Lena Delta (Russia), as well as in marine shelf environments in the Laptev Sea (Russia) and Tuktoyaktuk Island (NW Canada). Study areas where validation data was available were preferred and selected when possible. A passive seismic measuring device, consisting of a watertight metal cannister containing three-component broad-band seismometers, was lowered down to the sea floor from a small boat and left to collect data for 3-4 minutes. The data was recorded at a sample rate of 100Hz. Post-processing and analysis were done with MATLAB. The three seismic signals were individually detrended, the offset was removed and the power spectral density was calculated. The smoothing function proposed by Konno and Ohmachi (1998) was applied to each signal with a smoothing coefficient of 40. Lastly the H/V (Horizontal / Vertical) amplitude was calculated. The H/V amplitude was plotted against signal frequencies from 0 to 50 Hz. The peak resonance frequency is believed to indicate the ice-bonded permafrost table (IBPT) thereby enabling us to determine thaw depth from the H/V plots, assuming a simple 2-layer model: thawed layer over frozen ground, characterized by low and high wave speeds, respectively. Results generally display a good correlation, on average within 0.6 meters, between the thaw depth determined from HVSR and from physical validation, although HVSR often generates a thaw depth deeper than indicated by validation data. This may be a result of complex permafrost systems where several “zones” of frozen and unfrozen ground, of varying thickness, is present below the water bodies. We conclude that the method has the potential to be an effective (fast) non-invasive tool for investigating the extent and, if repeated, the thaw rate of subaquatic permafrost. Further field testing is planned in order to continue the development and optimization of the method.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".