Design and Deployment of a Controlled Source EM Instrument on the NEPTUNE Observatory for Long-term Monitoring of Methane Hydrate Deposits
Bibliographic record
Abstract
Hydrocarbon deposits in the form of petroleum, natural gas, and natural gas hydrates occur offshore worldwide. Electromagnetic methods that measure the electrical resistivity of sediments can be used to map, assess, and monitor these resistive targets. In particular, quantitative assessment of hydrate content in marine deposits, which form within the upper few hundred meters of seafloor, is greatly facilitated by complementing conventional seismic methods with EM data.\nThe North-East Pacific Time-series Undersea Network Experiment (NEPTUNE) is an underwater marine observatory that provides power and network connection to a host of instruments installed on the seafloor on the Cascadia Margin offshore Vancouver Island. The observatoryâs aim is to provide a platform for very long-term studies in which access to data is available on a continuous basis. For this thesis project, a transient dipole-dipole time-domain EM system was constructed and deployed on the NEPTUNE network with the goal of long-term monitoring of a well-studied hydrate deposit in the area. The instrument includes a source transmitter of electrical current and individual receivers to measure small electric field variations. The instrument is powered by the NEPTUNE observatory and data can be collected remotely by connecting to the instrument through the web. Data collected so far from the instrument are consistent with a resistive structure. The best fitting model from 1D inversion is a 36 ± 3 m thick layer of 5.3 ± 0.3 â¦m resistivity, overlaying a less resistive 0.7 ± 0.1 â¦m halfspace. Average hydrate concentration, deduced with the aid of ODP-889 well-log derived Archieâs parameters, is approximately 72% of pore space in the resistive layer, consistent with the very high concentration of gas hydrates (~80%) recovered from seafloor cores. The weekly collection of data from the instrument shows that the resistive structure has changed little since monitoring began in October of 2010.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".