The assessment and evolution of offshore gas hydrate deposits using seafloor controlled source electromagnetic methodology
Bibliographic record
Abstract
Natural gas hydrates are ice-like solids that occur worldwide in seafloor sediments typically along active continental margins. They consist of gas molecules, mainly methane, contained in a cage-like, clathrate structure of water molecules. They form under low temperature and high pressure conditions, typically offshore in the uppermost few hundred metres of sediment in water depth exceeding about 500 m. The global abundance of methane frozen in hydrate exceeds the amount of all other known fossil hydrocarbon resources. Gas hydrates are a source of a large volume of methane gas and are recognized as an important possible future energy resource. Marine controlled source electromagnetic (CSEM) methods, sensitive to variations in resistivity, have become an important and valuable tool in the detection of offshore hydrate Hydrate is a resistive target. It increases the formation resistivity of a sediment layer if it forms in sufficient quantity to block previously interconnected pore spaces. Controlled source electromagnetic (CSEM) methods depend on a simple concept of physics. If a time varying EM field is generated at or near the seafloor, then eddy currents are induced in the sea water and subjacent crust in accordance with Faraday's law. The outward progress of the currents with time depends on range and electrical conductivity of the surroundings. In particular, the apparent speed in the sea water will be slower than that in the less conductive crustal zones. Measurements at a remote location of the electric and magnetic fields associated with the eddy currents may be inverted for the crustal resistivity structure including local anomalous concentrations of hydrate. Our CSEM system has been used successfully to map hydrate on the Cascadia Margin, to the west of Vancouver Island, British Columbia. The area, a convergent margin, is the focus of intensive studies on gas hydrates which have been identified on seismic sections, by direct sampling and from the analyses of cores and logs collected by the Ocean Drilling Programs. It has also been used in New Zealand in a similar geologic setting. The next stage in the research is the monitoring of one of more deposits as a function of time in this case several years. The objective is the understanding of how hydrate is formed and how it evolves. It requires the installation of equipment on the seafloor which is locally powered and which can communicate with an onshore base. Neptune Canada provides the infrastructure for the experiment. It is a Canadian subsea observatory network consisting of a cable linking several nodes to a terminal on Vancouver Island. The cable carries power and high speed ethernet interconnectivity. Instruments, including the CSEM apparatus have been connected to the nodes and data may be collected from them in real time. The CSEM array spans a known gas hydrate deposit. The engineering of both the network and the CSEM system is described together with a numerical model study.
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 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".