Scientific Ocean Drilling: Characterizing and Sampling Methane Hydrates
Bibliographic record
Abstract
Abstract Scientific ocean drilling programs such as the Deep Sea Drilling Project (DSDP, 1968-1983) and Ocean Drilling Program (ODP, 1985-2003) have pioneered the study of marine methane hydrates through the development and application of sampling tools, wireline measurements and other techniques used to characterize hydrate deposits along continental margins. These tools and techniques have evolved over many years of engineering development and field trials on multiple expeditions, which have been marked by strong collaborative efforts among academic and industry participants with support from government sponsors. This paper will describe the current status of some of these tools and measurement systems and discuss their potential use in global deepwater exploration of marine methane hydrate. Knowledge of the gas concentration in deep sediment is critical for understanding the dynamics of hydrate formation and the effect hydrates may have on the physical properties of the sediment. However, reliable data on gas concentration are difficult to obtain. The only way to determine true in situ concentrations of natural gas in the sub-seafloor is to retrieve cores in an autoclave chamber that maintains as closely as possible in situ conditions. Characterizing natural marine methane hydrate deposits helps to advance our understanding of these ubiquitous deposits and determine their role as a hazard to be avoided or a potential resource to be explored. Introduction To date, three dedicated scientific ocean drilling expeditions have been undertaken to advance our understanding of marine methane hydrates, namely, ODP Legs 164 (Blake Ridge and Carolina Rise; Ref. 1) and 204 (Hydrate Ridge, offshore Oregon; Ref. 2) and Integrated Ocean Drilling Program (IODP) Expedition 311 (Cascadia Margin, offshore Vancouver Island, Canada; Ref. 3). These dedicated expeditions, which served to sequentially advance the tools, methods and procedures used to study hydrate deposits, were highly successful because of strong collaborative efforts among engineers, scientists and technicians to develop, test and deploy new technologies in innovative ways. For example, closely spaced measurements of temperature made using thermistors inserted into sediment through plastic core liners during ODP Leg 164, evolved into continuous noninvasive measurements of thermal anomalies made using infrared thermal imaging cameras during ODP Leg 204. Similarly, the availability of a single tool for wireline pressure coring on ODP Leg 164 (Ref. 4), evolved into the use of multiple pressure coring tools on ODP Leg 204 due to the synergistic efforts of U.S., European and Japanese groups of engineers and scientists focused on similar research and development goals over several years (Ref. 5). These tools and techniques have coalesced into a set of integrated operational procedures that serve to provide a robust system for characterizing methane hydrates in their natural environment and in the laboratory onboard the JOIDES Resolution.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".