Seismic velocity modelling, fixed point optimization, and evaluation of positioning uncertainty in the central Labrador Sea region: methods, a software tool, and an application
Bibliographic record
Abstract
Conversion between seismic two-way time (TWT) and sediment thickness is required to implement Article 76 of the United Nations Convention on the Law of the Sea. The deep water sedimentary succession of the central Labrador Sea is used to illustrate our approach to this problem. Multiple available sources of sediment seismic velocity information are assembled and analyzed with their cons and pros for this purpose, including scientific boreholes, seismic wide-angle reflection/refraction data, and proxy observations based on the normal moveout of seismic reflections. The latter exhibit a high degree of scatter and are subject to many caveats. Therefore we preprocessed the borehole and wide-angle reflection/refraction measurements from widely distributed locations across the region of interest to create a regional model of sediment velocity versus burial depth. The velocity model is constructed by numerical fitting of the observations with a slowness (inverse velocity) function that has strong theoretical and empirical linkages with the first-order porosity reduction behaviour documented for deep water successions around the world. The mathematical form of the model is attractive because it yields physically plausible velocities at depths beyond the range of observation, and because the model parameters are readily interpretable in terms of geologically significant physical properties. The fitting procedure of sediment velocity model accommodates measurement error in both velocity and depth by employing the reduced major axis (RMA) method. With RMA modeling, the bootstrapping method is used to estimate confidence bounds. For the example from the Labrador Sea, the bootstrapping results indicate an overall certainty of ±6.0% at the 95% level of confidence. An analytical function is derived that allows the model to be used for precise depth-to-time conversion. For time-to-depth conversion, the Newton-Raphson method is employed that provides a predefined accuracy, such as within ±1.0 cm with computing efficiency. Comparison of the velocity model with global results from deep sea drilling and also deep water marine shales of the Gulf of Mexico demonstrates a remarkable level of correspondence. In addition to providing support for the velocity model and its underlying methodology, the comparison provide strong evidence that porosity reduction due to compaction is the predominant factor controlling seismic velocity within the deep water marine successions. The purpose of invoking Article 76 is to define outermost fixed points along the margin. There are several criteria. One is the maximum of 2500 m bathymetry isoline plus 60 nm criterion; another is the sediment thickness formula which requires the sediment thickness to be greater than 1% of its distance to the nearest foot of continental slope (FOS). Implementation of sediment thickness criteria is significantly optimized in this work by integrating the interpreted seismic horizons (seafloor and top of basement), FOS points, and the conversion between TWT and sediment thickness using the constructed velocity model. Positioning uncertainty is unavoidable for current techniques in the identification of outmost fixed points. The sources of uncertainty include FOS identification, positioning of survey equipment, seismic data processing, horizon identification, and conversion between TWT and sediment thickness. These uncertainty sources are integrated into the net positioning uncertainty according to the methodology suggested by United Nations agencies. A software tool kit is provided for the construction of the velocity model, conversion between TWT and sediment thickness, optimization the identification of fixed point, and uncertainty evaluation. They are characterized flexibility as well as efficiency, such as one page web application and look up table enabling to be embedded them in a document, batch processing of all seismic profiles in one region, interactive graphic application. A user manual is also provided with giving step by step demonstration in this report.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".