Labrador Deepwater Exploration Insights into its Prospectivity From Broadband Seismic AVO Analysis and Seabed Coring
Bibliographic record
Abstract
Abstract The Labrador Sea, extending from the Davis Strait in the north, through the Saglek Basin and down to the Hopedale Basin in the south, is one of the largest under-explored areas along the eastern Canadian Margin. Exploration of this region has focused on the continental shelf with 30 wells drilled during the 1970's and 1980's. Most of the wells targeted shelfal structural traps. No exploration has occurred in the slope and deepwater areas. From 2011 to 2015, long offset, broadband 2D seismic data (42,400 km) has been acquired by TGS-PGS in the slope and deepwater regions. The broadband image quality has led to the identification of significant new plays and leads in a region that was never before considered prospective. Several of these leads have the potential for large accumulations of oil and gas. The possibility for oil plays in the area is supported by the presence of natural oil seeps along the slope that were identified by satellite surveys in 2010. The long offset (8 km cable) seismic data has identified AVO anomalies on the far stacks. A new regional rock physics study (2014-15) has permitted the careful analysis of these AVO leads and this is helping to reduce exploration risk factors. The analysis shows the importance of the long offsets to identify and characterize these Class II AVO anomalies. In 2015, a seabed coring survey was conducted to target areas near the oil seeps and over large potential traps. Early results from this work are positive and analysis will continue through the spring of 2016. Heatflow measurements taken during the coring survey are providing inputs for a basin modelling study. In addition, several of the shelfal wells were resampled and fluid inclusion analysis was performed. Early results are showing the presence of liquid hydrocarbon inclusions. All of this work has led to the identification and analysis of large potential traps that could hold major oil accumulations. This paper will provide insights from the new seismic data and the recent studies and analyses to demonstrate this prospectivity.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".