Geometrical Seismic Attribute for Fault Identifiction on Canada Exploration Field
Bibliographic record
Abstract
It has been performed data interpretation of 3D seismic data and drilling field exploration wellsBasin Nova ScotiaKanada to know structure fault on the field Missisauga Formation. Seismic dataused is 601 inline, crossline 482, and the data used drilling wells are two wells which there is a loggamma ray, sonic logs and log RHOB. Interpretation is done the analysis of the map in thestructure of time and analysis of seismic attribute maps based on the geometrical attribute serves todetermine their structure or structural faults of the data volume 3D. Based on the time structuremap well known that first well is in the region heights and second wells is in low region. Based oninterpretation of the map attributes known three faults are two major fault and one minor fault.Two faults are in the East Sea drilling wells and a small fracture that was on its western side. Thethree fults are directed from Northwest to the Southeast. Fault is expected to serve as ahydrocarbon trap in the area that will be accumulated in drilling wells.Keywords: geometrical attribute, Seismic data, drilling wells, time structure map.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".