Unravelling Seismic Dim Zone for Reservoir Characterization with Advanced Geophysical Analysis to Unlock Petroleum Potentials
Bibliographic record
Abstract
Summary A comprehensive technical evaluation with geophysical analysis was conducted after the completion of a recent exploration and appraisal drilling campaign to assess the future petroleum potentials in B Field, located in West Luconia Basin, offshore Sarawak. Understanding of seismic dim zone with the full integration of seismic interpretation, seismic inversion, JiFi and AVO modelling with integration of well data, MDT pressure data, has resulted in an improved understanding of reservoir distribution, and reduced the degree of uncertainty in reservoir connectivity, thus unlocking new petroleum potentials and allowing a more robust development strategy. This paper focuses on major discoveries, reservoirs of the Upper Cycle V, Sand X and Sand Y, with findings from key wells, namely Well-B2 and Well-B2ST1, using AVO modelling and seismic inversion, with well logs and MDT pressure data integration to better understand the petroleum potential for subsequent development planning.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".