Imaging through shallow gas: Integrating broadband acquisition, processing and high-end model building for improved imaging of deeper targets
Why this work is in the frame
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Bibliographic record
Abstract
We present a case study offshore Malaysia, shallow gas features in the overburden distort the seismic imaging at the target level. While a multifaceted approach involving a combination of seismic acquisition and processing strategies were used to improve the bandwidth of the seismic data, particularly for the low-frequency content of the seismic image, several distortions still existed at the target level. The prominent structural sag evident at the reservoir level is a typical indication that the overlying shallow gas velocity model needed to be resolved and incorporated into a depth migration algorithm.To resolve the transversally and laterally variant velocity features in the shallow gas areas, a solution that consisted of full waveform inversion (FWI) and high-resolution reflection traveltime tomography was utilized to produce an accurate compressional velocity model. To further resolve the amplitude and phase distortions at the reservoir level due to shallow gas effects, Q tomography was incorporated into the model building phase to derive a space-variant 1/Qmodel and Q compensation was integrated within depth migration.The integrated approach of broadband receiver acquisition, data processing strategies and high-end Earth model building has cumulatively improved the imaging of the reservoir below the shallow gas anomalies.
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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 | 0.001 | 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 | 0.001 |
| 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 it