Using InSAR to detect active deformation associated with faults in Suban field, South Sumatra Basin, Indonesia
Bibliographic record
Abstract
Abstract Suban field in southern Sumatra, Indonesia, is a fractured carbonate/crystalline wet-gas reservoir in a tectonically active island-arc setting. Reservoir-scale right-oblique reverse faults and folds that have trapped the hydrocarbons have been related previously to deformation in the back-arc setting of Sumatra associated with oblique subduction of the Indo-Australian Plate at the Sunda trench. Increased well productivity in some parts of the field was inferred to correlate with completing wells in the damage zones of critically stressed faults. Satellite interferometry acquired in 2008 through 2011 involving specially stacked and filtered interferograms, following prior applications to heavy-oil fields and Arctic sea ice, reveals active deformation in Suban field. Several areas of localized subsidence potentially exceeding ∼5 mm/yr have been identified in the field. Horizontal movements of comparable magnitude were resolved above the major right-oblique, critically stressed fault zone in the southwestern part of the field, corroborating wellbore-based inferences from the reservoir. Block-tectonic models constrained by GPS measurements across the entire Sumatra contractional orogen predict comparable magnitudes and directions for horizontal motions observed locally at Suban. The combination of InSAR and GPS-based plate-tectonic models provides a robust tool for monitoring the deformation of oil and gas fields in tectonically active areas.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".