Forward Modeling Time-Lapse Seismic based on Reservoir Simulation Result on The CCS Project at Gundih Field, Indonesia
Bibliographic record
Abstract
This paper contains reservoir simulation study of carbon storage at Gundih field in Central Java Island, Indonesia. Two different cases of injection simulation were performed and analyzed in this paper. The cases represent the conditions when the smallest and largest volumes of CO2areinjected into the subsurface to see the changes of reservoir that happen after the injection processes. The simulation result shows that when a larger amount of CO2 is injected into the targeted reservoir, it will migrate to the peak of anticline structure located in the southeast of CO2 injection well. The displacement of CO2 in the simulation progress shows that it will not reach the fault location. The geological model for synthetic seismogram calculation is then built based on the simulation reservoir result. The furthest displacement of CO2 is calculated on each case and described as the saturated CO2 layers. Forward modeling is performed to create synthetic seismic gather which will be processed to construct seismic section. The difference between the initial seismic section before the injection process and seismic section including saturated CO2 layer after the injection process will be evaluated by the potential of injected CO2 monitoring using time-lapse seismic survey in the Gundih field.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".