Harnessing 3D seismic data for mapping natural CO2 distribution: Paving the way for future CCS/CCUS implementation in the Lower Talang Akar Formation, Jabung Block, South Sumatra Basin
Bibliographic record
Abstract
Abstract Hydrocarbon reservoirs saturated with CO2 are naturally widespread in the Lower Talang Akar Formation (LTAF) and deposited in the Jabung Block, South Sumatra Basin, Indonesia. The different CO2 saturation contents stored in the reservoirs pose a challenge to planning future carbon capture and storage (CCS) and carbon capture, utilization, and storage (CCUS) in the area. This study integrates poststack 3D seismic data and existing wells in the western part of the Jabung Block. It utilizes seismic attribute methods such as sum of negative amplitude, relative impedance, variance, and ant tracking to predict the origin, saturation, and distribution of CO2-saturated hydrocarbon accumulations in the sandstone reservoirs of the LTAF. The results show that CO2 originated from the Betara Deep source rock in the study area's eastern side and migrated to the reservoirs through major northwest–southeast-trending fault zones. The saturation of CO2 in the reservoirs is mainly controlled by the distance from the source and the reservoir depths, faulting, and fracturing intensity. The fields closer to the Betara source rock tend to be filled with higher contents of CO2 saturation. The results provide valuable guidance in CO2 identification and mapping for future CCS and CCUS implementation in the study area.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".