High Heat Flow and Geothermal Opportunities in the Sunda Basin, Indonesia: A Case for Sustainable Energy Development
Bibliographic record
Abstract
ABSTRACT Indonesia's geothermal development has traditionally focused on Quaternary volcanic arcs, as exemplified by power plants in Sibayak (North Sumatra), Salak (West Java), Kamojang (West Java), and Sarulla (North Sumatra). However, increasing socio‐environmental challenges in densely populated regions highlight the need to explore alternative geothermal provinces. This study evaluates the geothermal potential of the offshore Sunda Basin using data from 21 oil wells. The results reveal heat flow values of 60–140 mW/m 2 , geothermal gradients of 30°–70°C/km, and thermal conductivity ranging from 1.66 to 2.14 W/m °C—indicating favourable thermal conditions within sedimentary units. These characteristics are structurally supported by a thin crust (~30 km), normal faulting, and back‐arc tectonic features formed during Tertiary‐age slab rollback and pull‐apart processes. Comparative analysis with global basins—including Gonghe, Upper Rhine Graben, Buyuk Menderes, Thrace, and Western Canada Sedimentary Basin (WCSB)—demonstrates that the Sunda Basin exhibits competitive geothermal characteristics, particularly in terms of accessible reservoir depth and thermal stability. The basin's offshore setting reduces typical onshore development constraints, offering a strategic opportunity for low‐impact geothermal exploitation through re‐utilisation of inactive oil wells and modular technologies. This study reinforces the Sunda Basin's role in diversifying Indonesia's geothermal portfolio and supporting national targets for net‐zero emissions by 2060.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".