Clay Mineral Alteration in Oil and Gas Fields: Integrated Analyses of Surface Expression, Soil Spectra, and X-Ray Diffraction Data
Bibliographic record
Abstract
Subsurface hydrocarbon occurrences can be detected by clay mineral (CM) alteration at the surface as a consequence of hydrocarbon migration. This study analyzed CM alteration in an oil and gas (O&G) field in the West Tugu field, located in the northwest Java Basin of Indonesia. Landsat 8 OLI data acquired on 25 September 2015 and soil spectral reflectance (SSR) data recorded using analytical spectral devices (ASD) in March 2017 were processed using clay indices to analyze CM alteration. Soil samples from a field survey of the same area were also analyzed using X-ray diffraction (XRD) to identify their CM compositions. CM distribution was empirically modeled by integrating the SSR bands re-sampled to Landsat 8 OLI (SSRL) bands and the CM composition using the best subset regression method and regression analyses. The resulting model was applied to Landsat 8 OLI images to map the surface CM alteration. The results show that CM alteration observed in the O&G field is an indicator of hydrocarbon microseepage at the surface. These results can be used as a technique to identify prospective regions that contain hydrocarbons and differentiate from those that are barren, and could be useful for increasing the rate of drilling success.
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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 | 0.000 | 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) | 0.000 | 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".