Observing maturing source rocks on seismic reflection data
Bibliographic record
Abstract
ABSTRACT Hydrocarbon generation in a source rock is a complex, irreversible phase change that occurs when a source rock is heated during burial to change the phase to a fluid. The fluid density is less than the kerogen density; therefore, in a closed or partially closed system, the volume of the pore space occupied by fluids increases. Burial also increases the effective stress, which leads to compaction and a significant reduction in porosity. The challenge of identifying source rocks on seismic data then becomes differentiating the smaller porosity increase due to hydrocarbon formation from the larger porosity decrease associated with burial. We have used a calibrated rock-physics model to indicate that Vshale and porosity data can be used to predict the P- and S-wave velocities and the density in wells over large sedimentary sections, including a source rock of variable maturity. These well data and models indicate that the difference between an immature and mature source rock is an increase in porosity (lower density) relative to compacting, nonsource rock sediments. We use these results to identify a potential source interval in the Orphan Basin in Eastern Canada on 2D regional seismic data. We find that the full stack amplitude response of a maturing source rock is significant during the main phase of generation (0.2 < transformation ratio < 0.8) relative to the surrounding sediments. Regional scale consistency of the amplitude response with the kerogen maturity model from an integrated basin simulator reduces exploration risk because of the independence of the thermal model from the seismic amplitude response. Finally, combining the seismic response with the source rock maturity model provides insight into the likely kerogen kinetics. Most of applications require regional data sets to capture the maturity window; however, applications are also possible around allochthonous salt where geometries can lead to local changes in the heat flow.
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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 | 0.001 |
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".