Hydrocarbon detection for Ordovician carbonate reservoir using amplitude variation with offset and spectral decomposition
Bibliographic record
Abstract
Abstract We have developed an example of hydrocarbon detection for an Ordovician cavern carbonate reservoir in western China with a burial depth exceeding 6600 m using amplitude variation with offset (AVO) and spectral decomposition. We selected six production wells, three prolific oil wells, and three brine wells to test the hydrocarbon detection method. The three oil wells have been producing for more than three years, and the three water wells only produce brine. We performed spectral decomposition to the angle gathers and analyzed amplitude variation patterns with incidence angles for different spectral components. Specifically, we compared the time corresponding to the peak spectral amplitude for different spectral components for the oil- and brine-saturated carbonate reservoirs. The main findings are as follows: (1) Oil-saturated cavern carbonate reservoirs show decreasing peak time with increasing frequency; i.e., the high-frequency components travel faster than do the low-frequency components. The maximum time difference between the 10 and 50 Hz spectral components could reach 35 ms. In contrast, the brine-saturated carbonate reservoirs do not exhibit conspicuous variation in the peak time, (2) AVO attributes extracted from the low-frequency spectral gathers are more robust than those extracted from the original seismic gathers, (3) oil-saturated cavern carbonate reservoirs cause strong energies in the low-frequency spectral components and severe attenuation to the high-frequency spectral components at large incidence angles. In contrast, the brine-saturated carbonate reservoirs do not produce such phenomenon. Rock physics analysis for carbonate reservoirs under different saturation conditions was conducted. The synthetic gathers were generated for carbonate reservoirs under oil- and brine-saturated conditions. The spectrally decomposed synthetic gathers are in agreement with the real gathers. The results indicate that AVO analysis of spectrally decomposed prestack gathers could be used as an effective hydrocarbon detection method for carbonate reservoirs.
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 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 | 0.002 | 0.001 |
| 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) | 0.001 | 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".