Fluid mapping in deeply buried <scp>O</scp>rdovician paleokarst reservoirs in the <scp>T</scp>arim <scp>B</scp>asin, western <scp>C</scp>hina
Bibliographic record
Abstract
Abstract The storage spaces within deeply buried Ordovician paleokarst reservoirs in the Tarim Basin are mostly secondary and characterized by strong heterogeneity and some degree of anisotropy. The types of fluids that fill the spaces within these reservoirs are of great importance for hydrocarbon exploration and exploitation. However, fluid identification from seismic data is often controversial in this area because the seismic velocity for this particular reservoir could be significantly influenced by many factors, including pore shapes, porosity, fluid types, and mineral contents. In this study, we employ the differential effective medium‐Gassmann rock physics model to interpret and discuss the characteristics of conventional karstic carbonate reservoirs in the Tarim Basin that are filled with different fluids (oil, gas, and water) using logging data and thus objectively build corresponding fluid identification criteria. These criteria are subsequently evaluated by amplitude versus offset (AVO) forward analysis based on typical logging data and further applied to ascertain the reservoir fluid types in two different areas in the Tarim Basin based on prestack inversion results. For conventional carbonate reservoirs, gas can be distinguished from heavy oil and water, but heavy oil and water are broadly similar on seismic data. For condensate carbonate reservoirs, water can be differentiated from light oil (i.e., condensates) and gas, but light oil and gas demonstrate substantial similarities in terms of their seismic responses. The predicted fluid results are in good agreement with the results of drilling and oil testing. In particular, modeling the seismically resolvable reservoirs in the carbonate strata in the Tarim Basin, which have needle‐ and sphere‐shaped storage spaces (pore aspect ratio > 0.3) and clay content that is lower than 5%, indicates that fluid properties could be properly evaluated if the porosity is larger than 5% for conventional carbonate reservoirs and >7% for condensate carbonate reservoirs.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".