Fluid environment for preservation of pore spaces in a deep dolomite reservoir
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Well TS 1 reveals many uncemented pores and vugs at depths of more than 8000 m in a deep Cambrian dolomite reservoir in the Tarim Basin, northwestern China. The fluid environment and mechanism required for the preservation of reservoir spaces have yet not been well constrained. Carbon, oxygen, and strontium isotope compositions and fluid inclusion data suggest two types of fluids, meteoric water and hydrothermal fluid, affecting the Lower Paleozoic carbonate reservoirs in the Tarim Basin. Based on simulation using a thermodynamic model for H 2 O‐ CO 2 ‐NaCl‐Ca CO 3 system, meteoric water has the ability to continuously dissolve carbonate minerals during downward migration from the surface to deep strata until it reaches a transition depth, below which it will begin to precipitate carbonate minerals to fill preexisting pore spaces. In contrast, hydrothermal fluid has the ability to dissolve carbonate in deep strata and precipitate carbonate in shallow strata during upward migration. Based on the dissolution–precipitation characteristics of the two types of fluids, the ideal fluid environment for the preservation of preexisting reservoir spaces occurs when carbonate reservoir is neither in the Ca CO 3 precipitation domain of meteoric water nor in the Ca CO 3 precipitation domain of hydrothermal fluid. Taking the Lower Paleozoic carbonate reservoirs in the north uplift area as an example, the spaces in the deep Cambrian dolomite reservoir near well TS 1 were seldom filled because thick Ordovician deposits blocked meteoric water from migrating downward into the Cambrian dolomite reservoir and because the Cambrian dolomite reservoir has been in the domain of hydrothermal dissolution since the Permian. The deep carbonate layers in basins elsewhere with a similar fluid environment may have high uncemented porosity and consequently have good hydrocarbon exploration potential.
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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 it