Research on Non-Linearity Percolation Characteristics in Tight Sandstone Gas Reservoir
Bibliographic record
Abstract
The microcosmic pore throat structure is complex in tight sandstone reservoir so that the fluid lodging situation and flow condition in the pore space is difficult to determine, which has an influence on the effective displacement and efficient development directly. Research on gas/water percolation feature in the formation is the foundation of recognizing the tight gas reservoir. Taking a tight gas reservoir block in Ordos Basin for example, constant speed mercury-injection method is carried on leading to a research and analysis about microcosmic pore throat structure features and fluid physical property relative parameters in the formation. Using the steady-state method, an experiment has been done that takes 15 pieces of cores as examples which gets gas/water relative permeability curves. We conduct normalization processing and analyze relative permeability characteristics. Flow-pressure testing method is applied for studying gas/water relative permeability features. In view of the tight gas, the permeability is lower and the velocity of flow is more slowly under a certain pressure difference. By controlling differential pressure, flow velocity’s subtle changes are tested and the commensurable curve can be got. Research shows that the water liquidity in the small pore throat is poorer and the residual water saturation is higher; the two-phase seepage area spans a narrow range while the whole liquidity is poorer; there is threshold pressure gradient in the tight sandstone formation so that it presents non-linear seepage characteristics; the threshold pressure gradient in the target block is higher at about 0.151 MPa/m. Based on the above reasons, effective displacement in the tight gas reservoir gets more difficult. Key words: Tight gas; Gas/water relative permeability features; Non-linearity seepage; Threshold pressure gradient
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".