A simplified transient technique for porosity and permeability determination in tight formations: Numerical simulation and experimental validation
Bibliographic record
Abstract
Abstract A simplified pulse decay method (PDM) with only a single downstream reservoir is proposed to replicate the in situ conditions for reservoir fluid flow, where the pore pressure at any location declines as production continues. The proposed PDM also allows determining the effective porosity and permeability for the core sample under replicated in situ conditions. A mathematical model is firstly established to closely represent the experimental design and verify the feasibility of the method. The analytical solutions of the model are derived to calculate the effective sample porosity and permeability. A series of experiments are then conducted under triaxial stress condition, and a detailed comparison is also made between the PDMs with a single upstream reservoir and a single downstream reservoir. The experimental results showed that accurate measurements on effective sample porosity and permeability can be achieved by the single downstream reservoir PDM due to its capability of better replicating the in situ fluid flow behavior, which extends the application of the transient technique. It is also found that the pore pressure along the sample changes linearly, and its gradient varies with time, indicating the applicability of the single‐reservoir PDMs in permeability determination. This method also lays a foundation for studying flow behavior when a second fluid phase evolves during pressure decline, which occurs in many 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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".