A New Method To Simultaneously Measure In-Situ Permeability and Porosity Under Reservoir Conditions: Implications for Characterization of Unconventional Gas Reservoirs
Bibliographic record
Abstract
Abstract Accurate estimation of gas-in-place is crucial for successful evaluation and exploitation of unconventional gas reservoirs, such as shale gas, coalbed methane, and tight gas. However, gas effective porosity, one of the most important parameter in estimating gas in-place, is commonly measured on crushed samples of cores or cuttings at ambient pressure although many studies have shown that the porosity and permeability of reservoirs rocks decrease with increasing effective stress, and thus the pore volume/porosity measured on crushed samples at ambient (zero stress) conditions will be larger than porosity measured under in-situ reservoir stress conditions. Normally the stress-dependence of porosity is simply accounted for by a correction factor based on the linear poro-elastic deformation, which is likely an over-simplification. In present study, we developed a new protocol for simultaneously measuring stress-dependent In-Situ Permeability and Porosity (ISPP) that provides a method for routine characterization of effective porosity and permeability under simulated reservoir conditions. Our new method can significantly reduce the uncertainties of porosity introduced by testing crushed samples under ambient conditions, testing time, and the need for good quality core samples that are usually unavailable. Preliminary test results indicate that the stress dependence of porosity (or pore compressibility) of fine grained reservoir rocks follows a unique trend of each tested sample, which cannot be simply adjusted from ambient porosity by a universal factor. Physical and numerical sample tests suggest that our ISPP method can obtain permeability similar to the normal pressure Pulse-Decay Permeability (PDP) technique if samples are homogeneous or transversely layered along their axes. Otherwise, our ISPP method likely tests the geometrical average permeability of longitudinally layered samples instead of the weighted arithmetical average permeability tested by the PDP method. Overall, our approach of simultaneously measuring effective porosity and permeability under reservoir conditions offers intrinsically consistent porosity-permeability data to characterize unconventional reservoirs. Our study also reveals that utilization of different methods to test samples in different orientations and different sizes is necessary to rigorously characterize the hierarchical permeability and porosity of heterogeneous and microporous unconventional reservoir rocks.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".