Nanopore Structure Analysis and Permeability Predictions for a Tight Gas/Shale Reservoir Using Low-Pressure Adsorption and Mercury Intrusion Techniques
Bibliographic record
Abstract
Abstract The pore structure of unconventional gas reservoirs, despite having a significant impact on hydrocarbon storage and transport, has historically been difficult to characterize due to a wide pore size distribution, with a significant pore volume in the nanopore range. A variety of methods are typically required to characterize the full pore spectrum, with each individual technique limited to a certain pore size range. In this work, we investigate the use of non-destructive, low-pressure adsorption methods, in particular low pressure N2 adsorption analysis, to infer pore shape, and to determine pore size distributions of a tight gas/shale reservoir in Western Canada. Unlike previous studies, core plug samples, not crushed samples, are used for isotherm analysis, allowing an undisturbed pore structure to be analyzed. Further, the core plugs used for isotherm analysis are subsamples (end pieces) of cores for which MICP and permeability measurements were previously made, allowing a more direct comparison with these techniques. Pore size distributions determined from two isotherm interpretation methods (BJH Theory and Density Functional Theory), are in reasonable agreement with MICP, for that portion of the pore size distribution sampled by both. The pore geometry is interpreted to be slit-shaped, as inferred from isotherm hysteresis loop shape, the agreement between adsorption- and MICP-derived dominant pore sizes, SEM imaging and the character of measured permeability stress-dependence. Although correlations between inorganic composition and total organic carbon (TOC) and dominant pore throat size and permeability are weak, the sample with the lowest illite clay and TOC content has the largest dominant pore throat size and highest permeability, as estimated from MICP. The presence of stress-relief-induced microfractures, however, appears to affect lab-derived (pressure-decay and pulse-decay) estimates of permeability, even after application of confining pressure. Based on the premise of slit-shaped pore geometry, fractured rock models (matchstick and cube) were used to predict absolute permeability, using dominant pore throat size from MICP/adsorption analysis and porosity measured under confining pressure. The predictions are reasonable, although permeability is mostly over-predicted for samples that are unaffected by stress-release fractures. The conceptual model used to justify the application of these models is slot pores at grain boundaries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".