Metre to Nanometre Characterization of Heterogeneous Porous Media: North-East Pembina Field Tight-Oil Reservoir Halo, Cardium Formation (Upper Cretaceous), Alberta, Canada
Bibliographic record
Abstract
This study uses a combination of sedimentological analysis, X-radiation techniques, electron microscopy, and routine core analysis methods to investigate multi-scale variations of reservoir properties from a tight-oil reservoir. Higher reservoir quality, defined by porosity and permeability values, is mostly associated with lower values of X-ray attenuation index, and corresponds well with lighter-colored (relatively clean sandstone) portions of the highly bioturbated lithofacies investigated. Physicochemical properties of the samples are highly influenced by its mineralogy, which is dominated by quartz and illitic clays (85-90% wt.), and can be captured using mainly the mass concentration of Si, Al, K, Fe, and Rb. Equally important, connectivity to main flow-paths at the reservoir scale can also be extracted from these interpretations. Evaluation of the three-dimensional distribution of reservoir properties at the core-scale indicate contrasting variations of these properties within elementary lithological components (ELCs). These ELCs are present at the cm- to sub-cm scale and are moderated in part by the effects of synsedimentary bioturbation. In order of decreasing reservoir quality, ELCs identified were defined as: a) SS1 – relatively clean sandstone, b) SS2 – argillaceous sandstone, c) SH – mudstone, and d) siderite- and pyrite nodules/concretions and dense mineral burrow fillings. Despite the high degree of bioturbation observed, sand-filled structures of biogenic origin were found to be poorly connected as confirmed with fluid flow numerical simulations. Also, a geometric averaging algorithm was observed to offer a better representation for the upscaling of simulated horizontal permeability datasets, whereas both geometric and harmonic averaging work similarly well for the vertical measurements on multi-scale virtual subsamples. Anisotropy of horizontal permeability was largely influenced by the presence of relic bedding structures. Pore size distribution obtained for ELC SS2 samples spans from ≈120 μm to ≈20 Å (diameter), with accessibility ratio higher than 90%. Comparison of incremental pore volume curves from mercury porosimetry and small-angle and ultra-small angle neutron scattering (SANS/USANS) highlights the potential influence of clay-hosted slit pores in controlling the fluid-flow process in these tight rocks. Moreover, discrepancies observed among the different analytical techniques highlights the influence of subtle compositional variations in the analysis of porosity and pore accessibility from SANS/USANS datasets.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".