High-Resolution Permeability Modeling in Highly Heterogeneous Tight-Oil Reservoirs
Bibliographic record
Abstract
Abstract A high-resolution simulation model of a highly heterogeneous tight oil rock sample is used to investigate the effects of physical and biogenic sedimentary structures on scaling and anisotropy of absolute permeability at the core scale. Results are compared to routine core analysis (RCA) available for similar samples. The volumetric distribution, quality and connectivity of different contrasting types of elementary flow units [microlithofacies (μLFs)] are individually evaluated for a highly heterogeneous Pembina Cardium lithofacies. Reservoir properties were measured/calculated at a sub-centimeter scale for a core sample using a combination of x-ray computer tomography, pressure decay profile permeability, and image analysis techniques. The derived high-resolution porosity, permeability, and μLFs distribution represents the primary input to a single phase flow model. This model was used to simulate whole-core steady-state tests from which absolute permeability for different orientations was derived. Several simulation sub samples with random location and volume are also selected for evaluation of the effect of scale/composition on the calculated permeability. The core sample evaluated exhibits three dominant rock types and a bimodal permeability within the microdarcy (μLFs SS2+SH1) and millidarcy ranges (μLFs SS1). The calculated (from whole core simulation) vertical and horizontal permeability values are in good agreement with actual RCA measurements from offset cores. Despite relatively good reservoir quality associated with μLFs SS1, results from the full diameter core simulation demonstrate that its limited volumetric abundance and restricted connectivity prevent this rock type from dominating the fluid flow process in these rocks. In fact, permeability seems to be dominated by the tighter encasing matrix (μLFs SS2 + SH1), which exhibits average permeability values very close to those reported from routine core analysis. The methodology used in this work is particularly applicable to the detailed characterization of reservoir rocks with high degree of heterogeneity associated with biological reworking and/or selective diagenetic imprints. The model incorporates statistical variations for several key geological/engineering parameters and offers a direct comparison to results obtained from laboratory measurements.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".