Sweet Spot and Porosity Development in an Unconventional Source Rock Play
Bibliographic record
Abstract
Diligent reservoir characterization is the key to successful production in most unconventional plays. Unconventional resource plays require one to adapt to the scale of observation (1 nm to 1 μm) and to use special imagery techniques (e.g., scanning electron microscope [SEM], ion-milled SEM) to characterize the nature and classes of the pore system. For the Duvernay Formation, a quantitative approach to porosity typing and measurement was conducted on two- and three-dimensional focused ion beam SEM images. These images showed that between 69% and 85% of the porosity is kerogen porosity, with an average of 75% for the studied wells. It is important to recognize that although organic porosity is also developed in the less mature wells, the biggest pores were found in the most mature areas. These results indicate that there is a positive correlation between liquid yield and pore size, as well as a positive correlation between thermal maturity and pore size. The pore volume and/or the number of accessible pores increase (i.e., hydrocarbon in the pore volume and, thus, permeability) following the same trend as the mean pore size. It is concluded that the matrix porosity and, more importantly, the matrix permeability are primarily the result of thermal maturation of the kerogen. These results were not observed in previous studies due to an erroneous estimation of maturity using vitrinite reflectance, or a lack of appropriate diversity and quality of samples collected throughout the maturation phase windows to obtain statistically representative results. Subsurface data (wells, seismic), outcrop work from literature, and public domain production data from the West Shale Basin were integrated at the regional scale with this nanoscale pore-system characterization to define the hydrocarbon production potential of the Duvernay Formation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".