An Improved Triple-Porosity Model for Evaluation of Naturally Fractured Reservoirs
Bibliographic record
Abstract
Summary Many naturally fractured reservoirs are composed of matrix, fractures, and nontouching vugs (there can also be any other type of nonconnected porosity that can occur; for example, in intragranular, moldic, and/or fenestral porosity). An improved triple-porosity model is presented that takes these different types of porosities into account. The model can be used continuously throughout a reservoir with segments composed of solely matrix porosity, solely matrix/fractures, solely fractures/vugs, or the complete triple-porosity system. The model improves a previous triple-porosity algorithm by handling rigorously the scale associated with each: matrix, fractures, and vugs. This permits determining more-realistic values of the cementation or porosity exponent, m, for the composite system and consequently improved values of water saturation and reserves evaluations. The values of m for the triple-porosity reservoir can be smaller than, equal to, or larger than the porosity exponent of only the matrix blocks, mb, depending on the relative contribution of the vugs and fractures to the total porosity system. It is concluded that not taking into account the contribution of matrix, fractures, and vugs in the petrophysical evaluation of triple-porosity systems can lead to significant errors in the determination of m, and consequently in the calculation of water saturation, hydrocarbons in place, and recoveries, and ultimately can lead to poor economic evaluations—either too pessimistic or too optimistic. This is illustrated with two examples from Middle East carbonates.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".