Effect of Fracture Dip and Fracture Tortuosity on Petrophysical Evaluation of Naturally Fractured Reservoirs
Bibliographic record
Abstract
Summary A model is developed for petrophysical evaluation of naturally fractured reservoirs where dip of fractures ranges between zero and 90°, and where fracture tortuosity is greater than 1.0. This results in an intrinsic porosity exponent of fractures (mf) that is larger than 1.0. The finding has direct application in the evaluation of fractured reservoirs and tight gas sands, where fracture dip can be determined, for example, from image logs. In the past, a fracture-matrix system has been represented by a dual-porosity model which can be simulated as a series-resistance network or with the use of effective medium theory. For many cases both approaches provide similar results. The model developed in this study leads to the observation that including fracture dip and tortuosity in the petrophysical analysis can generate significant changes in the dual-porosity exponent (m) of the composite system of matrix and fractures. It is concluded that not taking fracture dip and tortuosity into consideration can lead to significant errors in the calculation of water saturation. The use of the model is illustrated with examples.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 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 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".