A Petrophysical Dual Porosity Model for Evaluation of Secondary Mineralization and Tortuosity in Naturally Fractured Reservoirs
Bibliographic record
Abstract
Abstract Quantification of secondary mineralization or cementation within natural fractures has not been considered in previous petrophysical dual porosity models. This is however of paramount importance as morphology of the fractures indicates that they can be open, partially or completely mineralized. If cementation with secondary minerals is complete the recovery of hydrocarbons will be generally very small. If secondary mineralization is partial, production rates and recoveries could be quite significant as the secondary minerals would play the role of natural proppant agents helping to maintain the fractures open as the reservoir is depleted. If the fractures are initially open, production rates and recoveries could be large or small dependent on the orientation of the natural fractures and in-situ stresses. These observations lead to the key objective of this paper: to develop an analytical dual porosity model for quantifying secondary mineralization (cementation) and tortuosity in natural fractures. The method further allows estimating matrix and fracture porosities, and fracture compressibility based on the amount of secondary mineralization. Use of the new dual porosity model is explained with two core data sets drawn from tight gas formations in the United States and Canada. A comparison is made with results of current dual porosity models that do not take into account secondary mineralization within the natural fractures and tortuosity. The conclusion is reached that the proposed dual porosity model provides a valuable new quantitative tool for petrophysical evaluation of naturally fractured reservoirs. In addition, the methodology allows estimating fracture compressibility, a usually elusive parameter needed for estimating original petroleum in place in naturally fractured reservoirs. Although the methodology is explained using data from tight sandstones it also has application in other types of reservoirs and lithologies.
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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 | 0.001 |
| 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) | 0.001 | 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".