A Petrophysical Dual-Porosity Model for Evaluation of Secondary Mineralization and Tortuosity in Naturally Fractured Reservoirs
Bibliographic record
Abstract
Summary 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 because morphology of the fractures indicates that they can be open or partially or completely mineralized. If cementation with secondary minerals is complete, the recovery of hydrocarbons will be generally very small because hydrocarbons will not have any way to move from matrix to natural fracture and then to the wellbore. However, if secondary mineralization is partial, production rates and recoveries could be quite significant because 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 depending on the relative orientation of the natural fractures with respect to in-situ stresses. These observations lead to the key objective of this paper: to develop an analytical dual-porosity model using resistance networks for quantifying petrophysical fracture parameters such as degree of cementation (β), formation factor (F), dual-porosity exponent (m), and tortuosity (τ) for different degrees of mineralization (cementation) within the fractures. The method further allows estimating matrix and fracture porosities and fracture compressibility on the basis of 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 and reservoir-engineering evaluations of naturally fractured reservoirs. This is illustrated with two numerical examples that show determination of original petroleum in place and recovery. One example is volumetric, and the other one is based on the material-balance calculations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".