The Use of Electromagnetic Mixing Rules for Petrophysical Evaluation of Dual- and Triple-Porosity Reservoirs
Bibliographic record
Abstract
Summary Electromagnetic mixing rules such as the Maxwell-Gamett rule, the Bruggeman equation, and the coherent-potential formula, are shown to be useful for the evaluation of the porosity exponent m in naturally fractured reservoirs represented by dual- and tripleporosity models. Comparisons are made with core data from limestone, dolomite, and tight gas reservoirs to corroborate results from the theoretical models. Rigorous values of m reduce the uncertainty in the calculated values of water saturation and, thus, improve the estimates of hydrocarbons in place and recoveries, particularly in situations in which sufficient data are not available to use the material-balance approach. The main advantage of the new method developed in this paper for petrophysical analysis is that it can handle, with the use of a single equation, the individual mixing rules previously mentioned, and at the same time, depending on the availability of data, it can quantify the values of matrix, fracture, and nonconnected-vug porosity, and the porosity exponent of the total porosity system. It is concluded that electromagnetic mixing rules provide a useful methodology for the petrophysical evaluation of complex dual- and triple-porosity reservoirs.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| 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) | 0.001 | 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".