Integration of geology, petrophysics, and reservoir engineering for characterization of carbonate reservoirs through Pickett plots
Bibliographic record
Abstract
Abstract The concept of rock fabric has been shown to be very useful for characterization of carbonate reservoirs. This study shows that a Pickett crossplot of interparticle porosity vs. true resistivity (in some cases, apparent resistivity or true resistivity affected by a shale group) should result in a straight line for intervals with a constant rock fabric. The slope of the straight line is related to the porosity exponent m, the water saturation exponent n, and the size of the particles forming the interparticle porosity. Different slopes are obtained for different rock fabrics. The method helps to reconcile geology to fluid flow by illustrating the important link between geology, petrophysics, and reservoir engineering. Lines of constant rock fabric are displayed on a Pickett plot, together with water saturation, permeability, process speed k/ϕ, capillary-pressure curves, pore-throat apertures r35 and rp35, Kozeny's constant (Fsτ2), and height above the free-water table. Pattern recognition while placing all these data in a consistent form on a Pickett plot allows determination of flow units and a more rigorous characterization of carbonate reservoirs. The method is aimed at heterogeneous carbonate reservoirs, which have a limited amount of hard data. The use of this technique is illustrated with data from the Mission Canyon Formation in the Little Knife field of North Dakota, where a significant volume of oil in place is below the structural closure and updip wells penetrate microports that provide an effective seal in this stratigraphic trap.
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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 | 0.000 | 0.000 |
| 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".