Rock physics of the Wolfcamp Formation, Delaware Basin
Bibliographic record
Abstract
ABSTRACT Production from wells in organic-rich shales often shows considerable lateral variation. Reliable predrill methods to characterize the lateral heterogeneity of such reservoirs are required to optimize the trajectory of lateral wells in these low-permeability reservoirs. Petrophysical interpretation of measured well logs provides information on mineral, porosity, and kerogen content. Combining the results of petrophysical analysis with P-wave, S-wave, and density logs allows generation of a probability density function (PDF) for each of the different significant lithofacies. The PDFs are applied to the P- and S-impedance from prestack seismic amplitude variation with offset inversion to predict the spatial variation in the distribution of lithofacies and associated probability for the Wolfcamp Formation in an area covered by a 3D seismic survey in the Delaware Basin, West Texas. An anisotropic rock-physics model for the Wolfcamp Formation allows the effect of complex mineralogy, organic carbon concentration, and porosity on the P- and S-impedance to be investigated. Kerogen inclusions and pores act to increase Thomsen’s anisotropy parameter ϵ relative to γ, and there is a competition between clay matrix anisotropy and inclusion shape anisotropy in determining the anisotropy of the rock. Inclusions with isotropic elastic properties act to decrease the anisotropy due to the dilution effect, but this decrease is partially offset by the increase in anisotropy due to the anisotropic shape of the inclusions. Application of the model to the determination of minimum horizontal stress indicates that kerogen-rich siliceous shales have the lowest value of minimum horizontal stress, whereas silica-rich calcareous shales, mixed siliceous shales, and clay-rich siliceous shales have higher values and may therefore act as barriers for the vertical growth of hydraulic fractures.
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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 | 0.001 |
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".