Determination of target-oriented parameters for computation of curvature attributes
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Bibliographic record
Abstract
The application of curvature attributes on seismic horizons or 3D seismic volumes has been discussed in the literature in several ways. Such discussion largely ignores the detail of parameter selection that must be made by the working interpreter or the expert processor. Parameter selection such as window size and filtering methods for seismic curvature estimates have not been extensively compared in the literature and have never been validated using quantitative ground truthing to log or drilling data. Of even greater relevance to the interpreter is the lack of discussion of curvature parameters as they are relevant to interpretive and operational concerns. We focus on the seismic most-positive curvature attribute, its parameterization, and filtering for the overpressured tight sand target in the Falher F formation of the deep basin of Alberta, Canada. This sand has numerous natural fractures that constitute an occasional drilling hazard due to mud losses. Various parameterizations on horizon- and volume-based curvature extractions are made and examined in the context of the drilling results of four horizontal wells, one of which has image log fracture density along the lateral portion of the well. We compared different lateral (and vertical where applicable) window sizes in the initial curvature estimates, as well as different postcurvature filtering approaches including unfiltered, Gaussian-filtered, and Fourier-filtered products. The different curvature attribute estimates have been evaluated by way of map comparisons, cross-section seismic line comparisons, and correlations with the upscaled fracture density log data. We found that our horizon-based estimates of positive curvature suffered from mechanical artifacts related to the horizon picking process, and the volume-based methods were generally superior. Of the volume-based methods, we found that the Fourier-filtered curvature estimates were the most stable through smaller analysis windows. Gaussian-filtering methods on volumetric curvature gave results of varying quality. Unfiltered volumetric curvature estimates were only stable when very large time windows were used, which affected the time localization of the estimate. The comparisons give qualitative and quantitative perspective regarding the best parameters of curvature to predict the key properties of geologic target, which in this case are the potentially hazardous natural fractures within the overpressured Falher F sandstone.
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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 it