Acoustic and petrophysical properties of a clastic deepwater depositional system from lithofacies to architectural elements’ scales
Bibliographic record
Abstract
Abstract An analysis of acoustic, petrophysical, and stratigraphic heterogeneities has been completed at three scales for an outcropping/subcropping deep-water stratigraphic sequence: lithofacies (core/plug), lithostratigraphic unit (well log), and architectural element (seismic). Measurement techniques/instruments included outcrop measured sections; behind-outcrop drilling/logging/coring (and subsequent core and log analysis); ground-penetrating radar; shallow seismic reflection; and electromagnetic induction. At the lithofacies scale, four rock types are defined: (1) heterogeneous sandstones and (2) uniform sandstones, which differ in their grain composition and sedimentary structures, but do not differ significantly in average porosity, permeability, and acoustic impedance; and (3) organic-rich shales and (4) organic-poor shales, which exhibit significantly higher acoustic impedance than either sandstone type. There is an inverse relation between porosity and permeability versus acoustic impedance ofthe lithofacies at this scale. At the lithostratigraphic unit scale, three units of interbedded lithofacies are defined: (1) uniform sandstone prone, (2) heterogeneous sandstone prone, and (3) shale prone. Successive merging of thinner beds with thicker beds results in clear differences in average rock properties between the lithostratigraphic units, but there is insufficient variation about the averages to preclude statistically significant differentiation of the sandstones. Lithostratigraphic unit properties also vary laterally. At the architectural element scale, two architectural elements are channel element and lobe element. Only wellbore acoustic impedance differs significantly between these two elements. However, the internal lateral architecture of these two elements is quite different. The results highlight the difficulty in evaluating stratigraphic patterns away from the wellbore. More research in this area is warranted. Attempts to quantify lateral variability of properties in a geologically realistic manner are encouraged because lateral variability is as important to reservoir characterization and performance as is vertical variability.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".