Theoretical Approach in Vp/Vs Prediction from Rock Conductivity in Gas Saturating Shaly Sand
Bibliographic record
Abstract
Most of study in Oil and Gas Industry are studying Vp/Vs behaviour against hydrocarbon presence in a porous rock. Vp/Vs number is commonly used to model Amplitude Variation against Offset response of a gas sand which allow us be able to discriminate it from the water sand. The model is built in term to match the synthesized Vp/Vs against the observed Vp/Vs which actually correspond to elastic property of porous and fluid saturating rocks. This study is aimed to find correlation between elastic property and conductivity of saturated rocks, especially reservoir in this study is found as a shaly sand unit, a turbidite sand deposit in Kutai Basin, East Kalimantan. The correlation between elastic property and conductivity properties are rarely discussed in many studies, however this study gives a new insight and evidence of how elastic and the inverse of conductivity (resistivity) properties are correlating both ways formulized theoretically with a support from Gassmann and Archie equations. In this study, more realistic condition is accomplished by taking clay mineral into account in sand unit and hence impact to Vp/Vs derivation from resistivity. Furthermore, sand-shale texture is considered important when this study giving a significant discrepancy of how clay mineral is distributed in sand unit and impacted to Vp/Vs and resistivity values. Thomas-Stieber diagram is useful when defining a disperse and/or laminate distribution of shale in the observed porous sand.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".