Gas‐in‐place calculations in shale gas reservoirs using experimental adsorption data with adsorption models
Bibliographic record
Abstract
In this research, experimental adsorption measurements for a Dadas shale sample were conducted at various pressures (up to 13 790 kPa (2000 psia)) and temperatures (25, 50, and 75 °C) using pure methane (CH4). The effects of temperature and pressure on adsorption were observed. As pressure increases, CH4 adsorption increases. However, as temperature increases, CH4 adsorption decreases. Moreover, by using Langmuir isotherm and Ono‐Kondo models, experimental adsorption results were evaluated and adsorption isotherms were constructed. Although Ono‐Kondo and Langmuir isotherm models have similar fittings to the experimental adsorption data of Dadas shale, Ono‐Kondo models have several advantages. Different from Langmuir isotherms, the volume of adsorbed fluid, absolute adsorption data, and surface area of Dadas shale sample were predicted by Ono‐Kondo models. By comparing the results of the Ono‐Kondo monolayer and three‐layer models, the adsorption type of the Dadas shale sample was found as a monolayer (Type I). It was concluded that the Ono‐Kondo monolayer model is capable of fitting adsorption isotherms, especially at high pressures for shale samples. For initial gas‐in‐place calculations, the equations derived using the Langmuir isotherm were modified by the Ono‐Kondo monolayer model. For the first time, the Ono‐Kondo monolayer model was used in the formula of initial gas‐in‐place calculation. This formula provides better adsorption data evaluation, initial gas‐in‐place amounts, and adsorbed gas ratios in shale gas reservoir conditions compared to the values obtained with the Langmuir isotherm. This method is suggested to be used in flow and gas production simulations of shale gas reservoirs.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".