Shale plays: Production forecasts fromnumerical simulation predictive.
Bibliographic record
Abstract
The Shale gas is natural gas produced from Shales. Over the last decade, this resource has become an increasingly important source of energy in the United States, and interest has spread to Canada, Europe, Asia, Australia and now Latin America. Due to extremely low permeability to permit fluid flow significantly, most Shale are not commercial sources of natural gas and qualify as unconventional resources, as well as the coal bed methane, the tight sands and gas hydrates. To make the development of this resource economically feasible is necessary to implement horizontal wells technology combined with hydraulic fracturing techniques. In order to optimize the operational parameters, which are essential for the success of the operation, is very common production forecasting from reservoir simulation. A knowledge of the future behavior of shale gas reservoir to determine the viability of the projects, the economic estimates and expected production increase. In this paper shows the numerical and analytical modeling for a Single Well Model of shale gas in order to quantify the gas in place, the EUR of these deposits and determine the economic feasibility to produce these plays.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".