Thermal maturity of the Barnett Shale determined from well-log analysis
Bibliographic record
Abstract
Abstract Intensive development with large-scale fracturing treatments has made the Barnett Shale play (Newark East field) in the Fort Worth Basin the largest shale-gas field in the world. The Mississippian Barnett Shale is an organic-rich, self-sourced reservoir rock. Thermal maturity, thickness, and total organic carbon are the most important geological factors for commercial gas production from this shale formation. The log-derived thermal-maturity index (MI) has been developed in an effort to better understand and predict hydrocarbon phases across the basin. Maturity index was calculated using three types of open-hole logs: neutron porosity, deep resistivity, and density porosity (or bulk density). The derivation of MI is based on the hypotheses that shale gas is generated and stored locally without apparent migration from outside sources, and that the water saturation and the density of generated hydrocarbons decrease with an increase in thermal maturity. Maturity index correlates well with initial gas:oil ratios (GOR) from well production data. Based on this correlation, an empirical relationship has been demonstrated for the Fort Worth Basin. This method is useful in understanding the thermal-maturity levels of Barnett Shale source rock in the gas-generation window. Mapping MI, GOR, and gas heating value from hundreds of wells identifies the various maturity stages and areas of Barnett Shale that generate oil, condensate, wet gas, or dry gas in the Fort Worth Basin.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".