Localized Reservoir Characterization Model for Hydraulic Fracturing Design in Tight Reservoirs
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Bibliographic record
Abstract
Abstract Tight reservoirs with low and ultralow permeability must be successfully stimulated to produce at economic oil or gas rates. For this reason, costs of drilling and completing wells are very high in tight reservoirs. In order to reduce these costs, operators have often tried to replicate the same or similar hydraulic fracturing designs that have been successfully used in previous wells in the same geological area. This strategy sometimes results in unexpected surprises and operational challenges leading to unsuccessful stimulations and poor production performance. The major reason behind these challenges is that tight reservoirs exhibit a localized behavior with changes in reservoir quality such as mineralogy, hydrocarbon content, and thickness across the same reservoir. In order to study the localized behavior of tight reservoirs; three wells that penetrated the Eaglebine formation in Texas were evaluated. The Eaglebine formation contains both the Eagle Ford and the Woodbine reservoirs. The combined Eagle Ford and Woodbine (Eaglebine) reservoir can sometimes exceed 1,000 feet in thickness. These reservoirs are present at depths between 6,500 and 15,000 feet in East Texas. In some areas, the Eaglebine contains a large percentage of silica-rich sands interbedded in organic rich shale and carbonate layers. This paper investigates the reasons as to why same hydraulic fracturing techniques should not be applied necessarily for every well in the same geological area. Furthermore, it demonstrates how we can exploit the localized reservoir behavior to plan for future wells despite limited data availability. Data from mud logs, well logs, and cores, including mineralogy and geomechanical data are integrated to build the localized reservoir characterization model that can be used to plan how each individual well should be hydraulically fractured. The model provides information such as location of organic-rich zones, brittle zones, and ductile zones in a geological area. Lastly, it recommends the type of fracture fluid that can yield a successful stimulation operation in ductile or brittle zones.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it