Sampling a Stimulated Rock Volume: An Eagle Ford Example
Bibliographic record
Abstract
Summary Between 2014 and 2016, ConocoPhillips drilled five deviated wells adjacent to a multistage, stimulated horizontal producer to sample the physical characteristics of the reservoir stimulation caused by hydraulic fracturing in the Eagle Ford Formation in DeWitt County, Texas. The design, execution, and results of the pilot are described. This pilot establishes the paucity of pre-existing natural fractures in this locale and enables the determination of the spatial characteristics of the stimulation using information derived from the core, cuttings samples, borehole-image logs, tracer logs, microseismic, distributed temperature sensing (DTS)/distributed acoustic sensing (DAS), and pressure data. Results show that stimulation effectively breaks the reservoir rock and makes a complex array of hydraulic fractures that are more closely spaced near the producer. Some fractures, however, extend interwell distances of more than 1,000 ft. The pilot data indicate that abundant proppant transport appears to be limited to distances less than 75 ft from the producer, which suggests that the stimulated rock volume (SRV) might be greater than the volume of rock that can be effectively drained.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".