Delineating Stacked Pay with Existing and Emerging Diagnostic Tools
Bibliographic record
Abstract
Abstract Stacked pay in unconventional plays has emerged as the primary focus for a majority of operators in North America. The number of completion targets range from two zones in the Bakken to more than ten zones in areas of the Permian Basin. Proper development of multi-zone reservoirs will yield the greatest recovery factor for the unit and minimize the drilling hazards and completion challenges related to depletion. Proper development maximizes the propped height while minimizing propped fracture overlap; this combination improves recovery without overcapitalizing the completion. This paper will review existing and emerging diagnostic tools deployed in the STACK (Sooner Trend Anadarko Canadian and Kingfisher counties) to identify the number of landing intervals required to effectively drain the Meramec formation. The Meramec formation has produced a number of prolific wells from several benches contained within several hundred feet of reservoir. The diagnostic tools that will be reviewed in this paper include electromagnetic (EM) proppant detection, radioactive (RA) proppant tracer surveys and offset pressure responses. The EM proppant and RA proppant surveys were used in a vertical well to measure the propped fracture height. The presence of the RA tracer is detected using a spectral gamma ray log; the EM proppant is mapped using a surface array of electric- and magnetic-field receivers. Downhole gauges in a vertical well measured the pressure responses generated during the treatment of an offsetting horizontal well to evaluate the effects of fluid viscosity on fracture height. Results from the diagnostic tools have been integrated into the well spacing strategy for upcoming development units.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".