An Analytical Model for Analyzing and Forecasting Production From Multifractured Horizontal Wells With Complex Branched-Fracture Geometry
Bibliographic record
Abstract
Summary Analytical methods for analyzing and forecasting production from multifractured horizontal wells completed in unconventional reservoirs are in their infancy. Among the difficulties in modeling such systems is the incorporation of fracture-network complexity as a result of the hydraulic-fracturing process. Along with a primary propped-hydraulic-fracture network, a secondary fracture network, which may or may not contain proppant, may be activated during the stimulation process, creating a “branched-fracture” network. These secondary fractures can be the result of reactivation of healed natural fractures, for example. In the current work, we develop a fully analytical enhanced-fracture-region (EFR) model for analyzing and forecasting multifractured horizontal wells with complex fracture geometry that is more-general, -rigorous, and -flexible than those previously developed. Specifically, our new model allows nonsymmetric placement of a well within its area of drainage, to reflect unequal horizontal-lateral spacing; this is a very real scenario observed in the field, particularly for the external laterals on a pad. The solutions also can be reduced to be applicable for homogeneous systems without branch fractures. In addition to the general EFR solution, we have provided local solutions that can be used to analyze individual flow regimes in sequence. We provide practical examples of the application (and sometimes misapplication) of local solutions by use of simulated and field cases. One important observation is that a negative intercept obtained from a straight line drawn through data on a square-root-of-time plot (commonly used to analyze transient linear flow) may indicate EFR behavior, but this straight line should not be interpreted as linear flow because it represents transitional flow from one linear-flow period to another. Our general EFR solution therefore provides a powerful tool to improve both forecasting and flow-regime interpretation for hydraulic-fracture/reservoir characterization.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".