Production Data Analysis of Multi-Fractured Horizontal Wells Producing from Tight Oil Reservoirs – Bounded Stimulated Reservoir Volume
Bibliographic record
Abstract
Abstract Multi-fractured horizontal wells (MFHWs) are the most widely used technology for producing tight oil and gas reservoirs. Production data from a MFHW may exhibit multiple linear flow periods including linear flow within the fracture, linear flow in the stimulated reservoir volume (SRV), and linear flow in the unstimulated region of the reservoir. This study focuses on an SRV containing infinite-conductivity hydraulic fractures and no fluid flow contribution from the unstimulated region. The existing analytical models for these flow periods have been developed based on the linearized form of the flow equation. However, these models introduce considerable errors in permeability estimation and production forecasts for tight oil reservoirs if they do not account for stress-sensitivity. In previous work by the authors, the stress-sensitivity of permeability was incorporated into rate transient analysis (RTA) of tight oil reservoirs during transient flow period for wells containing a single hydraulic fracture. In this paper, the effects of stress-dependent formation permeability on the production data of MFHWs are studied. A new model is used to correct the conventional RTA techniques for these effects to improve permeability estimation and oil production forecasting. This study shows that the conventional methods that do not account for stress sensitivity give less accurate results for MFHWs producing under a high pressure drawdown. The results show that the new method reduces the error of the conventional techniques significantly and provides a reliable strategy for RTA of MFHWs. This study fulfills two important requirements of the tools for RTA of MFHWs; simplicity and accuracy. The strategy is to keep the conventional analysis routine unchanged, with a correction factor applied to account for the effects of the stress-sensitivity of permeability. The value of the correction factor is that it shows how far the conventional analytical methods are from the exact solutions. Further, the correction factor is used to remove the considerable error in conventional analyses.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".