Production Data Analysis of Multi-Fractured Horizontal Wells Producing from Tight Oil Reservoirs – Bounded Stimulated Reservoir Volume
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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