Introducing a Customized Workflow to Analyze DFIT-FBA Post-Flowback Shut-In (Rebound) Data
Bibliographic record
Abstract
Abstract DFIT-FBA (FBA = flowback analysis) offers a faster alternative to traditional diagnostic fracture injection tests (DFITs) for determining key parameters used in hydraulic fracturing design. While a method exists for estimating reservoir pressure from the flowback period of DFIT-FBA, this method could be inaccurate for certain cases. In this study, shut-in data (also called rebound) recorded after the flowback period of the DFIT-FBA test were analyzed to provide an independent estimate of reservoir pressure. An extensive DFIT-FBA post-flowback shut-in test was simulated and analyzed to interpret all pressure signatures. This detailed investigation provided valuable insights into physical mechanisms occurring during the post-flowback shut-in period of a DFIT-FBA test. Based on these findings, a customized analysis workflow was developed and then utilized to estimate reservoir pressure from post-flowback shut-in data for nine field cases. These results were then compared with the results obtained from the analysis of the flowback period of DFIT-FBA. Key observations from the simulation study include: 1) linear flow is the only reservoir flow regime observed during the post-DFIT-FBA shut-in data of the simulated case; 2) reservoir pressures estimated from the shut-in test are always higher than the actual reservoir pressure even after an extended shut-in period. The major takeaways from analyzing field examples include: 1) shut-in pressures recorded after a DFIT-FBA test reach a maximum, and will decline if pressure is monitored long enough; 2) more accurate reservoir pressure estimates will be obtained if the test is extended far beyond the point where maximum pressure is observed; 3) if the minimum horizontal stress and reservoir pressure are similar in magnitude, and/or occur close in time, the reservoir pressure signature during the flowback period of a DFIT-FBA could be masked by the fracture closure event. In such cases, the reservoir pressure estimate obtained from the analysis of DFIT-FBA flowback data should be used with caution, unless confirmed through independent estimates, such as DFIT-FBA post-flowback shut-in data.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.009 |
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".