Parent Well Characterization by Comparative Analysis of Initial and Second Flowback
Bibliographic record
Abstract
Abstract Infill drilling is becoming a common practice for more efficient development of tight reservoirs. However, child-well stimulation may lead to a parent-child well interference or a fracture hit. To mitigate the negative impacts of a fracture hit, the parent well is preloaded before the stimulation of child wells. Then, the injected water during the pre-loading period is later produced back to the surface. The preloading flowback (second flowback) data of parent wells may provide an opportunity for fracture charactrization. The main objective of this research is to compare the responses of initial and second flowback to capture the changes in fracture characterstics after production and preload processes. We construct rate-normalized pressure (RNP) diagnostic plots on both initial and second flowback (IFB and SFB, respectively) of six multi-fractured horizontal wells completed in Niobrara and Codell formations in DJ Basin. In general, the slope of RNP versus MBT during the SFB period is higher than that during the IFB period, except for well 1. We estimate the changes in average effective fracture volume (Vef) by analyzing the changes in the RNP slope and total compressibility during these two flowback periods. Compared to the IFB period, the Vef is generally decreased during the SFB period. The loss percentage of effective fracture volume (RVef) is estimated at 10-40%. We also compare the drive mechanisms for the two flowback periods by calculating the compaction drive index (CDI), hydrocarbon-drive index (HDI), and water-drive index (WDI). The dominant driving mechanism during both flowback periods is CDI, but its contribution is reduced by 12% in the SFB period. This drop is generally compensated by a relatively higher HDI during this period. Finally, we investigate the effects of duration of production (tp) on RVef. There is a positive correlation between tp and RVef during the two flowback periods. Therefore, the loss of effective fracture volume might be attributed to the pressure depletion in fractures caused by the long production period (more than 800 days).
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.
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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".