A Simplified Engineering Model Integrated Stimulated Reservoir Volume (SRV) and Tight Formation Characterization With Multistage Fractured Horizontal Wells
Bibliographic record
Abstract
Abstract Stimulated Reservoir Volume (SRV) is an engineering concept developed for the purposes of quickly evaluating the effective well drainage area and analyzing the actual performance of a multistage horizontal well in tight formation. Usually SRV is defined using microseismic event mapping. However, there are many other factors hindering the realization of the correct SRV value and largely impairing its engineering application. A simplified integrating model with multiple regions that combines the near wellbore engineered reservoir area, the SRV region, the original tight formation area and the outbound reservoir region, named as region I, II, III and IV, respectively, were built and analyzed systematically, where the region I confines the horizontal wellbore with multiple artificial hydraulic fractures and allows the integration of complex skin factor distribution, region II intends to capture the influence of SRV under various parametric settings such as fracture networking and matrix-fluid mobility variations, region III accommodates the general geological information for the original large scale tight formation environment and region IV supports the information input for the outbound reservoir environment. The multiple region modeling has been successfully built and applied to understand the relationship among wellbore, fracture, SRV and original reservoir formation. Theoretical study on the transient pressure and rate responses were conducted to address the technical challenge encountered. The results, presenting in a type curve format under various conditions, have shown that SRV region is strongly related to the fracture influenced/dominated boundary flow regime and appears as a region possessing a less than 1 slope in pressure and reciprocal rate derivative curves, which indicates that the flow process has reached the theoretical SRV boundary, i.e., the fracture influenced area/boundary. However, the derivative value would not reach one due to the inflow from the outside original reservoir region. This phenomenon is a symbolic feature of tight formation with SRV connectivity, as many field cases have been so indicated. This work allows a quick estimation of SRV region, a better understanding of the influence of the complicated wellbore configurations and a way to characterize the reservoir connectivity between SRV and original/outbound tight formation reservoir.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".