Analytical Modeling of Multistage Hydraulically Fractured Horizontal Wells Producing in Multilayered Reservoirs with Inter-Layer Pure-Planar Crossflow Using Source/Sink Function Method
Bibliographic record
Abstract
This study presents a comprehensive analytical modeling technology to model transient behaviors of multilayered reservoirs with inter-layer pure-planar crossflow induced by multi-stage hydraulically fractured horizontal well (MHFHW). The objective of this study is to develop an analytical model for multilayered reservoirs in conjunction with complex MHFHW and to achieve not only accurate and efficient computation, but also well-organized solutions expressed in a systematically integrated manner. The consideration of inter-layer crossflow across adjacent layers sets up the foundation for successful modeling of multilayered reservoirs. Source/sink function method (SSFM) is applied to describe fluid flow. Unsteady-state pressure or production rate solutions of MHFHW with the advantages of fast computation, accurate, and stable solutions are achieved. Comparative and consistent outcomes generated by this work and widely applied industry software have largely enhanced our technical confidence. More importantly, innovatively defined modified dimensionless terms that integrate systematic well-reservoir geometry information, as well as rock/fluid properties of each layer, have been newly applied to regulate the new modified dimensionless rate decline curve. This new technique sheds light on the reservoir characterization practice for complicated reservoir systems. Theoretical results in terms of transient pressure and rate were generated by the proposed multilayered model (SSFM-ML) for five scenarios of general concern, under various reservoir and well parameters, which were examined and discussed to demonstrate technical robustness. Not only does this study give solutions to the targeted multiple layered reservoirs, but it also provides insights into modeling three-dimensional fluid flow in heterogeneous reservoir with complex well configurations. It is recommended that future research should be conducted for more complicated two- and three-dimensional reservoirs, using the similar strategy of developing new type curves through adopting other new forms of modified dimensionless rate and time terms.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".