Transient Pressure Response of Fluvial Reservoir With Branching Channel and Splay
Bibliographic record
Abstract
Abstract Fluvial reservoirs with branching channels and splays comprise a commonly encountered depositional system, however, characterization of this type of system using transient pressure analysis has not yet been fully explored. This article presents a semi-analytical method to compute the transient pressure and pressure response for this system type. It simplifies the computation by decoupling the complex-geometry system into a discrete set of simple-geometry systems that are in hydraulic contact with each other, and exchange fluids at their hydraulic contacts[1,2]. The computed pressure and pressure derivatives were compared with those of other simple well/reservoir systems to gain insight into the information contained in the responses. The source and sink method[3] was used to compute the pressure response in the Laplace domain and the results were inverted numerically using the Stehfest Inversion algorithm[4]. The discussion in this paper is focused on four cases, consisting of a main channel and a side branch that connects with the main branch at angles of 30, 45, 60 and 90 degrees, respectively. In each of these cases, the set of "image" wells that create no-flow boundaries is easy to generate, and an efficient computational algorithm is developed. Excellent pressure and pressure derivative responses have been obtained; detailed examination of these responses provides insight into methods that may aid in the identification and characterization of this type of system.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".