Experimental Investigation and Numerical Simulation of Water Imbibition in Fractured Turbidite Systems
Bibliographic record
Abstract
Abstract The flow description applied for double porosity reservoirs is of paramount importance for evaluating the performance of fractured turbidite reservoirs. Many authors have measured in the lab and formulated formulas describing the transfer function between the fracture and the contiguous less permeable porous media. Other authors using these transfer functions described the flow behavior in a system of double porosity and double permeability. In this work, laboratory tests were performed in long cores with different fluids, diverse wettability condition and various flow rates. At first experiments were conducted on unfractured cores. Then, for the same core, geometry, flow pattern and fluids, the transfer function that occurred in a subsequent flow test for a double porosity system was measured. The saturation history during the test was measured with an X-ray scanning system. The experiments were conducted quite differently from those commonly used in imbibition experiments and provided additional insight into oil recovery from fractured reservoirs. In order to describe the lab flow tests it was used three mathematical approaches, namely: a finite difference commercial reservoir simulator, a semi-analytical solution, and an analytical solution for the hyperbolic system of equations governing the process. The experimental results obtained were matched satisfactorily by the three mathematical approaches investigated. At the end, the first two mathematical methods were applied to predict the production behavior for an equivalent injection pattern in a Brazilian fractured turbidite 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) | 0.000 | 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 | 0.001 | 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".