Streamline Simulation of Barium Sulfate Precipitation Occurring Within the Reservoir Coupled With Analyses of Observed Produced-Water-Chemistry Data To Aid Scale Management
Why this work is in the frame
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Bibliographic record
Abstract
Summary In waterflooded reservoirs under active scale management, produced-water samples are routinely collected and analyzed, yielding information on the evolving variations in chemical composition. These produced-water chemical-composition data contain clues as to the fluid/fluid and fluid/rock interactions occurring in the subsurface, and are used to inform scale-management programs designed to minimize damage and enable improved recovery. In this interdisciplinary paper, the analyses of produced-water compositional data from the Miller Field are presented to investigate possible geochemical reactions taking place within the reservoir. The 1D and 2D theoretical model has been developed to test the modeling of barium sulfate precipitation implemented in the streamline simulator FrontSim. A completely 3D streamline simulation study for the Miller Field is presented to evaluate brine flow and mixing processes occurring in the reservoir by use of an available history-matched streamline reservoir-simulation model integrated with produced-water chemical data. Conservative natural tracers were added to the modeled injection water (IW), and then the displacement of IW and the behaviors of the produced water in two given production wells were studied further. In addition, the connectivity between producers and injectors was investigated on the basis of the comparison of production behavior calculated by the reservoir model with produced-water chemical data. Finally, a simplified model of barite-scale precipitation was included in the streamline simulation, and the calculation results with and without considering barite precipitation were compared with the observed produced-water chemical data. The streamline simulation model assumes scale deposition is possible everywhere in the formation, whereas, in reality, the near-production-well zones were generally protected by squeezed scale inhibitor, and, thus, the discrepancies between modeled and observed barium concentrations at these two given wells diagnose the effectiveness of the chemical treatments to prevent scale formation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it