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Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
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Rapidly Varying Flow01:24

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Related Experiment Video

Updated: Mar 12, 2026

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses
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Numerical simulation of reservoir parameters' synergetic time-variability on development rules.

Jian Hou1, Yanhui Zhang2, Daigang Wang2

  • 1State Key Laboratory of Heavy Oil Processing, China University of Petroleum, Qingdao, China ; College of Petroleum Engineering, China University of Petroleum, Qingdao, China.

Journal of Petroleum Exploration and Production Technology
|November 8, 2016
PubMed
Summary

This study introduces a new simulation method to understand how changing reservoir properties, like porosity and permeability, affect oilfield development. The method links microscopic pore-scale variations to macroscopic reservoir behavior for better oil recovery predictions.

Keywords:
Network simulationReservoir numerical simulationReservoir parameterTime variabilityWater flooding

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Area of Science:

  • Petroleum Engineering
  • Reservoir Engineering
  • Computational Geoscience

Background:

  • Reservoir parameter variability significantly impacts oilfield development strategies during water flooding.
  • Interdependencies exist between the time-variability of different macroscopic reservoir parameters.

Purpose of the Study:

  • To develop a novel simulation method integrating micro and macro scales to analyze the synergetic time-variability of reservoir parameters.
  • To enhance oilfield development rules by accurately modeling parameter fluctuations.

Main Methods:

  • Utilized microscopic network simulation to model micro-parameter variations and their effects on macro-parameters.
  • Integrated microscopic and reservoir numerical simulations to create a comprehensive variability model.
  • Developed an improved reservoir numerical simulator considering time-varying porosity, permeability, and relative permeability.

Main Results:

  • The new method effectively simulates the influence of micro-parameter changes on macro-parameters.
  • A comprehensive model was established to represent reservoir parameter variability.
  • The improved simulator accurately models the impact of synergetic parameter variations on oilfield development.

Conclusions:

  • The developed simulation approach accurately captures the synergetic time-variability of reservoir parameters.
  • This method provides a more realistic simulation of oilfield development under dynamic reservoir conditions.
  • Enhanced understanding of parameter interactions leads to optimized oilfield management and improved recovery.