Surfactant Concentrations at Different Distances from the Injection Well

Area of Science:

• Petroleum Engineering
• Chemical Engineering
• Reservoir Engineering

Background:

• Accurate prediction of surfactant concentration profiles in reservoirs is crucial for effective surfactant-enhanced oil recovery (EOR).
• Traditional models struggle to account for dynamic surfactant depletion due to phase partitioning and rock adsorption during transport.
• Long-distance transport significantly impacts surfactant behavior, necessitating advanced modeling approaches.

Purpose of the Study:

• To develop a dynamic model for predicting surfactant concentration profiles in reservoirs.
• To understand the spatiotemporal evolution of surfactant concentrations during long-distance transport.
• To provide practical guidance for optimizing surfactant injection parameters in EOR operations.

Main Methods:

• Integrated experimental results from long-distance physical simulations.
• Monitored the spatiotemporal evolution of surfactant concentrations.
• Derived a dynamic governing equation by correlating partition coefficient and adsorption capacity with migration distance.

Main Results:

• Developed a mechanistic model revealing nonlinear kinetic characteristics of surfactant depletion.
• Quantified surfactant loss due to adsorption (monotonic decline) and partitioning (increased then decreased) with distance.
• Identified distinct control zones: near-well (0-100 m) governed by initial concentration, mid- to far-well (100-300 m) sensitive to cumulative injected pore volumes.

Conclusions:

• Shifted EOR design paradigm from concentration-based to volume-prioritized strategy for sustained effectiveness in deep zones.
• Established a robust theoretical framework for optimizing chemical injection in complex EOR operations.
• Provided practical guidance for enhancing oil recovery efficiency through better surfactant management.