Abstract: Multi-phase extraction (MPE) technology is commonly used for remediation of contaminated soil and groundwater in sites. The use of automated programs to efficiently calculate the reasonable horizontal layout plan and screen opening position of extraction wells plays an important role and significance in improving MPE remediation efficiency, reducing costs, and reducing carbon emissions during operation. This study used a self-developed MATLAB-TMVOC joint optimization program based on genetic algorithm to optimize the horizontal layout plan and screen position of extraction wells for benzene contaminated sites with different numbers of wells, and explored the optimal layout plan of extraction wells in sites with different soil permeability. The research results indicate that the MATLAB-TMVOC joint optimization program can efficiently simulate and optimize the layout plan of extraction wells, eliminating the complex manual parameter adjustment process, saving more than 50% of simulation time and more than 90% of simulation amount. The spacing between extraction wells should decrease with the decrease of soil permeability. For this study model, when the soil permeability is within the range of 10^-13 to 10^-12 m², the spacing between extraction wells should be reduced by 0.13 m for every 10^-13 m² decrease in soil permeability. The soil permeability decreases by an order of magnitude, and the spacing between extraction wells decreases by 17.8%~48.3%. When the permeability is below 10-¹³ m², the spacing between wells at the core of the site pollution plume should be less than 4 m. With the same number of wells, the optimized MPE repair can achieve a maximum improvement of 25.3% in repair efficiency compared to before optimization. With the same repair objectives, the optimized MPE repair plan can save 21.4% to 40.4% in operating costs, 29.7% to 34.7% in total costs, and 22.7% to 29.3% in carbon emissions. This study provides a joint optimization program approach for MPE simulation optimization, and provides data support for achieving low-carbon and efficient remediation of contaminated soil and groundwater.