Sailing speed is a critical factor affecting the ship’s energy consumption and operating costs for a voyage. Inland waterways present a complex navigation environment due to their narrow channels, numerous curved segments, and significant variations in water depth and flow speed. This paper constructs a model of a ship’s energy consumption based on an analysis of ship resistance and the energy transfer relationship of ships. The K-means clustering algorithm is introduced to divide the Yangtze River waterway into multiple segments based on the similarity of navigation environments. Considering the constraints of the ship’s main engine and the desired arrival time, a multi-objective particle swarm optimization (MOPSO) algorithm, improved with cosine decreasing inertial weight and Gaussian random mutation, is employed to optimize segmented navigation speeds to achieve different goals. Finally, four cases are studied with a fully electric ship navigating the reaches of the Yangtze River. The results indicate that the optimized speed can reduce ship energy consumption by up to 6.18% and significantly reduce ship energy consumption and operational costs under different conditions.

The distribution characteristics of remaining oil in low permeability reservoirs are aimed at the quantity and distribution of remaining oil in the reservoir at the present stage, so as to take measures to exploit these remaining oil under reasonable economic and technical conditions, so as to improve recovery. The technology of carbon dioxide hubbing and pumping is to inject a certain amount of carbon dioxide into the reservoir under a certain pressure, stew the well for a period of time to make the carbon dioxide spread in the formation and miscible with the formation crude oil, and then open the well for production. At present, there are many methods to study residual oil at home and abroad, mainly including reservoir engineering methods such as logging method, core analysis method, numerical simulation, and dynamic analysis method using monitoring data and dynamic and static data of reservoir. Study the macro and micro residual oil distribution accurately using CO2 huff and huff technology to increase production.