  The reserve of crude oil in the Arctic area is abundant. Ice melting is
making it possible to have intermediate access to the Arctic crude oil and its
transportation. A novel compositional data's grey model is proposed in this
paper to structurally forecast Arctic crude oil import. Firstly, the general
accumulative operation sequence of multivariate compositional data is defined
according to Aitchison geometry, then obtaining the novel model with the form
of the compositional data vectors. Secondly, this paper studies the least
square parameter estimation of the model. The novel model is deduced and
selected as the time-response expression of the solution. Thirdly, this paper
infuses the novel model with traditional grey model to improve its robustness.
Differential Evolution algorithm is introduced to determine the optimal value
of the general matrix. Lastly, two validation examples are provided for
confirming the effectiveness of the novel model by comparing it with other
existing models, before being employed to forecast the crude oil import
structure in China. The results show that the novel model provides better
performance in all crude oil cases in short-term forecasting. Therefore, by
using the new model, China's development parameter is 0.5214 and Determination
Factor of the novel model is 0.5999, which means that the crude oil import
structure of China is being changed. Specifically, the amount of crude oil
imported from the Arctic area is obviously increasing in the next 6 years,
showing sufficient proof of the edge owned by the Arctic area: abundant crude
oil reserves and shortening transportation distance.
