Underground salt cavern reservoirs are ideal spaces for energy storage. China is rich in salt rock resources with layered lacustrine sedimentary structures. However

the dissolution mechanism of layered salt rocks remains poorly understood

resulting in significant differences between the actual measurements and the designed indices for the layered salt rock water-soluble cavity-making cycle and the cavity shape. In this work

the dissolution rates of 600 groups of layered salt rocks in China under different conditions were determined experimentally. Thus

the established artificial neural network prediction model was used to assess the effects of the contents of NaCl

Na

2

SO

4

and CaSO

4

in the salt rocks

concentrations

dissolution angles

and flow rates on their dissolution rates by performing ANOVA and F-test. The results provide a theoretical basis for evaluating the dissolution rate of layered salt rocks under different conditions and for the numerical simulation of the layered salt rock water-soluble cavity-making process.