CO

2

solubility in saline aquifer is an important parameter for estimating the volume of CO

2

that can be dissolved and stored underground. To rapidly and economically evaluate and analyze the solubility of CO

2

in saline aquifers

a study was conducted using grey GM（1

1） modeling based on existing data of CO

2

solubility in water under various temperatures

pressures

and salinities. By using Markov theory

the state interval was divided

the state transition probability matrix was constructed

and the prediction results were revised. A prediction model of CO

2

solubility in saline aquifer based on grey Markov theory was proposed. T

he results showed that the average relative errors between the predicted values of the grey Markov theory and the measured values were 1.52%、17.73%、0.21% and 3.97%

respectively. The average relative errors between the prediction results of the gray GM（1

1） model were 2.37%、19.29%、3.62% and 3.94%

respectively. The predicted values of the grey Markov model were more consistent with the measured data

and the prediction performance of the model was better

so as to provide a new method for predicting the solubility of CO

2

in underground salt water.