Abstract:

CO₂ solubility in saline aquifer is an important parameter for estimating the volume of CO₂ that can be dissolved and stored underground. To rapidly and economically evaluate and analyze the solubility of CO₂ in saline aquifers, a study was conducted using grey GM（1,1） modeling based on existing data of CO₂ 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 CO₂ solubility in saline aquifer based on grey Markov theory was proposed. The 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 CO₂ in underground salt water.

Key words: CO₂ solubility, saline aquifers, dissolution, Markov theory, grey GM（1,1） model, forecast method