This paper presents a distributed and dynamic programming framework to the mining rate target tracking of multiple mines under financial uncertainty. A single mine's target tracking is stated as a stochastic optimization problem, and the solution is obtained by solving the dynamic program which gives the optimal production rate schedule of each mine as a Markovian feedback control on the price process. The global solution is distributed on multiple mines by a policy iteration method, and this iterative method is shown to provide the unique equilibrium among Markovian strategies. Numerical results confirm the efficacy of the proposed global method compared to individual optimization of mining rate target tracking.