| description abstract | Plugging is a prominent reason for production reduction in coalbed methane (CBM) wells. In order to solve this problem, authors conducted the feasibility analysis and optimal design of acidizing of CBM wells to remove the plugging in Hancheng block (H block) China. First, X-ray diffraction analysis shows that the plugging contains acid-soluble minerals and the field case indicates that acidizing effect is positively correlated with the content of acid-soluble minerals. Inspired by this, authors analyze determining factors of the content of acid-soluble minerals. Well logging parameters (DEN, AC, GR) are selected to establish a neural network model to predict the content of acid-soluble minerals. Furthermore, a feasibility criterion of acidizing of CBM wells is proposed. Then, a forward model and an inversion algorithm are proposed to diagnose the plugging. The multisolution problem of parameters inversion is solved by the Gauss–Marquardt (G-M) algorithm based on the stochastic initial value and maximum probability. Combining this method with the current numerical model of acidizing, authors present an optimal design in order to optimize the volume and injection rate of the acid. Meanwhile, by experimental study, authors propose a new acid formulation. Finally, results have been applied in the field to confirm the feasibility of the acidizing. It turns out that acidizing is an effective stimulation technology for some specific CBM wells, and the feasibility analysis and the optimal design can improve the effect of acidizing of CBM wells. | |
