（研究的问题）To improve the measurement accuracy of the downhole accelerometer, a method for online compensation of accelerometer errors based on a magnetic-inertial coati optimization algorithm is designed. （研究的过程和方法）Firstly, an error compensation model is established based on the sources of error; the constraint conditions of the gravity angle and the magnetic-gravity angle are established using a gyroscope and a magnetometer; the difference between the true value of the acceleration and the modulus of the theoretical value is set as the objective function. Secondly, based on the coati optimization algorithm, the initial search boundary for error parameters is determined according to the recursive gravity acceleration, and the boundary is narrowed based on the relative distance among the current error parameters, the optimal error parameters, and the boundary values; a boundary point selection is designed to screen the initial error parameters, enabling the algorithm to initially search in the direction of high-quality solutions while retaining some inferior solutions to increase the diversity of error parameters; in the global exploration stage of the algorithm, parameters are designed to adjust the search range of accelerometer error parameters based on the error between the current error parameters and the average error parameters. Finally, the ratio of the modulus of gravity is set as the threshold for deep development, and a Gaussian mutation vector is constructed to enable the accelerometer error parameters to break out of local optima. （研究结果）Experimental results show that after MICOA compensation, the accelerometer error decreases, and the range of inclination angle decreases by approximately 62.5%; at different drilling angles, the root mean square error and standard deviation of the inclination angle can be maintained below 1°.