The invention discloses an IDW interpolation method for multi-parameter collaborative optimization of geoscience data. The method comprises the steps of A, giving initialization conditions of a
particle swarm algorithm, enabling the searching dimension D to be 4(alpha,
lambda, theta, N), wherein alpha is a distance
attenuation coefficient,
lambda is a distance adjustment parameter, theta is an
anisotropy direction, N is a
nearest point number, and generating a group of solution sets containing (alpha,
lambda, theta, N) by adopting a random
population initialization method; B, calculating the fitness value of the particle swarm; C, acquiring an individual optimal value pbesti of each particle; D, obtaining a
global optimal value of the group; E, updating the speed and the position of the particle; F, if the termination condition of the
particle swarm algorithm is not met, returning to the step B, and when the termination condition of the
particle swarm algorithm is met, stopping updating; G, outputting the optimal position; and H, substituting the optimized parameter combination solution (alpha, lambda, theta, N) into the IDW interpolation model to obtain a to-be-interpolated pointattribute value. According to the method, the defects in the prior art can be overcome, and the satisfactory solution of the IDW interpolation effect in the global sense is obtained.