Slope tomography based on adaptive constraints of reflection-point positions

Slope tomography inverts the traveltimes and slopes of locally coherent reflected waves to reconstruct the subsurface background velocity model. By employing all reflected waves passing through a discrete grid cell for its velocity inversion, conventional slope tomography introduces notable averaging effects, which in turn reduce the accuracy of the inverted model. To mitigate this problem, we propose an improved slope tomography method by incorporating adaptive constraints of reflection-point positions. The method adaptively weights reflection data according to the distance between reflection points and grid cells: the greater the distance, the smaller the weight, and vice versa. Consequently, the velocities of shallow and deep layers are inverted from their corresponding reflection data, which mitigates the gradient averaging effects and improves the accuracy of the inverted model. Numerical tests and a field data application verify the accuracy and effectiveness of the proposed method.