Abstract Differential semblance optimization (DSO) is an approach to the inversion of the velocity which avoids the severe convergence associated with nonlinear least-squares inversion.DSO method-based wave-equation migration velocity analysis measures the focusing or flatness of image gathers and uses the deviation as the criterion to update the velocity.The DSO objective function has a decent global convexity property,therefore it can avoid the local minima problem,the gradient of objective function is smooth,it can inverse the background velocity accurately when there lacks low frequency data.Generally,ODCIGs is used to construct the objective function.In this paper,the authors use ADCIGs to construct the objective function,and the result of the test shows that DSO method with ADCIGs can estimate the correctness of velocity model directly and reflect the coupling relation between velocity and depth accurately.
Received: 01 August 2016
Published: 20 October 2017
