Sensitivity-based data reduction of large 3D DC/IP surveys

Abstract

Summary In this paper, we present an algorithm based on the sensitivity of the data to the model space to reduce the large amount of data commonly collected during 3D DC/IP surveys to only those most relevant and important to the model space. The sensitivity-based data reduction (SBDR) algorithm is demonstrated using both synthetic and field data examples. The results indicate that the SBDR recovered models are valid solutions to the full inversion problem but require a fraction of the computation time and resources, providing a geologic solution in a much shorter time than required to solve the full inversion problem.