Optimizing Seismic Survey Design and Processing Flows: A Fast Tree Search Using the Van Trees Inequality

The goal in designing a seismic survey is to achieve an optimal tradeoff between cost and information accuracy. There are many options for seismic data acquisition and multiple algorithms to choose from at each processing step. Each choice affects the cost as well as the accuracy of reservoir property estimates. The Van Trees inequality is a lower bound on the mean squared error of any estimate of a parameter from a data set. It can be used in conjunction with a fast tree search algorithm to rapidly identify the combination of acquisition and processing options that minimizes an objective function of both cost and estimate mean squared error. The bound can also identify for future research those steps in acquisition and processing where the most information is being lost. These applications are illustrated in assembling an acquisition and processing plan to estimate oil sand thickness.