A compressive sensing approach to the calculation of the inverse data space
KAUST DepartmentPhysical Sciences and Engineering (PSE) Division
Environmental Science and Engineering Program
Earth Science and Engineering Program
MetadataShow full item record
AbstractSeismic processing in the Inverse Data Space (IDS) has its advantages like the task of removing the multiples simply becomes muting the zero offset and zero time data in the inverse domain. Calculation of the Inverse Data Space by sparse inversion techniques has seen mitigation of some artifacts. We reformulate the problem by taking advantage of some of the developments from the field of Compressive Sensing. The seismic data is compressed at the sensor level by recording projections of the traces. We then process this compressed data directly to estimate the inverse data space. Due to the smaller number of data set we also gain in terms of computational complexity.
Conference/Event name74th EAGE Conference and Exhibition incorporating EUROPEC 2012