@inproceedings{scholars10625,
            year = {2018},
             doi = {10.4043/28241-ms},
            note = {cited By 0; Conference of Offshore Technology Conference Asia 2018, OTCA 2018 ; Conference Date: 20 March 2018 Through 23 March 2018; Conference Code:138192},
         journal = {Offshore Technology Conference Asia 2018, OTCA 2018},
       publisher = {Offshore Technology Conference},
           title = {Least-squares reverse time migration using generalised diffraction-stack imaging condition},
          author = {Moussavi Alashloo, S. Y. and Ghosh, D. and Bashir, Y.},
            isbn = {9781510862159},
        keywords = {Diffraction; Image enhancement; Inverse problems; Offshore oil well production; Offshore technology; Seismic prospecting, Anticline structure; Imaging conditions; Inversion process; Layered model; Least-squares inversion; REmove noise; Reverse time migrations; Wave-field continuation, Least squares approximations},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088202629&doi=10.4043\%2f28241-ms&partnerID=40&md5=7a8b92e8acf2a1459670d12687a2443e},
        abstract = {Reverse time migration (RTM) is a wavefield-continuation method which is accepted as the best migration method currently available for imaging complicated geology. RTM is defined as a reversal procedure of seismic wave propagation, but, conventional RTM does not formulate this reversal procedure as an inverse problem. This problem can be solved using least-squares migration (LSM). This paper presents developing RTM by utilizing least squares inversion process. A matrix-based least squares RTM (LSRTM) algorithm is studied by employing the generalized diffraction-stack migration method. A simple layered model with an anticline structure, and Marmousi model are used to monitor how LSRTM can improve the imaging of dip reflectors, steep dips and the pinch-out. The LSRTM method succeeded to image the flanks, remove noises and improve the resolution. Inversion process of least squares RTM was more efficient than conventional RTM to enhance the resolution of image, remove the artifacts, and correct the amplitude. {\^A}{\copyright} 2018, Offshore Technology Conference.}
}