@inproceedings{scholars6665,
           title = {Modeling shales and marls reflections by autoregression method},
         journal = {AIP Conference Proceedings},
       publisher = {American Institute of Physics Inc.},
             doi = {10.1063/1.4968165},
            year = {2016},
            note = {cited By 0; Conference of 4th International Conference on Fundamental and Applied Sciences, ICFAS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125141},
          volume = {1787},
          author = {Malik, U. and Ching, D. L. C. and Daud, H. and Januarisma, V.},
            issn = {0094243X},
            isbn = {9780735414518},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85005950686&doi=10.1063\%2f1.4968165&partnerID=40&md5=d714c27ac5d29a4124af09e355edb3c1},
        abstract = {Seismic modeling is pervasive in exploring the subsurface structure. The propagation of elastic waves in homogenous medium has to be modeled to create synthetic seismograms. A numerical solution of partial differential equations describes the propagation phenomenon in elastic medium under the initial and boundary condition that is Clayton Engquist (CE). The subsurface discontinuities like fractures effect the seismic reflections that are used for subsurface imaging. A fractured velocity model with shales and marls sedimentary rocks is built and common depth point (CDP) seismograms with single shot are preprocessed by automatic gain control. The subsurface reflections are modeled by using the first-order autoregressive (AR(1)) model. A comparison of synthetic and real data AR model is made on the basis of average reflectivity, R2 and means square error (MSE). The real data has smaller average reflectivity, -1.80e-10, 93.966 explained variation i.e. R2 and 1.71e-07 minimum MSE. {\^A}{\copyright} 2016 Author(s).}
}