@inproceedings{scholars8218,
             doi = {10.1088/1755-1315/88/1/012001},
          volume = {88},
            note = {cited By 2; Conference of 5th International Conferences on Geological, Geographical, Aerospaces and Earth Sciences 2017, AeroEarth 2017 ; Conference Date: 20 May 2017 Through 21 May 2017; Conference Code:131444},
          number = {1},
           title = {Characterizing Geological Facies using Seismic Waveform Classification in Sarawak Basin},
            year = {2017},
         journal = {IOP Conference Series: Earth and Environmental Science},
       publisher = {Institute of Physics Publishing},
        keywords = {Deposition; Earth sciences; Gas industry; Geology; Lithology; Petroleum prospecting; Petroleum reservoirs; Seismic waves; Seismographs; Stratigraphy; Waveform analysis, Depositional environment; Exploration and productions; Geological facies; Oil and Gas Industry; Productivity enhancement; Seismic facies classification; Seismic inversion; Seismic waveforms, Seismology},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033220465&doi=10.1088\%2f1755-1315\%2f88\%2f1\%2f012001&partnerID=40&md5=25dfc7cd35727e1be4c157ca84ef72fa},
        abstract = {Numerous effort have been made to build relationship between geology and geophysics using different techniques throughout the years. The integration of these two most important data in oil and gas industry can be used to reduce uncertainty in exploration and production especially for reservoir productivity enhancement and stratigraphic identification. This paper is focusing on seismic waveform classification to different classes using neural network and to link them according to the geological facies which are established using the knowledge on lithology and log motif of well data. Seismic inversion is used as the input for the neural network to act as the direct lithology indicator reducing dependency on well calibration. The interpretation of seismic facies classification map provides a better understanding towards the lithology distribution, depositional environment and help to identify significant reservoir rock. {\^A}{\copyright} Published under licence by IOP Publishing Ltd.},
            issn = {17551307},
          author = {Zahraa, A. and Zailani, A. and Ghosh, D. P.}
}