@inproceedings{scholars973,
         address = {Islamabad},
           title = {Singularity spectrum analysis of windowed seismograms},
         journal = {Proceedings of the 8th International Conference on Frontiers of Information Technology, FIT'10},
            note = {cited By 2; Conference of 8th International Conference on Frontiers of Information Technology, FIT'10 ; Conference Date: 21 December 2010 Through 23 December 2010; Conference Code:84130},
             doi = {10.1145/1943628.1943647},
            year = {2010},
          author = {Khan, M. M. and Hani, A. F. M.},
            isbn = {9781450303422},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79952581627&doi=10.1145\%2f1943628.1943647&partnerID=40&md5=1cd324a7c63e1db5e2490e88312f5651},
        keywords = {Alternative methods; Correlation dimensions; Cost saving; Elastic properties; Energy peaks; Exploration and productions; Extraction of information; Hydrocarbon detection; Hydrocarbon exploration; Seismic; Seismic datas; Sensing techniques; Signal processing algorithms; Singularity Spectrum; Spectral decomposition; Well location, Discrete wavelet transforms; Geological surveys; Hydrocarbons; Information technology; Interferometry; Petroleum prospecting; Remote sensing; Seismic response; Seismic waves; Signal processing; Spectrum analysis, Hydrocarbon refining},
        abstract = {Seismic, is one of the extensively exploited hydrocarbon exploration tools. It is a remote-sensing technique that takes advantage of the elastic properties of the formations. For effective hydrocarbon exploration maximum possible extraction of information from seismic data set is required which is dependent heavily on signal processing algorithms e.g spectral decomposition mechanisms. Improvements in such methods is significant as inaccurate interpretation leads to invalid well locations (dry wells/water wells) which is a great loss of money (approx 25 million USD). Singularity Spectrum analysis of the seismic data using the windowing concept is proposed and is applied on real seismic data. It is found that the energy peaks of the singularity spectral attributes namely width, correlation dimension, {\^I}{$\pm$}peak and asymmetry within these windows indicates hydrocarbon zones. The development of a windowed singularity spectrum on seismic data for direct hydrocarbon detection is not only an alternative method but an efficient and cost saving technology in exploration and production. Copyright {\^A}{\copyright} 2010 ACM.}
}