@inproceedings{scholars10068,
             doi = {10.1190/segam2018-2986106.1},
            year = {2018},
            note = {cited By 0; Conference of Society of Exploration Geophysicists International Exposition and 88th Annual Meeting, SEG 2018 ; Conference Date: 14 October 2018 Through 19 October 2018; Conference Code:175271},
           pages = {3105--3109},
           title = {Improvised Approach Using SQp-SQs Attributes for Hydrocarbon Prediction: A Field Case Study in Malay Basin},
         journal = {SEG Technical Program Expanded Abstracts},
       publisher = {Society of Exploration Geophysicists},
        keywords = {Electric logging; Gamma rays; Hydrocarbons; Oil well logging; Petroleum reservoir evaluation, Case-studies; Data coverage; Electromagnetic data; Higher hydrocarbons; Hydrocarbon distribution; Hydrocarbon predictions; Hydrocarbon reservoir; Hydrocarbon saturation; Malay Basin; Seismic attenuation, Lithology},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121841013&doi=10.1190\%2fsegam2018-2986106.1&partnerID=40&md5=c67895ae62dc6059e4ca3d3f739b5173},
        abstract = {Identification of areas with high hydrocarbon distribution within a field can be achieved if the field has electromagnetic data coverage. However, it is not the case for Field A which has led to the study of determining an improvised approach to achieve the purpose. SQp and SQs attributes which are formulated from seismic-attenuation rock physics were applied to Field A for hydrocarbon distribution prediction. These attributes can be computed with Vp/Vs and density parameters that can be achieved through elastic inversion. From the well logs, the SQp attribute response has some association with gamma ray whereas the SQs attribute resembles the resistivity log. This allow the attributes to be utilized as the lithology and fluid indicators. The results show that the SQp-SQs cross-plot provides good demarcation in delineating the sand, silt and clay. Besides that, the cross-plot also allows hydrocarbon reservoirs to be interpreted and increasing SQs values are corresponding to increasing hydrocarbon saturation. The extracted SQp maps from the channel reservoir zones show the sand distribution at the area of interest. It is observed that within the channel features, the SQp values are typically low (sand dominant), whereas within the flood plain region, it indicated high SQp values (mud dominant). The SQs maps show that high SQs values are related to high hydrocarbon saturation region (potential of more than 60) based on the analysis from the SQp-SQs cross-plot whereas low SQs values are corresponding to high water saturation distribution. The application of SQp and SQs attributes in Field A helps to enhance visualization in terms of lithology and fluid distribution. The SQs attribute can be used as a tool for indicating hydrocarbon reservoir. It may also be utilized to detect the high hydrocarbon saturation area which is essential for economical evaluation and well planning. {\^A}{\copyright} 2018 SEG},
            issn = {10523812},
          author = {Lew, C. L. and Hermana, M. and Ghosh, D. P.}
}