@article{scholars14962,
            year = {2021},
       publisher = {Geological Society of Malaysia},
         journal = {Bulletin of the Geological Society of Malaysia},
           pages = {149--157},
            note = {cited By 0},
          volume = {71},
             doi = {10.7186/bgsm71202113},
           title = {A new method to estimate resistivity distribution of shaly sand reservoirs using new seismic attributes},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85108946869&doi=10.7186\%2fbgsm71202113&partnerID=40&md5=904088bd7fb02cb015f7e331efd68520},
        abstract = {A subsurface resistivity model is important in hydrocarbon exploration primarily in the controlled-source electromagnetic (CSEM) method. CSEM forward modelling workflow uses resistivity model as the main input in feasibility studies and inversion process. The task of building a shaly sand resistivity model becomes more complex than clean sand due to the presence of a shale matrix. In this paper, a new approach is introduced to model a robust resistivity property of shaly sand reservoirs. A volume of seismic data and three wells located in the K-field of offshore Sarawak is provided for this study. Two new seismic attributes derived from seismic attenuation property called SQp and SQs are used as main inputs to predict the volume of shale, effective porosity, and water saturation before resistivity estimation. SQp attribute has a similar response to gamma-ray indicating the lithological variation and SQs attribute is identical to resistivity as an indicator to reservoir fluids. The petrophysical predictions are performed by solving the mathematical step-wise regression between the seismic multi-attributes and predicted petrophysical properties at the well locations. Subsequently, resistivity values are estimated using the Poupon-Leveaux (Indonesia) equation, an improvised model from Archie{\^a}??s to derive the mathematical relationship of shaly sand{\^a}??s resistivity to the volume and resistivity of clay matrix in shaly sand reservoirs. The resistivity modeled from the predicted petrophysical properties distributed consistently with sand distribution delineated from SQp attribute mainly in southeast, northeast, and west regions. The gas distribution of the net sand modeled by 5 and 90 of gas saturation scenarios also changed correspondingly to SQs attribute anomaly indicating the consistent fluid distribution between the modeled resistivity and SQs attribute. {\^A}{\copyright} 2021 Geological Society of Malaysia. All rights reserved.},
            issn = {01266187},
          author = {Salleh, N. F. and Hermana, M. and Ghosh, D. P.}
}