Korelasi Data Log Sumur dan Seismik untuk Penyebaran Litologi dan Porositas Reservoir Hidrokarbon Formasi Gumai Cekungan Sumatera Selatan
Timur Dikman, Adi Susilo, Said Sabbeq
Abstract
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Timur Dikman, Adi Susilo, Said Sabbeq
Abstract
Open-access reader
Integration of seismic data and well log is carried on the field X to identify the distribution of lithology and porosity in the reservoir target zone in this field. With the purpose to get a good interpretation of the subsurface in the process of hydrocarbon exploration. The integration of data is done by using acoustic impedance inversion analysis. Two types of acoustic impedance inversion method is applied to the well log data and seismic, i.e maximum likelihood sparse spike and a model-based inversion. Both of them have a high correlation coefficient and a low error rate. Sparse spike inversion result was selected to use in the next process as it has an acoustic impedance value that is more similar to the well log acoustic impedance value. Acoustic impedance models correlated with the lithological profiles of well log is used to predict the spread of reservoir lithology. Sparse spike inversion results are then used as input to the module EMERGE on Hampson Russell Suite 9 software, to predict the distribution of porosity from seismic volume. The volume of porosity is determined from regression function crossplot between acoustic impedance inversion results with fixed porosity well logs.
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Integration of seismic data and well log is carried on the field X to identify the distribution of lithology and porosity in the reservoir target zone in this field. With the purpose to get a good interpretation of the subsurface in the process of hydrocarbon exploration. The integration of data is done by using acoustic impedance inversion analysis. Two types of acoustic impedance inversion method is applied to the well log data and seismic, i.e maximum likelihood sparse spike and a model-based inversion. Both of them have a high correlation coefficient and a low error rate. Sparse spike inversion result was selected to use in the next process as it has an acoustic impedance value that is more similar to the well log acoustic impedance value. Acoustic impedance models correlated with the lithological profiles of well log is used to predict the spread of reservoir lithology. Sparse spike inversion results are then used as input to the module EMERGE on Hampson Russell Suite 9 software, to predict the distribution of porosity from seismic volume. The volume of porosity is determined from regression function crossplot between acoustic impedance inversion results with fixed porosity well logs.
Key concepts: Geology, Lithology, Inversion (geology), Acoustic impedance, Seismic inversion, Porosity, Well logging, Electrical impedance