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"ABSTRACTTo define reservoir potential or to have a better understanding of reservoircharacterization become the most important part to get many subsurface information.It will be very useful to analyze and prospect new candidates. Reservoircharacterization combined with the formation evaluation data between vertical andhorizontal dimensions will produce a geologic model, which is used as an input forreservoir simulation.The objectives of this research is to develop a reservoir model within the producinginterval of interest defined as horizons ?E? where it plays as a main oil target. It is apart of the Salemba Field, Kutai Basin, East Kalimantan.A geostatistical method used for the study was stochastic since the data setavailability is good. But to have better self confidence, a glance of deterministicmethod was applied to see how the differences. There are three kind of stochasticmethod will try for facies modeling, there are: Object-base Modeling, FaciesTransition and Sequential Indicator Simulation. Each method was varied usingexponential types of variogram, which is considered as the best match use in MutiaraField.By using the existing software, it resulted more than 10 good scenarios andrealizations of geological model generated for this study. Also the criterion of themain ranking will use the OOIP and OGIP. The result also was calibrated withcurrent condition, cumulative production and recovery factor to see the remainingreserves."

"Suatu model persebaran litofasies sangat penting dalam proses karakterisasi reservoar. Dengan adanya model kita dapat memperhitungkan nilai keekonomian dari reservoar tersebut termasuk menyusun program pengembangan reservoar selanjutnya, serta dapat pula menjadi masukan sebagai model statik dalam proses simulasi resevoar. Dua metode geostatistik dalam memodelkan fasies telah dilakukan dalam penelitian ini yaitu, sequential indicator simulation dan truncated gaussian simulation. Kedua metode tersebut menggunakan analisa model variogram, namun truncated gaussian simulation memperhitungkan konsep model pengendapan litofasies sementara sequential indicator simulation tidak memperhitungkan konsep tersebut. Untuk memodelkan porositas zona reservoar digunakan metode sequential gaussian simulation. Atribut impedansi akustik digunakan sebagai konstrain dalam setiap pemodelan. Dari hasil penelitian disimpulkan bahwa apabila data sumur yang tersedia terbatas dan pemodelan dikonstrain oleh atribut impedansi akustik, metode truncated gaussian simulation lebih baik dalam memetakan persebaran litofasies dibandingkan dengan metode sequential indicator simulation.

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A model of lithofasies distribution is very important in the process of reservoar characterization. By using this model, we can calculate the economic value of the reservoar. It also can be used as an input static model for reservoar simulation. Two methods of geostatistics stochastic in facies modeling have been done in this research, sequential indicator simulation and truncated gaussian simulation. Both of methods use the variogram model analysis, however truncated gaussian simulation consider the concept of depositional models of lithofasies while sequential indicator simulation not. Sequential gaussian simulation method has been used to model the reservoar porosity zone. Every modelling process use acoustic impedance attribute as litofasies constrain. The study concluded that if the well data is sparse and acoustic impedance has been used as constrain, truncated gaussian method will produced a better model than sequential indicator method."