Hydrocarbon Reservoir Characterization of ‘Y’ Field in Kutai Basin East Kalimantan Using Artificial Neural Network Method

Abstract

The Kutai Basin in East Kalimantan is one of the largest oil and gas production areas in Indonesia. However, because the area has quite complex geology, the distribution of sandstone reservoirs in this area tends to be random. In the ‘Y’ field there are two wells named TU-1 and TS-1. The presence of gas-type hydrocarbon was shown in the TU-1 well while TS-1 well is a dry well. For this reason, the volume of rock properties were distributed to predict the presence and distribution of sandstones that have the potential to become hydrocarbon reservoirs. This study uses artificial neural network method with seismic attribute volumes, such as instantaneous amplitude, instantaneous phase, and instantaneous frequency, and also acoustic impedance inversion as the input. The volume of rock properties that were successfully predicted by the neural network were density, P-wave velocity, and effective porosity. From this volume, there is one horizon that becomes an interesting area because it has an area that indicates a hydrocarbon reservoir, that is Late Miocene horizon. Its properties have density value range from 2.1 - 2.25 gr/cc, P-wave velocity value ranges from 1800 - 2500 m/s, and effective porosity value ranges from 10 - 15%.