Perpustakaan Digital ITB

The Arps Decline Curve Analysis is one of very powerful method that can be used to determine our reservoir performance because of it’s very simple and widely used in oil industry. However, the method contains a few demerits and one important demerit is the subjectivity in determining the slope of the line during the analysis which leads to uncertainty in EUR values. This means that the results may mislead even though the analysis appears to fits the most part of the real data.Looking forward to this demerit, the purpose of this paper is to reduce the uncertainty by providing guidelines for taking a slope on the Arps Decline Curve Analysis. The guidelines provided have to accomplish two main things, it has to be simple in use, and it has to be reliable.Author used numerous well from two types, i.e. carbonate reservoir and sandstone reservoir field data to accomplish the purpose of this paper, and the guidelines proposed are validated using field data and other sophisticated method including the Blasingame Decline Curve Analysis and Reservoir Simulation. Reservoir Simulation validation shows that the error between the reservoir simulation and the Arps Decline Curve Analysis is less than 1 %, thus, the guidelines are valid to be used.The guidelines have been produced and are able to improve the reliability of the Arps Decline Curve Analysis results. Moreover, this study also yields a relationship between the Blasingame Decline Curve Analysis and the Arps Decline Curve Analysis for the two types of the field. For the sandstone reservoir, the Arps Decline Curve forecast rate always below the Blasingame Decline Curve Forecast Rate. On the other hand, the Carbonate Reservoir, at high oil rate, the Blasingame Decline Curve forecast rate is higher than the Arps Decline Curve forecast rate, but at low oil rate, the Blasingame Decline Curve forecast rate is lower than the Arps Decline Curve forecast rate.