EVALUATION AND PRODUCTION PERFORMANCE PREDICTION METHOD FOR BROWNFIELDS APPLICATION

• Main Author: Irawan (NIM 22205003), Dedy
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/5922
• Institution: Institut Teknologi Bandung

ABSTRACT: <br /> <br /> <br /> <br /> <br /> Water drive and water flooding are driving mechanism and production improvement methods that frequently utilized in oil field development. The mechanisms in these processes are identified as immiscible displacement by means there are no interaction between displacing and displaced fluids (water and oil) in their movement. <br /> <br /> <br /> <br /> <br /> Nowadays most of oil production especially in Indonesia comes from mature fields or Brownfields since the difficulties in founding new ones. The characteristics of the Brownfield are declining in oil production and reservoir pressure, but on the other hand this field has an abundant of data, especially production history. The production history data is very useful and can be used to characterize the reservoir and to predict the production performance. <br /> <br /> <br /> <br /> <br /> Several production performance methods had been used by the oil industry, they are: Decline Curve Analysis, Water Oil Ratio plot as a function of cumulative oil production and Cut Cum Plot or X Plot (plotting water cut function namely X as a function of oil cumulative production). In this thesis a new performance prediction method is developed to improve the existing method for better performance prediction quality. <br /> <br /> <br /> <br /> <br /> Numerical simulation model was used to evaluate the effect of reservoir characteristics and production operation to the production performance behavior. A new simple and applicative performance prediction method of the well under water drive reservoir or water flooding process was developed based on reservoir simulation results. This method is based on a linear relationship of cumulative WOR (Wp/Np) as a function of time and cumulative WOR as a function of cumulative liquid. <br /> <br /> <br /> <br /> <br /> Application of the proposed method using actual production data demonstrates good results, which oil and water production can be simultaneously predicted. The proposed method can to be also used when different production operation scenarios were employed.