The True Value of Data Integration to Discover Hidden Hydrocarbon Reservoir; A Successful Exploration Story from West Java Basin, Indonesia.

Abstract

For a few decades, West Java Basin, Indonesia has been known to be one of the most prolific hydrocarbons producing basins in Indonesia. Unfortunately, the hydrocarbon discovery in this area is getting harder from time to time. One of the reasons for this is because the main reservoirs here do not show prominent hydrocarbon indication on the standard open hole log. They appear in high GR, low contrast - low resistivity with limited to no N-D separation. Hence, these reservoirs were difficult to be identified. Pertamina EP as one of operators in this area managed to tackle this problem through implementing a new interpretation workflow that promote data integration. This workflow comprised of various advanced logging data, namely, magnetic resonance, dielectric, resistivity image log, formation tester and sidewall core data. On the early interpretation stage, the integration of magnetic resonance, dielectric and resistivity image log was used to help revealing hidden reservoir, differentiating pay zone from residual zone and maximizing the formation tester points selection. Later, the formation tester was used to reveal the formation and reservoir fluid type properties. Meanwhile, the actual reservoir rock samples were planned to be obtained through the sidewall core acquisition. This workflow was tested in one of Pertamina EP’s recent well, AMJ-001. It proved to be effective in unlocking the hidden reservoir in both sandstone / carbonate lithology. It was also learned that the potential hydrocarbon intervals in this well exhibits specific signature in the advanced log dataset. These intervals were indicated by magnetic resonance data that shows increasing in the porosity bin number 6 (100-300 ms) and porosity bin number 7 (300-1000 ms). In the image log, they were associated with the well sorted sandstone or vuggy limestone. Meanwhile the advanced formation tester was successfully obtained the pressure data and conclusive fluid analysis in these reservoir zones. By using this data integration, Pertamina EP was able to determine optimum DST intervals that eventually shows good hydrocarbon production rate. This case study indicates that data integration is critical in order to ensure the exploration success. It is encouraged to perform similar workflow in the other area that face similar reservoir characteristics.

AAPG Datapages/Search and Discovery Article #90354 © 2019 AAPG Asia Pacific Technical Symposium, The Art of Hydrocarbon Prediction: Managing Uncertainties, Bogor, (Greater Jakarta), Indonesia, August 7-8, 2019