EGU2020-12089
https://doi.org/10.5194/egusphere-egu2020-12089
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Well location optimization of Zama reservoir using top down reservoir modeling(TDRM)

Taehun Lee, Kyungbook Lee, Hyunsuk Lee, and Wonsuk Lee
Taehun Lee et al.
  • KIGAM, Petroleum and Marine Research Division, Daejeon, Korea, Republic of (thlee@kigam.re.kr)

Artificial intelligence is applied in various fields of human life and is being actively studied and applied in the oil fields. Especially, the digital oil field, which has recently been spotlighted, is required to simulate the reservoir using artificial intelligence. However, there is almost little research to date. Therefore, in this study, we applied TDRM using artificial intelligence technology to Zama field located on the land of Canada. The required static and dynamic data were obtained from Accumap, a Canadian well information S/W. As a result, the reservoir model was constructed successfully and the well location optimization could be performed in a short time using TDRM.

How to cite: Lee, T., Lee, K., Lee, H., and Lee, W.: Well location optimization of Zama reservoir using top down reservoir modeling(TDRM), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12089, https://doi.org/10.5194/egusphere-egu2020-12089, 2020