Study and apply the advanced analysis algorithm to screen the optimal enhanced oil recovery solution for oil and gas fields in Viet Nam

  • Affiliations:

    1 Vietnam Petroleum Institute, Hanoi, Vietnam 2 Vietnam Oil and Gas Group, Hanoi, Vietnam 3 Hanoi University of Mining and Geology, Hanoi, Vietnam

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  • Received: 18th-Feb-2021
  • Revised: 29th-May-2021
  • Accepted: 20th-June-2021
  • Online: 10th-July-2021
Pages: 17 - 29
Views: 2121
Downloads: 1032
Rating: 5.0, Total rating: 102
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Abstract:

Applying the methods of enhanced oil recovery (EOR) for oil and gas fields has always many risks of economic and technology because EOR projects are influenced by many characteristic factors of the reservoir such as structure of reservoir, reservoir formation, geological properties, parameters of reservoir engineering, production technology to EOR application. Some EOR methods have been successfully applied in the world, but when these methods conduct in specific reservoir with different geological characteristics, tight production conditions have resulted in failures and ineffective economic, even caused dreadful aftermath to be handled in operations. Researches, evaluations and EOR applications in Vietnam are limited and only carried out on a laboratory scale. Therefore, the ability to be applied the EOR modern technology with a large scale or full field still faces many difficulties and the feasibility of projects is not high enough. The authors have been analysed all EOR projects successfully that applied many oil and gas fields in the world and then building EOR database. Based on EOR database, a study has been conducted on statistical analysis to build EOR screening criteria for reservoir parameters from past to now. The study also combined in-depth analysis algorithms such as Fuzzy, K - mean, PCA Artificial Intelligence to screen the optimal EOR method for sandstone reservoirs of Cuu Long Basin.

How to Cite
Hoang, L., Trinh, T.Viet, Trieu, T.Hung, Nguyen, Q.Minh, Pham, N.Quy, Doan, H.Huy and Hoang, L. 2021. Study and apply the advanced analysis algorithm to screen the optimal enhanced oil recovery solution for oil and gas fields in Viet Nam (in Vietnamese). Journal of Mining and Earth Sciences. 62, 3a (Jul, 2021), 17-29. DOI:https://doi.org/10.46326/JMES.2021.62(3a).03.
References

Al - Adasani A., Bai B., (2010). Recent Developments and Updated Screening Criteria of Enhanced Oil Recovery Techniques. Society of Petroleum Engineers. 51 - 60.

Guerillot D. R., (1988). EOR Screening With an Expert System. Society of Petroleum Engineers 137 - 142.

Hoàng Long, (2021). Nghiên cứu lựa chọn các giải pháp công nghệ và thực nghiệm đánh giá các tác nhân nâng cao hệ số thu hồi dầu cho đối tượng trầm tích lục nguyên của các mỏ dầu thuộc bể Cửu Long. Đề tài Độc lập cấp Nhà nước của Bộ KHCN, mã số ĐT ĐLCN.26/19. Viện dầu khí Việt Nam.

Hoàng Long, (2020). Nghiên cứu xây dựng cơ sở dữ liệu của 200 dự án EOR trên thế giới và phần mềm chuyên ngành để đánh giá, lựa chọn các giải pháp nâng cao hệ số thu hồi dầu. Đề tài cấp Viện dầu khí Việt Nam, Mã số 5338.VDKVN.

Poettmann F. H., Hause,W. R., (1978). Micellar - Polymer Screening Criteria And Design. Society of Petroleum Engineers. 102 - 110.

Ramos. G. A. R., Akanji. L., (2017). Application of artificial intelligence for technical screening of enhanced oil recovery methods. Journal of Oil, Gas and Petrochemical Sciences. 57 - 64.

Siena Martina, Guadagnini Alberto, (2016). A Novel EOR Screening Approach based on Bayesian Clustering and Principal Component Analysis. SPE Res Eval and Eng 19 (03). 382-390.

Taber J. J., Martin, F. D., Seright, R. S., (1997). EOR Screening Criteria Revisited - Part 1: Introduction to Screening Criteria and Enhanced Recovery Field Projects. Society of Petroleum Engineers. 189-198.

Zhang Na, (2015). Steam flooding screening and EOR prediction by using clustering algorithm and data visualization. Masters Theses. 488p