Forecasting oil production for Oligocene C sequence, X field, Cuu Long basin using logistic growth model

  • Affiliations:

    1 Hanoi University of Mining and Geology, Hanoi, Vietnam
    2 PetroVietnam University, Ba Ria - Vung Tau, Vietnam

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  • Received: 30th-Sept-2021
  • Revised: 12th-Jan-2022
  • Accepted: 5th-Mar-2022
  • Online: 30th-Apr-2022
Pages: 71 - 79
Views: 3577
Downloads: 2310
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Abstract:

Hydrocarbon production forecasting for the field lifetime in the short and long term is an important phase, the accuracy of this process plays a tremendous role in giving the decision of reasonable field management and development. In this article, the logistic growth models using the function MATLAB’s ‘nlinfit’ have been built to forecast oil production yield for the Oligocene C sequence, X field, Cuu Long basin. Thanks to the combination with the history matching process, the logistic growth model expressed high accuracy, the results of the model are very close to the actual production data with a relative error of 1,85%. The article analyzed and evaluated the production parameters of wells obtained when building logistic growth models such as the time at which half of the carrying capacity has been produced, the steepness of the decline of the rate, and the production rate of the wells at the forecast time. Without applying any improved oil recovery method, the decline of the rate of all wells approaches 100 bbl/d before reaching the validity period of the oil and gas contract. This is the basis for operators to establish and improve field development plans.

How to Cite
Bui, N.Thi, Le, A.Ngoc, Nguyen, M.Duy, Nguyen, H.Minh and , . 2022. Forecasting oil production for Oligocene C sequence, X field, Cuu Long basin using logistic growth model (in Vietnamese). Journal of Mining and Earth Sciences. 63, 2 (Apr, 2022), 71-79. DOI:https://doi.org/10.46326/JMES.2022.63(2).07.
References

Arps, J.J. (1945). Analysis of Decline Curves. AIME, Vol. 160, pp. 228-247.

Campbell, C.J. (1997). The coming oil crisis. Brentwood, Essex, UK: Multi-Science Publishing; and Dublin, Republic of Ireland: Petroconsultants.

Campbell, C.J., Heapes, S. (2008). An atlas of oil and gas depletion. Huddersfield, UK: Jeremy Mills Publishing. 

Clark, A.J., Lake, L.W., Patzek, T.W. (2011). Production forecasting with Logistic Growth Models. SPE Annual Technical Conference and Exhibition, Denver, Colorado, USA, 30 October - 2 November.

Juvkam-Wold, H.C., Dessler, A.J. (2009). Using the Hubbert equation to estimate oil reserves. World Oil, Vol. 230, No. 4. 

Hubbert, M.K. (1956). Nuclear energy and fossil fuels. In Meeting of the Southern District, Division of Production, American Petroleum Institute, San Antonio, TX, USA, 7–9 March 1956. San Antonio, TX: Shell Development Company.

Hubbert, M.K. (1982). Techniques of prediction as applied to the production of oil and gas. In Proc. Symp. on Oil and Gas Supply Modeling, Washington, DC, USA, 18–20 June 1980. NBS Spec. Publ. No. 631, pp. 16-141. Washington, DC: US Department of Commerce.

Laherrefre, J. (2000). Learn strengths, weaknesses to understand Hubbert curve. Oil and Gas Journal, Vol. 98, No. 16, pp. 63-76. 

Laherrefre, J. (2002). Modeling future liquids production from extrapolation of the past and from ultimates. Energy exploration and exploitation, Vol. 20, No. 6, pp. 457-479. 

Laherrefre, J. (2004). Oil and natural gas resource assessment: production growth cycle models. In Encyclopaedia of energy (ed. CJ Cleveland). Elsevier, Amsterdam, pp. 617-631.

Mohr, S., Evans, G. (2008). Peak oil: testing Hubbert’s curve via theoretical modeling. Natural Resources Research Vol. 17, No. 1, pp. 1-11. 

Nashawi, I.S., Malallah, A., Al-Bisharah, M. (2010). Forecasting world crude oil production using multi-cyclic Hubbert model. Energy Fuels, Vol. 24, pp. 1788-1800. 

Nguyen, V.H., Le, P.N. (2019). Development of production-forecasting models for oil and gas wells. Petrovietnam Journal, No. 8-2019, pp. 14-20. (in Vietnamese)

Sorrell, S., Speirs, J. (2014). Using growth curves to forecast regional resource recovery: approaches, analytics and consistency tests. Phil. Trans. R. Soc. A 372: 20120317.

Tsoularis, A., and Wallace, J. (2002). Analysis of logistic growth models. Mathematical Biosciences, Vol.179, No. 1, pp. 21-55.

Tran, D.T., Dinh, D.H., Tran, X.Q., Pham, T.G., Le, V.Q., Le, T.H., Le, Q.T., Tran, N.L. (2019). Research on applied logistic growth model to forecast production for lower miocene, Bach Ho field. Petrovietnam Journal, No. 9-2019, pp. 16-22. (in Vietnamese)

Verhulst, P.F. (1838). Notice sur la loi que la population suit dans son accroissement, Correspondance mathématique et physique, Vol. 10, pp. 113-121.