A Data-Driven Method to Reconstruct Reservoir Flow Field

doi:10.7657/XJPG20230512

Abstract

Abstract:

The production stabilization and water-cut control of multilayer clastic reservoirs have always been a hot topic in oilfield development. At the medium-high water-cut development stage, oilfields usually exhibit obvious decline of production, scattered distribution of remaining oil, and prominent development conflicts between layers. For these oilfields, there is an urgent need for appropriate optimization and control methods to achieve sustained and stable production. Based on the Bayesian posterior probability method and reservoir streamline simulator, by applying a random maximum likelihood function, the history matching problem was solved and a space data set was constructed. Furthermore, by using finite-memory quasi-Newton gradient method, the data space set was inverted to predict the future. The transient flow velocity of the reservoir flow field was characterized by integrating Pollock streamline tracing method. Thus, a reservoir flow field reconstruction method based on data space inversion was proposed. This method allows real-time optimization of the reservoir injection-production parameters without the need for complex and repetitive calculations. It overcomes the limitations of traditional optimization methods in finely describing flow field evolution and fills the gap in the application of data space inversion in flow field optimization. Taking reservoir B in the Bohai oilfield as an example, the proposed method was used to reveal the mechanism of the reservoir injection-production structure optimization and intuitively demonstrate the process of reservoir flow field optimization. The field application results show that the overall water cut of the reservoir is relatively steady, the scattered remaining oil in the target flooding unit is effectively exploited, and the swept area of water flooding expands by 24.85%, indicating a remarkable flow field control effect. These digitalization efforts for reservoirs will provide valuable reference for the development and data-driven flow field control of similar medium-high water-cut oilfields.

Key words: medium-high water cut, data-driven, flow field characterization, production stabilization and water cut control, reconstruction method, data space inversion, streamline simulator

CLC Number:

TE341

FENG Gaocheng, LI Jinman, LIU Yuming, YIN Yanjun, WEI Zhiyong, ZHANG Qiang, MENG Fankun. A Data-Driven Method to Reconstruct Reservoir Flow Field[J]. Xinjiang Petroleum Geology, 2023, 44(5): 598-607.

Figures/Tables 9

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