Research Papers: Petroleum Engineering

Optimized Cyclic Water Injection Strategy for Oil Recovery in Low-Permeability Reservoirs

[+] Author and Article Information
Xiaofei Sun*, Yanyu Zhang, Mengke Xie, Hang Hu

School of Petroleum Engineering,
China University of Petroleum (East China),
Qingdao 266580, Shandong, China

Jie Wu

Downhole Service Company,
Shengli Petroleum Engineering Co., Ltd.
SINOPEC, Dongying 257000, Shandong, China

Contributed by the Petroleum Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received January 13, 2018; final manuscript received June 27, 2018; published online August 9, 2018. Assoc. Editor: Daoyong (Tony) Yang.

J. Energy Resour. Technol 141(1), 012905 (Aug 09, 2018) (13 pages) Paper No: JERT-18-1043; doi: 10.1115/1.4040751 History: Received January 13, 2018; Revised June 27, 2018

With the worldwide decline in conventional oil production, tremendous unconventional resources, such as low-permeability reservoirs, are becoming increasingly important. Cyclic water injection (CWI) as an oil recovery method has attracted increasing attention in the present environment of low oil prices. However, the optimal CWI strategy is difficult to determine for a mature oilfield due to the involvement of multiple wells with multiple operational parameters. Thus, our main focus in this paper is to present a novel and systematic approach to optimize CWI strategies by studying a typical low-permeability, namely, reservoir G21. To this end, a comprehensive method that combines the advantages of streamline simulation and fuzzy comprehensive evaluation (FCE) was proposed to identify water channeling in the reservoir. Second, the reliability of the method was verified using tracer tests. Finally, a new hybrid optimization algorithm, the simulated annealing-genetic algorithm (SAGA), coupled with a reservoir simulator was developed to determine an optimal CWI strategy for the low-permeability reservoir. The results show that the CWI technique is viable as a primary means in the present environment of low oil prices to improve the waterflood performance in low-permeability reservoirs. The oil recovery of the most efficient strategy increases by 6.8% compared to conventional waterflooding. The asymmetric CWI scheme is more efficient than the symmetric CWI scheme for the low-permeability reservoir.

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Fig. 1

The evaluation system for water channel identification

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Fig. 2

Reservoir model and permeability distribution: (a) structural model, (b) permeability distribution of layer Es24-3, and (c) permeability versus depth for the representative well

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Fig. 3

History match results of the (a) cumulative oil production, cumulative water production, and water cut, and (b) reservoir pressure

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Fig. 4

Streamline simulation results for the G21 reservoirs.

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Fig. 6

Tracer test results of well groups 1, 2, and 5

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Fig. 7

The distribution map of water channeling obtained by the comprehensive method and tracer tests

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Fig. 8

Flow chart of the SAGA algorithm

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Fig. 5

The evaluation results of the comprehensive method by combining the results of the FCE method and streamline simulations

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Fig. 9

Schematic diagram of the symmetric and asymmetric CWI schemes: (a) symmetric CWI scheme and (b) asymmetric CWI scheme

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Fig. 12

Comparison between optimized CWI schemes and conventional waterflooding in terms of oil recovery and water cut: (a) oil recovery and (b) water cut

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Fig. 13

The streamline distribution for both optimized CWI schemes after a ten year period: (a) symmetric CWI scheme and (b) asymmetric CWI scheme

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Fig. 10

The optimization processes of scheme 1: (a) average and highest oil recovery, (b) QL of producer G21-1, (c) Ti or TS of injector G21-2, (d) Qi of injector G21-2, and (e) Pi of injector G21-2

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Fig. 11

The optimization processes of scheme 2: (a) average and highest oil recovery, (b) QL of producer G21-1, (c) Ti of injector G21-2, (d) TS of injector G21-2, (e) Qi of injector G21-2, and (f) Pi of injector G21-2



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