Xinjiang Petroleum Geology ›› 2021, Vol. 42 ›› Issue (5): 584-591.doi: 10.7657/XJPG20210511

• RESERVOIR ENGINEERING • Previous Articles     Next Articles

Injection-Production Optimization of Carbonate Oil Reservoirs Based on a Well Connectivity Model

LEI Sheng1(), ZHOU Yuhui1(), WANG Ning2a, Saierjiang AHATI2b, ZHENG Qiang2a, SHENG Guanglong1   

  1. 1. School of Petroleum Engineering, Yangtze University, Wuhan, Hubei 430100, China
    2. PetroChina Xinjiang Oilfield Company, a.Research Institute of Exploration and Development; b.Baikouquan Oil Production Plant, Karamay, Xinjiang 834000, China
  • Received:2020-09-09 Revised:2020-11-09 Online:2021-10-01 Published:2021-09-28
  • Contact: ZHOU Yuhui E-mail:779644318@qq.com;zhyhtree@163.com

Abstract:

Carbonate oil reservoirs are very heterogeneous, so that injected water is easy to advance through high-permeability channels, and results in water channeling or flooding, and consequently fast rising water cut and low development effeciency in production wells. Based on the principle of well connectivity, and considering the geological features and development performance of fractured-vuggy carbonate oil reservoirs, parameters of well connectivity (conductivity and connected volume) were quantitatively characterized, then a vertical multi-layer well connectivity model was established, and parameters such as plane splitting coefficient and utilization rate of injected water were estimated for each layer of the oil reservoirs, and finally by using automatic history matching method and production optimization algorithm, real-time optimization and prediction of production performance of oil and water wells were realized. Field application has proved that the yearly incremental oil production is 1.1×104 m3 by using this method and good effect has been obtained. The method has important guiding significance for efficient development of similar oil reservoirs.

Key words: carbonate oil reservoir, well connectivity, conductivity, utilization rate of injected water, injection-production optimization

CLC Number: