基于数据驱动的油藏流场重构方法

doi:10.7657/XJPG20230512

摘要/Abstract

摘要：

多层碎屑岩油藏稳油控水一直是油田开发的热点问题，油田进入中—高含水期后产油量下降明显，平面剩余油分布零散，层间开发矛盾突出，迫切需要合适的优化调控方法使其持续稳产。根据贝叶斯后验概率方法与油藏流线模拟器，应用随机极大似然函数求解历史拟合问题并构建数据空间集，利用有限记忆的拟牛顿梯度方法来反演数据空间集与推测未来，综合Pollock流线追踪方法表征油藏流场的瞬时流动速度，提出了一种基于数据空间反演的油藏流场重构方法。此方法无需复杂重复的运算就可实现油藏注采参数的实时优化，突破了传统优化方法无法精细描述流场演变的局限性，弥补了数据空间反演在流场优化方面应用的空白。以渤海B油藏为例，利用基于数据空间反演的油藏流场重构方法，揭示了油藏注采结构优化的运行机理，直观展示了油藏流场优化的实现过程。现场调控结果显示，油藏综合含水率较为稳定，调控井组单元零散状剩余油被有效动用，水驱波及面积扩大24.85%，油藏流体疏导效果显著。这些油藏数字化探索与实践，将为同类中—高含水期油田开发与数据驱动油藏流场调控的应用提供借鉴。

关键词: 中—高含水期, 数据驱动, 流场表征, 稳油控水, 重构方法, 数据空间反演, 流线模拟器

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

中图分类号:

TE341

冯高城, 李金蔓, 刘玉明, 尹彦君, 魏志勇, 张强, 孟凡坤. 基于数据驱动的油藏流场重构方法[J]. 新疆石油地质, 2023, 44(5): 598-607.

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.

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