基于多次数据吸收集合平滑算法的自动油藏历史拟合研究

doi:10.3969/j.issn.1006-6535.2021.03.015

特种油气藏 ›› 2021, Vol. 28 ›› Issue (3): 99-105.DOI: 10.3969/j.issn.1006-6535.2021.03.015

基于多次数据吸收集合平滑算法的自动油藏历史拟合研究

王泽龙^1,2,3, 刘先贵^1,2,4, 唐海发⁴, 吕志凯⁴, 刘群明⁴

1.中国科学院大学,北京 100049;
2.中国科学院大学渗流流体力学研究所, 河北廊坊 065007;
3.中国石油国际勘探开发有限公司,北京 100034;
4.中国石油勘探开发研究院,北京 100083

收稿日期:2020-12-28 修回日期:2021-03-08 出版日期:2021-06-25 发布日期:2022-02-16
通讯作者: 刘先贵(1963—),男,教授级高级工程师,1982年毕业于大庆石油学院采油工程专业,1985年毕业于中国科学院兰州渗流力学室流体力学专业,获硕士学位,现主要从事油藏渗流理论、数值模拟及提高采收率等方面研究工作。
作者简介:王泽龙(1989—),男,工程师,2012年毕业于西南石油大学油气储运工程专业,现为中国科学院大学渗流流体力学专业在读博士研究生,主要从事油气田开发与规划研究工作。
基金资助:
国家科技重大专项“页岩气气藏工程及采气工艺技术”(2017ZX05037-001)

Study on Automatic Reservoir History Matching Based on ES-MDA Algorithm

Wang Zelong^1,2,3, Liu Xiangui^1,2,4, Tang Haifa⁴, Lyu Zhikai⁴, Liu Qunming⁴

1. University of Chinese Academy of Sciences, Beijing 100049, China;
2. Institute of Porous Flow and Fluid Mechanics, University of Chinese Academy of Sciences, Langfang, Hebei 065007, China;
3. China National Oil and Gas Exploration and Development Co., Ltd., Beijing 100034, China;
4. Research Institute of Petroleum Exploration & Development, Beijing 100083, China

Received:2020-12-28 Revised:2021-03-08 Online:2021-06-25 Published:2022-02-16

摘要/Abstract

摘要： 针对常见历史拟合方法存在计算量大、油藏参数更新异常、油藏模型修正失真等问题。采用集合平滑算法,通过引入集合卡尔曼滤波算法(EnKF)中多次迭代思路,对相同数据重复吸收,推导出多次数据吸收集合平滑算法(ES-MDA)的核心公式,并编写了自动油藏历史拟合软件。以北海布伦特油田海相砂岩油藏为例,将基于ES-MDA算法的油藏自动历史拟合程序应用于该油藏,对油田的注水采油开发进行历史拟合。结果表明:油藏数值模拟的预测数据与实际测量的数据匹配程度达到90%以上,且能够较准确地表征真实油藏的孔隙度分布特征;ES-MDA算法具有算法稳定、运行效率高、模型更新准确等优点。研究成果对实现计算机自动油藏历史拟合,实时优化油藏生产具有重要意义。

关键词: 历史拟合, 数学模型, 模拟算法, 数据吸收, 集合平滑, 集合卡尔曼滤波

Abstract: To address the shortcomings of common history matching methods such as large amounts of computation, abnormal update of reservoir parameters, and distortion of reservoir model corrections, ensemble smoother algorithm was adopted to repeatedly assimilate the same data by multiple iterations in the ensemble Kalman filter (EnKF) algorithm to derive the core formula of the ES-MDA algorithm (ensemble smoother with multiple data assimilations) and write automatic reservoir history matching software. In a case study of marine sandstone reservoir of Brent Oilfield in the North Sea, the automatic history matching program of the reservoir based on the ES-MDA was applied to the reservoir to conduct history matching for water injection, oil production and development of the oilfield. The results showed that the predicted data obtained from the numerical modeling of the reservoir matched the actual measured data by more than 90%, and characterized the porosity distribution of the real reservoir more accurately. The ES-MDA algorithm is advantaged by stable algorithm, high operation efficiency and accurate model updating. The research results are of great significance for realizing computer-based automatic reservoir history matching and real-time optimization of reservoir production.

Key words: history matching, mathematical model, simulation algorithm, data assimilation, ensemble smoother, ensemble Kalman filter

中图分类号:

TE319

王泽龙, 刘先贵, 唐海发, 吕志凯, 刘群明. 基于多次数据吸收集合平滑算法的自动油藏历史拟合研究[J]. 特种油气藏, 2021, 28(3): 99-105.

Wang Zelong, Liu Xiangui, Tang Haifa, Lyu Zhikai, Liu Qunming. Study on Automatic Reservoir History Matching Based on ES-MDA Algorithm[J]. Special Oil & Gas Reservoirs, 2021, 28(3): 99-105.

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基于多次数据吸收集合平滑算法的自动油藏历史拟合研究

Study on Automatic Reservoir History Matching Based on ES-MDA Algorithm

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