新疆石油地质 ›› 2009, Vol. 30 ›› Issue (5): 658-660.

• 讨论与争鸣 • 上一篇    下一篇

两种求解广义翁氏模型方法的对比

赵林1, 冯连勇1, 陆祥安1, 童晓光1,2   

  1. 1.中国石油大学 石油天然气工程学院,北京 102249;
    2.中国石油天然气勘探开发公司,北京 100083
  • 收稿日期:2008-11-05 修回日期:2009-02-23 出版日期:2009-10-01 发布日期:2020-09-30
  • 作者简介:赵 林(1982-),男,江苏江都人,在读博士研究生,石油工程管理, (Tel)010-89731752(E-mail)zhaolin@yahoo.cn.
  • 基金资助:
    国家自然科学基金项目,国际能源价格波动背景下国家能源价格调控策略研究(70841024)资助

Comparison of Two Methods for Generalized Weng Model

ZHAO Lin1, FENG Lian-yong1, LU Xiang-an1, TONG Xiao-guang1,2   

  1. 1.Institute of Oil-Gas Engineering, Ching University of Petroleum, Beijing 102249, China;
    2.China National Oil and Gas Exploration and Production Corporation, Beijing 100083, China
  • Received:2008-11-05 Revised:2009-02-23 Online:2009-10-01 Published:2020-09-30

摘要: 广义翁氏模型是石油产量预测的基础模型之一。陈元千教授首次提出的求解广义翁氏模型的线性迭代试差法,提出一种新求解方法,以辽河油田为例,对比了两种方法的求解过程及计算结果,分析了两种方法的优缺点。结果表明,原线性迭代试差法在求解模型时,需要用计算机软件模拟参数 b 的取值,然后选择一个判断标准来寻找最优的b 值,但在回归段的选择上比较直观,新方法通过二元回归可以直接求出参数 b,但在回归段的选择没有原方法直观。两种方法并不存在根本性差异,各有优劣,在实践应用中可互为补充。

关键词: 产量, 预测, 模型, 方法

Abstract: To solve generalized Weng model is one of fundamental problems for petroleum production prediction. This paper traces back the origin of petroleum production prediction problem, reviews the initial linear iterative try and error method proposed firstly by Dr. Chen Yuan-qian, and presents a new method for solving this model. Taking Liaohe oilfield as an example, the solving process and results of two methods are compared, and the advantage and disadvantage of each method are analyzed. The case study shows that in the initial linear iterative try and error method, parameter b needs to be simulated with the software, selecting a judgment criteria to find the optimal value, and it is intuitive to select regression data; while in this new method, the optimal value of parameter b can be found directly by multiple regression, but it is less intuitive to select regression data. The two methods have individual advantage and disadvantage without any essential difference, which can complement each other in practice.

Key words: production rate, prediction, forecast, model, method

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