多模型的油藏模拟自动历史拟合方法研究

doi:10.11885/j.issn.1674-5086.2020.11.10.01

西南石油大学学报(自然科学版) ›› 2022, Vol. 44 ›› Issue (6): 97-104.DOI: 10.11885/j.issn.1674-5086.2020.11.10.01

多模型的油藏模拟自动历史拟合方法研究

卢异¹, 胡浩², 成亚斌¹, 夏国朝³, 任光文¹

1. 中国石油大港油田勘探开发研究院, 天津滨海新区 300280;
2. 中海福陆重工有限公司, 广东珠海 519090;
3. 中国石油大港油田公司资源评价处, 天津滨海新区 300280

收稿日期:2020-11-10 发布日期:2023-01-16
通讯作者: 胡浩,E-mail:3292203482@qq.com
作者简介:卢异,1971年生,男,汉族,四川遂宁人,高级工程师,主要从事油藏评价及新区产能建设方面的研究。E-mail:dg_luyi@petrochina.com.cn
胡浩,1996年生,男,汉族,黑龙江双鸭山人,硕士,主要从事油气藏工程及数值模拟方面的研究工作。E-mail:3292203482@qq.com
成亚斌,1981年生,男,汉族,山西运城人,高级工程师,硕士,主要从事油气藏工程、数值模拟及储气库方案方面的研究工作。E-mail:chengybin@petrochina.com.cn
夏国朝,1974年生,男,汉族,江苏泰州人,高级工程师,博士,主要从事油气藏评价、油气藏工程等方面的研究和管理工作。E-mail:xiagchao@petrochina.com.cn
任光文,1986年生,男,汉族,天津静海人,工程师,硕士,主要从事油气藏地质方面的研究。E-mail:dg_rengwen@petrochina.com.cn
基金资助:
国家科技重大专项（2017ZX05013-005）

Research on Automatic History Matching Method Based on Multi Models

LU Yi¹, HU Hao², CHENG Yabin¹, XIA Guochao³, REN Guangwen¹

1. Exploration and Development Research Institute, Dagang Oilfield, PetroChina, Binhai New Area, Tianjin 300280, China;
2. COOEC-FLUOR Heavy Industries, Zhuhai, Guangdong 519090, China;
3. Department of Resource Evaluation, Dagang Oilfield, PetroChina, Binhai New Area, Tianjin 300280, China

Received:2020-11-10 Published:2023-01-16

摘要/Abstract

摘要： 传统油气藏数值模拟通常仅建立单个随机地质模型，采用人工历史拟合方式获得符合油藏动态的地质模型并用于方案预测。但由于地质资料相对稀少且地层非均质性的客观事实存在，历史拟合问题必然存在多解性，所获得的单个地质模型无法保证准确反映地下真实情况。本次研究中首先利用静态地质资料生产大量随机实现，使用PCA降维方法减少模型数据量，再利用聚类方法挑选出多个特征各异的实现作为初始模型，采用基于SPSA算法的自动历史拟合方法，获得多个符合油藏动态却又包含不同特征的历史拟合模型。结果表明，多模型能够更接近地下的真实情况，产生的预测结果不再是单一动态曲线，而是具有多种开发可能性的一系列曲线，这样使预测更为科学可靠。

关键词: 自动历史拟合, PCA降维, K中心点聚类, SPSA算法, 不确定性评价

Abstract: In traditional reservoir numerical simulation, only a single random geological model is established, and the artificial history fitting method is used to obtain the geological model that conforms to reservoir production history and is used for project prediction. However, due to the relative scarcity of geological data and the heterogeneity of reservoir, the historical fitting problem must have multiple solutions, and the single geological model obtained cannot guarantee the accurate reflection of the real underground situation. In the numerical simulation study in this research, static geological data are used to produce a large number of random implementations, PCA dimensionality reduction method is used to reduce the amount of model data, and then the clustering method is used to select a number of implementations with different characteristics as the initial model. The automatic history fitting method based on SPSA algorithm was used to obtain several historical fitting models which conform to reservoir dynamics but contain different characteristics. Multi models can reflect the real underground situation more completely, and the prediction result is no longer a single dynamic curve, but a series of curves with multiple development possibilities, making the prediction more scientific and reliable.

Key words: automatic history matching, PCA dimensionality reduction, K-medoids clustering, SPSA algorithm, uncertainty evaluation

中图分类号:

TE319

卢异, 胡浩, 成亚斌, 夏国朝, 任光文. 多模型的油藏模拟自动历史拟合方法研究[J]. 西南石油大学学报(自然科学版), 2022, 44(6): 97-104.

LU Yi, HU Hao, CHENG Yabin, XIA Guochao, REN Guangwen. Research on Automatic History Matching Method Based on Multi Models[J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2022, 44(6): 97-104.

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多模型的油藏模拟自动历史拟合方法研究

Research on Automatic History Matching Method Based on Multi Models

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