考虑油藏环境因素和微生物因子的微生物采油数学模型

doi:10.7623/syxb201904006

石油学报 ›› 2019, Vol. 40 ›› Issue (4): 448-456.DOI: 10.7623/syxb201904006

考虑油藏环境因素和微生物因子的微生物采油数学模型

王天源^1,2,3, 修建龙³, 黄立信³, 崔庆锋³, 马原栋³, 苗钧逸⁴, 俞理³

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. 中国石油勘探开发研究院河北廊坊 065007;
4. 长江大学石油工程学院湖北武汉 430071

收稿日期:2018-11-28 修回日期:2019-01-23 出版日期:2019-04-25 发布日期:2019-05-07
通讯作者: 俞理,男,1964年8月生,1987年获兰州大学学士学位,现为中国石油勘探开发研究院高级工程师,主要从事微生物提高采收率方面的工作。Email:yuli69@petrochina.com.cn
作者简介:王天源,男,1990年2月生,2016年获中国地质大学(武汉)学士学位,现为中国科学院大学渗流流体力学研究所博士研究生,主要从事微生物渗流方面的工作。Email:wangtiany123@126.com
基金资助:
中国石油天然气股份有限公司科学研究与技术开发项目"微生物驱油技术研究与应用"（2016B-1106）资助。

A mathematical model for microbial enhanced oil recovery considering reservoir environment and microbial factor

Wang Tianyuan^1,2,3, Xiu Jianlong³, Huang Lixin³, Cui Qingfeng³, Ma Yuandong³, Miao Junyi⁴, Yu Li³

1. University of Chinese Academy of Sciences, Beijing 100049, China;
2. Institute of Porous Flow and Fluid Mechanics, University of Chinese Academy of Sciences, Hebei Langfang 065007, China;
3. Research Institute of Petroleum Exploration and Development, Hebei Langfang 065007, China;
4. School of Petroleum Engineering, Yangtze University, Hubei Wuhan 430071, China

Received:2018-11-28 Revised:2019-01-23 Online:2019-04-25 Published:2019-05-07

摘要/Abstract

摘要：

为研究油藏环境耦合作用下微生物驱技术提高采收率机理，建立了能全面反映微生物驱油过程的三维三相六组分数学模型，模型涉及的组分有油、气、水、微生物、营养物以及代谢产物。该模型综合考虑了微生物生长/死亡、营养消耗、产物生成、化学趋向性、对流扩散、油相黏度降低、吸附、解吸附以及油-水界面张力变化等特性。其中，微生物生长动力学方程以Monod模型为基础，考虑油藏环境因素对微生物生长模型的影响且微生物在地上与地下生长速率不一致；同时为了体现菌体对微生物驱油的作用，引入微生物因子到微生物驱油机理中。对微生物生长模型、微生物和营养物的混合溶液注入量、环境抑制系数、最大比生长速率以及微生物因子等进行分析的结果表明，通过完善后的微生物生长方程计算得出的产物浓度要比Monod模型低，但这两种微生物生长方程下的产物浓度的差异对最终采收率的影响较小；随着混合溶液注入量的增长，这两种微生物生长方程下的产物浓度差值和采收率提高幅度将增大；微生物因子对微生物驱油有较大的影响，不同微生物因子下提高原油采收率的绝对误差可高达24.53 %。

关键词: 微生物, 油藏环境, 微生物因子, 微生物采油, 数学模型

Abstract:

In this study, a 3D three-phase six-component mathematical model is established to fully reflect the microbial flooding process. The components of this model involve oil, gas, water, microbes, nutrients and metabolites. The model comprehensively involves such properties as microbial growth/death, nutrient consumption, metabolite production, chemotaxis, convection-diffusion, oil viscosity reduction, adsorption, desorption and oil-water interfacial tension change. Considering the effect of reservoir environmental factors on the microbial growth model and inconsistent growth rate of microbes on the ground and underground, the microbial growth kinetics equation is improved on a basis of Monod model. Meanwhile, in order to reflect the effect of bacteria on microbial flooding, a microbial factor is introduced into the mechanism of microbial flooding. Based on case studies, this paper conducts an analysis of the microbial growth model, microbe-nutrient mixed solution injection, environmental inhibition coefficient, maximum specific growth rate and microbial factors. The results show that the metabolite concentration calculated by the improved microbial growth kinetics equation is lower than that of Monod model, but the difference in metabolite concentration obtained using the two microbial growth equations has less effect on final oil recovery. With an increase in the injection amount of microbe-nutrient mixed solution, the difference in metabolite concentration and oil recovery in these two microbial growth equations will be improved. The microbial factor has a great impact on microbial flooding, and the absolute error under different microbial factors in oil recovery can reach up to 24.53 %.

Key words: microbe, reservoir environment, microbial factor, microbial enhanced oil recovery, mathematical model

中图分类号:

TE357.9

王天源, 修建龙, 黄立信, 崔庆锋, 马原栋, 苗钧逸, 俞理. 考虑油藏环境因素和微生物因子的微生物采油数学模型[J]. 石油学报, 2019, 40(4): 448-456.

Wang Tianyuan, Xiu Jianlong, Huang Lixin, Cui Qingfeng, Ma Yuandong, Miao Junyi, Yu Li. A mathematical model for microbial enhanced oil recovery considering reservoir environment and microbial factor[J]. Acta Petrolei Sinica, 2019, 40(4): 448-456.

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考虑油藏环境因素和微生物因子的微生物采油数学模型

A mathematical model for microbial enhanced oil recovery considering reservoir environment and microbial factor

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