地球科学进展 ›› 2020, Vol. 35 ›› Issue (4): 350 -362. doi: 10.11867/j.issn.1001-8166.2020.037

综述与评述 上一篇    下一篇

页岩气水平井产能预测数值模型综述
李亚龙 1, 2, 3( ),刘先贵 2, 3,胡志明 2, 3,端祥刚 2, 3,张杰 1, 2, 3,詹鸿铭 1, 2, 3   
  1. 1. 中国科学院大学,北京 100049
    2. 中国科学院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
  • 收稿日期:2020-01-10 修回日期:2020-03-20 出版日期:2020-04-10
  • 基金资助:
    国家科技重大专项项目“页岩气气藏工程及采气工艺技术”(2017ZX05037-001);国家重大专项“十三五”示范工程“长宁—威远页岩气开发示范工程”(2016ZX05062-002-001)

Summary of Numerical Models for Predicting Productivity of Shale Gas Horizontal Wells

Yalong Li 1, 2, 3( ),Xiangui Liu 2, 3,Zhiming Hu 2, 3,Xianggang Duan 2, 3,Jie Zhang 1, 2, 3,Hongming Zhan 1, 2, 3   

  1. 1. University of Chinese Academy of Sciences, Beijing 100049, China
    2. Institute of Porous Flow and Fluid Mechanics, Chinese Academy of Sciences, Langfang Hebei 065007, China
    3. Research Institute of Petroleum Exploration and Development, Langfang Hebei 065007, China
  • Received:2020-01-10 Revised:2020-03-20 Online:2020-04-10 Published:2020-05-08
  • About author:Li Yalong (1993-), male, Dingxi City, Gansu Province, Ph.D student. Research areas include shale gas seepage mechanism and development. E-mail: liyalong16@mails.ucas.ac.cn
  • Supported by:
    the National Science and Technology Major Project of the Ministry of Science and Technology of China "Shale gas reservoir engineering and gas production technology"(2017ZX05037-001);The Demonstration Project of the National Science and Technology Major Project of the Ministry of Science and Technology of China "Changning-Weiyuan shale gas development demonstration project"(2016ZX05062-002-001)

页岩气的规模开采已逐步实现高产和稳产,作为替代能源弥补油气能源短缺成为可能。页岩储层致密,微纳米孔发育,具有吸附解吸特征和扩散、滑脱效应。同时天然裂缝、层理等发育,水平井体积压裂后水力裂缝不规则扩展,具有多场耦合跨尺度流动效应。其产能预测困难且不确定性大,制约着页岩储层的高效开发和评价。考虑页岩气多尺度多重输运特征,综述了基于双重介质模型、多重介质模型以及复杂缝网模型的页岩气水平井产能预测数值模型的研究发展现状。认为双重介质和多重介质产能模型均弱化了页岩储层压后开采时复杂缝网系统提供的庞大的可渗流面积和通道,不能综合表征页岩气全尺度多重耦合运输特征。而基于复杂缝网的页岩气水平井产能预测数值模型提供了多尺度流动嵌入的缝网系统,解决流动系统性的同时又精确表征了各尺度流动。产能可靠预测需要获得符合储层地质特征、岩石力学行为、高压流体冲击流固耦合作用机理的复杂缝网形态表征。缝网表征是页岩气水平井产能预测的关键。

Shale gas production has gradually achieved high and stable output, which makes it possible to make up for the shortage of oil and gas energy as an alternative energy source. Shale reservoir is compact, with well-developed nano-pore, and has the characteristics of adsorption and desorption, diffusion and slippage. At the same time, there are a large number of natural cracks, bedding and foliation. Hydraulic fractures expand irregularly after volume fracturing in horizontal wells. The whole system has multi-field coupling and cross-scale flow effects. Productivity prediction of shale gas is difficult and uncertain, which restricts the efficient development and evaluation of shale reservoirs. In this paper, the development status of productivity numerical models for shale gas horizontal wells is reviewed in consideration of the multi-scale transport characteristics of shale gas. These models include dual media capacity models, multiple media capacity models, and complex seam productivity models. It is considered that the dual medium and multi-media productivity models weaken the large permeable flow area and channel provided by the complex seam network system after shale reservoir lamination, and cannot comprehensively characterize the full-scale coupled transport characteristics of shale gas. The numerical model for productivity prediction of shale gas horizontal wells based on complex fracture network provides a multi-scale flow embedded fracture network system, which solves the problem of systematic flow without losing the ability to accurately characterize each scale flow. It is necessary to obtain the complex fracture network morphological characterization which conforms to reservoir geological characteristics, rock mechanical behavior and fluid-solid coupling mechanism. Fracture network characterization is the key to the productivity prediction of shale gas horizontal wells.

中图分类号: 

图1 数值模型构成模块及求解流程
Fig.1 Numerical model composition module and solution process
表1 页岩气与常规天然气、致密砂岩气、煤层气对比 [ 1 , 3 , 4 ]
Table 1 Comparison of shale gas with conventional natural gas, tight sandstone gas and coalbed methane [ 1 , 3 , 4 ]
图2 渗流机理示意图[ 13 , 14 ]
(a)吸附—解吸;(b)菲克扩散;(c)克努森扩散;(d)表面扩散;(e)滑脱
Fig.2 Schematic diagram of percolation mechanism[ 13 , 14 ]
(a)Adsorption-desorption; (b)Fick diffusion; (c)Knudsen diffusion; (d)Surface diffusion; (e)Slippage
表2 不同尺度孔缝结构对应的流动方式、流态及流动模型 [ 23 ]
Table 2 Multi-scale pore-slot structure and flow mechanism [ 23 ]
表3 理论特征及与产能模型关系
Table 3 Theoretical characteristics and relationship with capacity models
图3 双重介质模型图 [ 29 ]
(a)双孔单渗模型;(b)双孔双渗模型;红色箭头:缝网渗流;蓝色箭头:基质渗流
Fig.3 Double medium model diagram [ 29 ]
(a)Double-hole and single-permeability; (b)Double-hole and double-permeability;Red arrow represent fracture network seepage;Blue arrow represent matrix seepage
表4 双重介质产能模型发展及完善历程
Table 4 Development and improvement of capacity model based on dual media
图4 多区耦合的多重介质模型[ 40 ]
LF 为主裂缝间距, Lf 为次生裂缝间距
Fig.4 Multi-zone coupled multimedia model[ 40 ]
LF . Main fracture spacing, Lf .Secondary fracture spacing
表5 多重介质产能模型发展及完善历程
Table 5 Development and improvement of productivity model based on multimedia
研究学者 模型特征 研究特征
Ahmadi等[ 41 ] 建立三重介质线性流模型,等效有机基质—基质微孔隙—天然裂缝均为线性流动 天然裂缝系统流动能力对产能的影响
Brown等[ 42 ] 提出三线性流模型,等效基岩—次生裂缝—主裂缝均为线性流动 基岩对裂缝网络的产能供给
郭小哲等[ 43 ] 构建考虑滑脱对渗透率影响规律的三线性渗流模型 滑脱效应对页岩压裂水平井产能的影响
李泽沛等[ 44 ] 考虑基质解吸的基质—等效双孔裂缝体(二级次生缝和一级次生缝)三重介质三孔双渗模型 基质吸附解吸和储层不同区域渗透率变化对产能的影响
程远方等[ 45 ] 考虑重力和毛细管力的有机基质—基质微孔隙—裂缝系统三重介质模型 重力和毛细管力对产能的影响
吴永辉等[ 46 ] 考虑页岩气解吸、滑脱、扩散、压缩非线性的三线性渗流模型 页岩气赋存及非线性流动机理对产能的影响
Wu等[ 40 ] 考虑应力敏感、Klinkenberg效应、裂缝高速非达西流的基质—天然裂缝—压裂缝多重介质模型 Klinkenberg效应对产能的影响
何易东等[ 47 ] 考虑解吸、扩散、滑脱、黏性流、应力敏感效应的支撑主裂缝、缝网波及区与未压裂区多重介质模型 页岩气藏体积压裂水平井生产动态和压力场分布
赵金洲等[ 48 ] 考虑吸附解吸、扩散、滑脱流、应力敏感和人工裂缝非达西流效应的基质一天然裂缝一人工裂缝多重介质模型 考虑多重微观渗流的产能预测
Stalgorova等[ 49 ] 考虑缝间未改造区,建立缝间和外区同时向SRV供给的五区复合线性流模型 基于非常规裂缝复合体系的产能预测
图5 多重介质复杂缝网产能模型[ 52 ]
(a)储层改造模型;(b)缝网模型;(c)基质模型; L为SRV区域表征单元体长度
Fig.5 Productivity model of complex slit mesh with multiple medium[ 52 ]
(a) Reservoir transformation model;(b) Crack network model;(c) Matrix model; L.The length of representative elementary volume of SRV region
表6 复杂缝网产能模型发展及完善历程
Table 6 Development and improvement of productivity model based on complex fracture network
表7 各产能数值模型对比分析
Table 7 Comparative analysis of numerical models for each production capacity
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