A dual-porosity flow-net model for simulating water-flooding in low-permeability fractured reservoirs

多孔性 磁导率 离散化 地质学 储层模拟 达西定律 石油工程 流量(数学) 机械 流体力学 网络模型 计算机科学 数学优化 岩土工程 多孔介质 物理 数据挖掘 数学 数学分析 遗传学 生物
作者
Xia Yan,Guoyu Qin,Liming Zhang,Kai Zhang,Yongfei Yang,Jun Yao,Jialin Wang,Qinyang Dai,Dawei Wu
标识
DOI:10.1016/j.geoen.2024.213069
摘要

The physics-based data-driven flow-network models with high computational efficiency have received great attention as the promising surrogate models for reservoir numerical simulation. However, the existing flow-network models developed for water-flooding reservoirs fail to consider different seepage characteristics of matrix and fractures and cannot be straightly applied to simulate the water-flooding process in low-permeability fractured reservoirs. In this study, we combine the flow-network model with the dual-porosity model to propose a new physics-based data-driven surrogate model, namely the Dual-Porosity Flow-Network Model (Flow-Net-DP), which can consider the non-Darcy flow in tight matrix and the stress-sensitive effects and preferential flow characteristic in fractures. Specifically, we refer to the dual-porosity model and use two channels to represent the connections between wells: one indicates the fracture system, the other represents the matrix system, and the fluid exchange between these two systems is considered by using a transfer function. Besides, each channel is discretized into one-dimensional grids, and a fully implicit scheme with Newton iteration is used to calculate pressure and saturation. Moreover, we establish an automated history matching method by using the Ensemble Smoother with Multiple Data Assimilation (ESMDA) algorithm to calibrate model parameters of Flow-Net-DP, and develop a production optimization method by using the Differential Evolution (DE) algorithm. Finally, the numerical simulation, history matching, and production optimization are conducted on different numerical examples to validate the capability of Flow-Net-DP. The results indicate that the Flow-Net-DP can provide a better description of water flooding process in low-permeability fractured reservoirs compared with the existing flow-network model, especially the rapid water breakthrough caused by the preferential flow characteristic in fractures. Furthermore, both history matching and production optimization based on the Flow-Net-DP yield satisfactory outcomes. For instance, when the optimization results are similar to the full-order simulation model, the optimization speed of Flow-Net-DP is increased by more than five times.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
虚幻的冬瓜完成签到,获得积分10
1秒前
斯文败类应助糊涂的听筠采纳,获得10
2秒前
所所应助科研通管家采纳,获得10
3秒前
脑洞疼应助科研通管家采纳,获得10
3秒前
3秒前
bkagyin应助科研通管家采纳,获得10
3秒前
充电宝应助科研通管家采纳,获得10
3秒前
完美世界应助科研通管家采纳,获得10
4秒前
Orange应助科研通管家采纳,获得10
4秒前
4秒前
4秒前
脑洞疼应助科研通管家采纳,获得10
4秒前
4秒前
共享精神应助科研通管家采纳,获得10
4秒前
搜集达人应助科研通管家采纳,获得10
4秒前
Owen应助科研通管家采纳,获得10
4秒前
顾矜应助科研通管家采纳,获得10
4秒前
NexusExplorer应助科研通管家采纳,获得10
4秒前
5秒前
5秒前
5秒前
7秒前
7秒前
年轻的凡桃完成签到,获得积分20
8秒前
8秒前
10秒前
chen发布了新的文献求助10
10秒前
11秒前
11秒前
11秒前
guantlv发布了新的文献求助10
12秒前
14秒前
14秒前
绿波电龙完成签到,获得积分10
15秒前
pure milk发布了新的文献求助10
15秒前
15秒前
16秒前
qazxc发布了新的文献求助10
16秒前
19秒前
cdercder应助木子采纳,获得10
19秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Arthritis and Related Conditions, An Issue of Orthopedic Clinics 1000
Development of a Bridge Weigh-In-Motion System: A technology to convert the bridge response to the passage of traffic into data on vehicle configurations, speeds, times of travel and weights 1000
ズームレンズの光学設計に関する研究 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7288320
求助须知:如何正确求助?哪些是违规求助? 8908082
关于积分的说明 18853488
捐赠科研通 6957123
什么是DOI,文献DOI怎么找? 3208876
关于科研通互助平台的介绍 2378670
邀请新用户注册赠送积分活动 2184659