Uncertainty Analysis of Factors Influencing Stimulated Fracture Volume in Layered Formation

Hydraulic fracture dimension is one of the key parameters affecting stimulated porous media. In actual fracturing, plentiful uncertain parameters increase the difficulty of fracture dimension prediction, resulting in the difficulty in the monitoring of reservoir productivity. In this paper, we estab...

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Main Authors: Jingxuan Zhang, Xiangjun Liu, Xiaochen Wei, Lixi Liang, Jian Xiong, Wei Li
Format: Article
Language:English
Published: MDPI AG 2019-11-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/12/23/4444
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spelling doaj-7f16fbc9feda45b8869e430072eb857f2020-11-25T00:39:17ZengMDPI AGEnergies1996-10732019-11-011223444410.3390/en12234444en12234444Uncertainty Analysis of Factors Influencing Stimulated Fracture Volume in Layered FormationJingxuan Zhang0Xiangjun Liu1Xiaochen Wei2Lixi Liang3Jian Xiong4Wei Li5State Key Laboratory of Oil and Gas Reservoir Geology and Development Engineering, Southwest Petroleum University, Chengdu 610500, ChinaState Key Laboratory of Oil and Gas Reservoir Geology and Development Engineering, Southwest Petroleum University, Chengdu 610500, ChinaState Key Laboratory of Oil and Gas Reservoir Geology and Development Engineering, Southwest Petroleum University, Chengdu 610500, ChinaState Key Laboratory of Oil and Gas Reservoir Geology and Development Engineering, Southwest Petroleum University, Chengdu 610500, ChinaState Key Laboratory of Oil and Gas Reservoir Geology and Development Engineering, Southwest Petroleum University, Chengdu 610500, ChinaState Key Laboratory of Oil and Gas Reservoir Geology and Development Engineering, Southwest Petroleum University, Chengdu 610500, ChinaHydraulic fracture dimension is one of the key parameters affecting stimulated porous media. In actual fracturing, plentiful uncertain parameters increase the difficulty of fracture dimension prediction, resulting in the difficulty in the monitoring of reservoir productivity. In this paper, we established a three-dimensional model to analyze the key factors on the stimulated reservoir volume (SRV), with the response surface method (RSM). Considering the rock properties and fracturing parameters, we established a multivariate quadratic prediction equation. Simulation results show that the interactions of injection rate (<i>Q</i>), Young&#8217;s modulus (<i>E</i>) and permeability coefficient (<i>K</i>), and Poisson&#8217;s ratio (<i>&#956;</i>) play a relatively significant role on SRV. The reservoir with a high Young&#8217;s modulus typically generates high pressure, leading to longer fractures and larger SRV. SRV reaches the maximum value when <i>E</i>1 and <i>E</i>2 are high. SRV is negatively correlated with <i>K</i>1. Moreover, maintaining a high injection rate in this layered formation with high <i>E</i>1 and <i>E</i>2, relatively low <i>K</i>1, and <i>&#956;</i>1 at about 0.25 would be beneficial to form a larger SRV. These results offer new perceptions on the optimization of SRV, helping to improve the productivity in hydraulic fracturing.https://www.mdpi.com/1996-1073/12/23/4444fluid-driven fracturesreservoir modelingfinite element methoduncertainty analysis
collection DOAJ
language English
format Article
sources DOAJ
author Jingxuan Zhang
Xiangjun Liu
Xiaochen Wei
Lixi Liang
Jian Xiong
Wei Li
spellingShingle Jingxuan Zhang
Xiangjun Liu
Xiaochen Wei
Lixi Liang
Jian Xiong
Wei Li
Uncertainty Analysis of Factors Influencing Stimulated Fracture Volume in Layered Formation
Energies
fluid-driven fractures
reservoir modeling
finite element method
uncertainty analysis
author_facet Jingxuan Zhang
Xiangjun Liu
Xiaochen Wei
Lixi Liang
Jian Xiong
Wei Li
author_sort Jingxuan Zhang
title Uncertainty Analysis of Factors Influencing Stimulated Fracture Volume in Layered Formation
title_short Uncertainty Analysis of Factors Influencing Stimulated Fracture Volume in Layered Formation
title_full Uncertainty Analysis of Factors Influencing Stimulated Fracture Volume in Layered Formation
title_fullStr Uncertainty Analysis of Factors Influencing Stimulated Fracture Volume in Layered Formation
title_full_unstemmed Uncertainty Analysis of Factors Influencing Stimulated Fracture Volume in Layered Formation
title_sort uncertainty analysis of factors influencing stimulated fracture volume in layered formation
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2019-11-01
description Hydraulic fracture dimension is one of the key parameters affecting stimulated porous media. In actual fracturing, plentiful uncertain parameters increase the difficulty of fracture dimension prediction, resulting in the difficulty in the monitoring of reservoir productivity. In this paper, we established a three-dimensional model to analyze the key factors on the stimulated reservoir volume (SRV), with the response surface method (RSM). Considering the rock properties and fracturing parameters, we established a multivariate quadratic prediction equation. Simulation results show that the interactions of injection rate (<i>Q</i>), Young&#8217;s modulus (<i>E</i>) and permeability coefficient (<i>K</i>), and Poisson&#8217;s ratio (<i>&#956;</i>) play a relatively significant role on SRV. The reservoir with a high Young&#8217;s modulus typically generates high pressure, leading to longer fractures and larger SRV. SRV reaches the maximum value when <i>E</i>1 and <i>E</i>2 are high. SRV is negatively correlated with <i>K</i>1. Moreover, maintaining a high injection rate in this layered formation with high <i>E</i>1 and <i>E</i>2, relatively low <i>K</i>1, and <i>&#956;</i>1 at about 0.25 would be beneficial to form a larger SRV. These results offer new perceptions on the optimization of SRV, helping to improve the productivity in hydraulic fracturing.
topic fluid-driven fractures
reservoir modeling
finite element method
uncertainty analysis
url https://www.mdpi.com/1996-1073/12/23/4444
work_keys_str_mv AT jingxuanzhang uncertaintyanalysisoffactorsinfluencingstimulatedfracturevolumeinlayeredformation
AT xiangjunliu uncertaintyanalysisoffactorsinfluencingstimulatedfracturevolumeinlayeredformation
AT xiaochenwei uncertaintyanalysisoffactorsinfluencingstimulatedfracturevolumeinlayeredformation
AT lixiliang uncertaintyanalysisoffactorsinfluencingstimulatedfracturevolumeinlayeredformation
AT jianxiong uncertaintyanalysisoffactorsinfluencingstimulatedfracturevolumeinlayeredformation
AT weili uncertaintyanalysisoffactorsinfluencingstimulatedfracturevolumeinlayeredformation
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