首页 > 最新文献

Computational Geosciences最新文献

英文 中文
Binary well placement optimization using a decomposition-based multi-objective evolutionary algorithm with diversity preservation 基于分解的多样性保持多目标进化算法在二元井布局优化中的应用
IF 2.5 3区 地球科学 Q1 Mathematics Pub Date : 2023-07-25 DOI: 10.1007/s10596-023-10235-0
Matheus Bernardelli de Moraes, G. P. Coelho, A. A. S. Santos, D. Schiozer
{"title":"Binary well placement optimization using a decomposition-based multi-objective evolutionary algorithm with diversity preservation","authors":"Matheus Bernardelli de Moraes, G. P. Coelho, A. A. S. Santos, D. Schiozer","doi":"10.1007/s10596-023-10235-0","DOIUrl":"https://doi.org/10.1007/s10596-023-10235-0","url":null,"abstract":"","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46970073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Robustness and efficiency of iteration schemes for variably saturated flow across the range of soils, initial and boundary conditions found in practice 在实践中发现的不同土壤、初始条件和边界条件下变饱和流迭代方案的鲁棒性和效率
IF 2.5 3区 地球科学 Q1 Mathematics Pub Date : 2023-07-23 DOI: 10.1007/s10596-023-10230-5
Denis Maier, H. Montenegro, B. Odenwald
{"title":"Robustness and efficiency of iteration schemes for variably saturated flow across the range of soils, initial and boundary conditions found in practice","authors":"Denis Maier, H. Montenegro, B. Odenwald","doi":"10.1007/s10596-023-10230-5","DOIUrl":"https://doi.org/10.1007/s10596-023-10230-5","url":null,"abstract":"","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43460130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Hard enforcement of physics-informed neural network solutions of acoustic wave propagation 声波传播的物理信息神经网络解决方案的硬执行
IF 2.5 3区 地球科学 Q1 Mathematics Pub Date : 2023-07-23 DOI: 10.1007/s10596-023-10232-3
Harpreet Sethi, Doris Pan, Pavel Dimitrov, J. Shragge, Gunter Roth, K. Hester
{"title":"Hard enforcement of physics-informed neural network solutions of acoustic wave propagation","authors":"Harpreet Sethi, Doris Pan, Pavel Dimitrov, J. Shragge, Gunter Roth, K. Hester","doi":"10.1007/s10596-023-10232-3","DOIUrl":"https://doi.org/10.1007/s10596-023-10232-3","url":null,"abstract":"","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42020479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
An integrated framework for optimal monitoring and history matching in CO $$_{2}$$ storage projects CO $$_{2}$$存储项目中最优监测和历史匹配的集成框架
IF 2.5 3区 地球科学 Q1 Mathematics Pub Date : 2023-07-23 DOI: 10.1007/s10596-023-10216-3
Dylan M. Crain, Sally M. Benson, Sarah D. Saltzer, Louis J. Durlofsky

Monitoring is an important component of geological carbon storage operations because it provides data that can be used to estimate key quantities such as CO(_{2}) plume location. The design of the monitoring strategy is complicated, however, because the monitoring plan must be established prior to the availability of extensive flow data. In this work, we present and apply a framework that integrates monitoring well optimization and (subsequent) history matching. The monitoring well optimization entails finding the locations of monitoring wells such that, with the data acquired at those locations, the expected uncertainty reduction in a particular flow quantity is maximized. This optimization requires the simulation of a large set of prior models, though these simulations need only be performed once for a given injection scenario. Once the monitoring wells are in place and CO(_{2}) injection begins, history matching is performed using the monitoring data. This is accomplished here using an ensemble smoother with multiple data assimilation. The overall framework is applied to variogram-based geomodels that are representative of an actual storage project under development in the USA. Two injection scenarios are considered with two different (synthetic) ‘true’ models, which provide the observed data. History matched models are constructed using data from both optimally located and heuristically placed monitoring wells. Posterior uncertainty, evaluated in terms of the cumulative distribution function for a metric related to plume extent over the ensemble of history matched models, is shown to be minimized through use of optimized monitoring wells. These results demonstrate the importance of optimizing the monitoring plan, and the degree of uncertainty reduction that can be realistically achieved.

监测是地质碳储存作业的重要组成部分,因为它提供的数据可用于估计CO (_{2})烟羽位置等关键数量。然而,监测策略的设计是复杂的,因为必须在获得大量流量数据之前制定监测计划。在这项工作中,我们提出并应用了一个框架,该框架集成了监测井优化和(后续)历史匹配。监测井优化需要找到监测井的位置,以便根据在这些位置获取的数据,最大限度地降低特定流量的预期不确定性。这种优化需要模拟大量先前的模型,尽管这些模拟只需要针对给定的注入场景执行一次。一旦监测井就位并开始注入CO (_{2}),就可以使用监测数据进行历史匹配。这在这里是使用具有多个数据同化的集成平滑器来完成的。整体框架应用于基于变方差的地质模型,这些模型代表了美国正在开发的实际存储项目。采用两种不同的(合成的)“真实”模型考虑了两种注入情景,这些模型提供了观测数据。历史匹配模型是利用最优定位和启发式定位监测井的数据构建的。后验不确定性,根据历史匹配模型集合上与羽流范围相关的度量的累积分布函数进行评估,表明通过使用优化的监测井可以最小化。这些结果表明了优化监测计划的重要性,以及可以实际实现的不确定性降低程度。
{"title":"An integrated framework for optimal monitoring and history matching in CO $$_{2}$$ storage projects","authors":"Dylan M. Crain, Sally M. Benson, Sarah D. Saltzer, Louis J. Durlofsky","doi":"10.1007/s10596-023-10216-3","DOIUrl":"https://doi.org/10.1007/s10596-023-10216-3","url":null,"abstract":"<p>Monitoring is an important component of geological carbon storage operations because it provides data that can be used to estimate key quantities such as CO<span>(_{2})</span> plume location. The design of the monitoring strategy is complicated, however, because the monitoring plan must be established prior to the availability of extensive flow data. In this work, we present and apply a framework that integrates monitoring well optimization and (subsequent) history matching. The monitoring well optimization entails finding the locations of monitoring wells such that, with the data acquired at those locations, the expected uncertainty reduction in a particular flow quantity is maximized. This optimization requires the simulation of a large set of prior models, though these simulations need only be performed once for a given injection scenario. Once the monitoring wells are in place and CO<span>(_{2})</span> injection begins, history matching is performed using the monitoring data. This is accomplished here using an ensemble smoother with multiple data assimilation. The overall framework is applied to variogram-based geomodels that are representative of an actual storage project under development in the USA. Two injection scenarios are considered with two different (synthetic) ‘true’ models, which provide the observed data. History matched models are constructed using data from both optimally located and heuristically placed monitoring wells. Posterior uncertainty, evaluated in terms of the cumulative distribution function for a metric related to plume extent over the ensemble of history matched models, is shown to be minimized through use of optimized monitoring wells. These results demonstrate the importance of optimizing the monitoring plan, and the degree of uncertainty reduction that can be realistically achieved.</p>","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138514558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
High-order compact difference schemes based on the local one-dimensional method for high-dimensional nonlinear wave equations 基于局部一维方法的高维非线性波动方程的高阶紧致差分格式
IF 2.5 3区 地球科学 Q1 Mathematics Pub Date : 2023-07-14 DOI: 10.1007/s10596-023-10226-1
Mengling Wu, Z. Wang, Y. Ge
{"title":"High-order compact difference schemes based on the local one-dimensional method for high-dimensional nonlinear wave equations","authors":"Mengling Wu, Z. Wang, Y. Ge","doi":"10.1007/s10596-023-10226-1","DOIUrl":"https://doi.org/10.1007/s10596-023-10226-1","url":null,"abstract":"","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47349625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Adaptive mesh refinement in locally conservative level set methods for multiphase fluid displacements in porous media 多孔介质中多相流体驱替的局部保守水平集方法中的自适应网格细化
IF 2.5 3区 地球科学 Q1 Mathematics Pub Date : 2023-07-13 DOI: 10.1007/s10596-023-10219-0
Deepak Singh, H. A. Friis, E. Jettestuen, J. O. Helland
{"title":"Adaptive mesh refinement in locally conservative level set methods for multiphase fluid displacements in porous media","authors":"Deepak Singh, H. A. Friis, E. Jettestuen, J. O. Helland","doi":"10.1007/s10596-023-10219-0","DOIUrl":"https://doi.org/10.1007/s10596-023-10219-0","url":null,"abstract":"","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49474638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Solving the fixed gravimetric boundary value problem by the finite element method using mapped infinite elements. 利用映射无限元的有限元方法求解固定重力边值问题。
IF 2.5 3区 地球科学 Q1 Mathematics Pub Date : 2023-07-05 DOI: 10.1007/s10596-023-10224-3
M. Macák, Z. Minarechová, Lukáš Tomek, R. Cunderlík, K. Mikula
{"title":"Solving the fixed gravimetric boundary value problem by the finite element method using mapped infinite elements.","authors":"M. Macák, Z. Minarechová, Lukáš Tomek, R. Cunderlík, K. Mikula","doi":"10.1007/s10596-023-10224-3","DOIUrl":"https://doi.org/10.1007/s10596-023-10224-3","url":null,"abstract":"","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42364295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An enhanced V-cycle MgNet model for operator learning in numerical partial differential equations 一种用于数值偏微分方程算子学习的增强型v循环MgNet模型
3区 地球科学 Q1 Mathematics Pub Date : 2023-07-01 DOI: 10.1007/s10596-023-10211-8
Jianqing Zhu, Juncai He, Qiumei Huang
{"title":"An enhanced V-cycle MgNet model for operator learning in numerical partial differential equations","authors":"Jianqing Zhu, Juncai He, Qiumei Huang","doi":"10.1007/s10596-023-10211-8","DOIUrl":"https://doi.org/10.1007/s10596-023-10211-8","url":null,"abstract":"","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135264336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A quasi-Newton trust-region method for optimization under uncertainty using stochastic simplex approximate gradients 用随机单纯形近似梯度求解不确定条件下优化问题的拟牛顿信赖域方法
IF 2.5 3区 地球科学 Q1 Mathematics Pub Date : 2023-06-24 DOI: 10.1007/s10596-023-10218-1
Esmail Eltahan, F. Alpak, K. Sepehrnoori
{"title":"A quasi-Newton trust-region method for optimization under uncertainty using stochastic simplex approximate gradients","authors":"Esmail Eltahan, F. Alpak, K. Sepehrnoori","doi":"10.1007/s10596-023-10218-1","DOIUrl":"https://doi.org/10.1007/s10596-023-10218-1","url":null,"abstract":"","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45367478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Bayesian source identification of urban-scale air pollution from point and field concentration measurements 基于点和场浓度测量的城市尺度空气污染的贝叶斯源识别
IF 2.5 3区 地球科学 Q1 Mathematics Pub Date : 2023-06-18 DOI: 10.1007/s10596-023-10206-5
Elissar Al Aawar, Samah El Mohtar, I. Lakkis, A. K. Alduwais, I. Hoteit
{"title":"Bayesian source identification of urban-scale air pollution from point and field concentration measurements","authors":"Elissar Al Aawar, Samah El Mohtar, I. Lakkis, A. K. Alduwais, I. Hoteit","doi":"10.1007/s10596-023-10206-5","DOIUrl":"https://doi.org/10.1007/s10596-023-10206-5","url":null,"abstract":"","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2023-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43624712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
期刊
Computational Geosciences
全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1