Jinsong Chen - Academia.edu (original) (raw)
Papers by Jinsong Chen
Genomics, 2009
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of reservoir scale electrical anisotropy from marine CSEM data
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Journal of environmental radioactivity, 2017
This paper presents a multiscale data integration method to estimate the spatial distribution of ... more This paper presents a multiscale data integration method to estimate the spatial distribution of air dose rates in the regional scale around the Fukushima Daiichi Nuclear Power Plant. We integrate various types of datasets, such as ground-based walk and car surveys, and airborne surveys, all of which have different scales, resolutions, spatial coverage, and accuracy. This method is based on geostatistics to represent spatial heterogeneous structures, and also on Bayesian hierarchical models to integrate multiscale, multi-type datasets in a consistent manner. The Bayesian method allows us to quantify the uncertainty in the estimates, and to provide the confidence intervals that are critical for robust decision-making. Although this approach is primarily data-driven, it has great flexibility to include mechanistic models for representing radiation transport or other complex correlations. We demonstrate our approach using three types of datasets collected at the same time over Fukushim...
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Eos, Transactions American Geophysical Union, 2001
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SEG Technical Program Expanded Abstracts 2004, 2004
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SEG Technical Program Expanded Abstracts 2005, 2005
A stochastic joint inversion approach for estimating reservoir fluid saturations and porosity is ... more A stochastic joint inversion approach for estimating reservoir fluid saturations and porosity is proposed. The approach couples seismic amplitude versus angle (AVA) and marine controlled source electromagnetic (CSEM) forward models into a Bayesian formalism, ...
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Water Resources Research, 2004
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Water Resources Research, 2012
ABSTRACT We developed a hierarchical Bayesian model to estimate the spatiotemporal distribution o... more ABSTRACT We developed a hierarchical Bayesian model to estimate the spatiotemporal distribution of aqueous geochemical parameters associated with in-situ bioremediation using surface spectral induced polarization (SIP) data and borehole geochemical measurements collected during a bioremediation experiment at a uranium-contaminated site near Rifle, Colorado (USA). The SIP data were first inverted for Cole-Cole parameters, including chargeability, time constant, resistivity at the DC frequency, and dependence factor, at each pixel of two-dimensional grids using a previously developed stochastic method. Correlations between the inverted Cole-Cole parameters and the wellbore-based groundwater chemistry measurements indicative of key metabolic processes within the aquifer (e.g., ferrous iron, sulfate, uranium) were established and used as a basis for petrophysical model development. The developed Bayesian model consists of three levels of statistical submodels: (1) data model, providing links between geochemical and geophysical attributes, (2) process model, describing the spatial and temporal variability of geochemical properties in the subsurface system, and (3) parameter model, describing prior distributions of various parameters and initial conditions. The unknown parameters were estimated using Markov chain Monte Carlo methods. By combining the temporally distributed geochemical data with the spatially distributed geophysical data, we obtained the spatiotemporal distribution of ferrous iron, sulfate, and sulfide, and their associated uncertainty information. The obtained results can be used to assess the efficacy of the bioremediation treatment over space and time and to constrain reactive transport models.
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Water Resources Research, 2009
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Geosphere, 2006
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GEOPHYSICS, 2006
A stochastic joint-inversion approach for estimating reservoir-fluid saturations and porosity is ... more A stochastic joint-inversion approach for estimating reservoir-fluid saturations and porosity is proposed. The approach couples seismic amplitude variation with angle (AVA) and marine controlled-source electromagnetic (CSEM) forward models into a Bayesian framework, which allows for integration of complementary information. To obtain minimally subjective prior probabilities required for the Bayesian approach, the principle of minimum relative entropy (MRE) is employed. Instead of single-value estimates provided by deterministic methods, the approach gives a probability distribution for any unknown parameter of interest, such as reservoir-fluid saturations or porosity at various locations. The distribution means, modes, and confidence intervals can be calculated, providing a more complete understanding of the uncertainty in the parameter estimates. The approach is demonstrated using synthetic and field data sets. Results show that joint inversion using seismic and EM data gives bette...
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GEOPHYSICS, 2006
Accurately estimating reservoir parameters from geophysical data is vitally important in hydrocar... more Accurately estimating reservoir parameters from geophysical data is vitally important in hydrocarbon exploration and production. We have developed a new joint-inversion algorithm to estimate reservoir parameters directly, using both seismic amplitude variation with angle of incidence (AVA) data and marine controlled-source electromagnetic (CSEM) data. Reservoir parameters are linked to geophysical parameters through a rock-properties model. Errors in the parameters of the rock-properties model introduce errors of comparable size in the reservoir-parameter estimates produced by joint inversion. Tests of joint inversion on synthetic 1D models demonstrate improved fluid saturation and porosity estimates for joint AVA-CSEM data inversion (compared with estimates from AVA or CSEM inversion alone). A comparison of inversions of AVA data, CSEM data, and joint AVA-CSEM data over the North Sea Troll field, at a location for which we have well control, shows that the joint inversion produces ...
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Journal of Medical …, 2009
... 2, WANG Long-xin,WANG He,YANG Xiao-jian,QIN Wei-jun,LIU He-liang,YUAN Jian-lin,YU Lei,ZHANG G... more ... 2, WANG Long-xin,WANG He,YANG Xiao-jian,QIN Wei-jun,LIU He-liang,YUAN Jian-lin,YU Lei,ZHANG Geng (Department of Urology,Xijing Hospital,the Fourth Military Medical University,Xi'an 710033,Shaanxi,China);Expression of ... 9, Huang Zicun, Yang Jian, Zhou Jianliang, ...
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inversion of magnetotelluric data using a sharp boundary parameterization and application to a ge... more inversion of magnetotelluric data using a sharp boundary parameterization and application to a geothermal site
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Journal of Geophysical Research: Biogeosciences
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Genomics, 2009
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of reservoir scale electrical anisotropy from marine CSEM data
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Journal of environmental radioactivity, 2017
This paper presents a multiscale data integration method to estimate the spatial distribution of ... more This paper presents a multiscale data integration method to estimate the spatial distribution of air dose rates in the regional scale around the Fukushima Daiichi Nuclear Power Plant. We integrate various types of datasets, such as ground-based walk and car surveys, and airborne surveys, all of which have different scales, resolutions, spatial coverage, and accuracy. This method is based on geostatistics to represent spatial heterogeneous structures, and also on Bayesian hierarchical models to integrate multiscale, multi-type datasets in a consistent manner. The Bayesian method allows us to quantify the uncertainty in the estimates, and to provide the confidence intervals that are critical for robust decision-making. Although this approach is primarily data-driven, it has great flexibility to include mechanistic models for representing radiation transport or other complex correlations. We demonstrate our approach using three types of datasets collected at the same time over Fukushim...
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Bookmarks Related papers MentionsView impact
Eos, Transactions American Geophysical Union, 2001
Bookmarks Related papers MentionsView impact
SEG Technical Program Expanded Abstracts 2004, 2004
Bookmarks Related papers MentionsView impact
SEG Technical Program Expanded Abstracts 2005, 2005
A stochastic joint inversion approach for estimating reservoir fluid saturations and porosity is ... more A stochastic joint inversion approach for estimating reservoir fluid saturations and porosity is proposed. The approach couples seismic amplitude versus angle (AVA) and marine controlled source electromagnetic (CSEM) forward models into a Bayesian formalism, ...
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Water Resources Research, 2004
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Water Resources Research, 2012
ABSTRACT We developed a hierarchical Bayesian model to estimate the spatiotemporal distribution o... more ABSTRACT We developed a hierarchical Bayesian model to estimate the spatiotemporal distribution of aqueous geochemical parameters associated with in-situ bioremediation using surface spectral induced polarization (SIP) data and borehole geochemical measurements collected during a bioremediation experiment at a uranium-contaminated site near Rifle, Colorado (USA). The SIP data were first inverted for Cole-Cole parameters, including chargeability, time constant, resistivity at the DC frequency, and dependence factor, at each pixel of two-dimensional grids using a previously developed stochastic method. Correlations between the inverted Cole-Cole parameters and the wellbore-based groundwater chemistry measurements indicative of key metabolic processes within the aquifer (e.g., ferrous iron, sulfate, uranium) were established and used as a basis for petrophysical model development. The developed Bayesian model consists of three levels of statistical submodels: (1) data model, providing links between geochemical and geophysical attributes, (2) process model, describing the spatial and temporal variability of geochemical properties in the subsurface system, and (3) parameter model, describing prior distributions of various parameters and initial conditions. The unknown parameters were estimated using Markov chain Monte Carlo methods. By combining the temporally distributed geochemical data with the spatially distributed geophysical data, we obtained the spatiotemporal distribution of ferrous iron, sulfate, and sulfide, and their associated uncertainty information. The obtained results can be used to assess the efficacy of the bioremediation treatment over space and time and to constrain reactive transport models.
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Water Resources Research, 2009
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Geosphere, 2006
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GEOPHYSICS, 2006
A stochastic joint-inversion approach for estimating reservoir-fluid saturations and porosity is ... more A stochastic joint-inversion approach for estimating reservoir-fluid saturations and porosity is proposed. The approach couples seismic amplitude variation with angle (AVA) and marine controlled-source electromagnetic (CSEM) forward models into a Bayesian framework, which allows for integration of complementary information. To obtain minimally subjective prior probabilities required for the Bayesian approach, the principle of minimum relative entropy (MRE) is employed. Instead of single-value estimates provided by deterministic methods, the approach gives a probability distribution for any unknown parameter of interest, such as reservoir-fluid saturations or porosity at various locations. The distribution means, modes, and confidence intervals can be calculated, providing a more complete understanding of the uncertainty in the parameter estimates. The approach is demonstrated using synthetic and field data sets. Results show that joint inversion using seismic and EM data gives bette...
Bookmarks Related papers MentionsView impact
GEOPHYSICS, 2006
Accurately estimating reservoir parameters from geophysical data is vitally important in hydrocar... more Accurately estimating reservoir parameters from geophysical data is vitally important in hydrocarbon exploration and production. We have developed a new joint-inversion algorithm to estimate reservoir parameters directly, using both seismic amplitude variation with angle of incidence (AVA) data and marine controlled-source electromagnetic (CSEM) data. Reservoir parameters are linked to geophysical parameters through a rock-properties model. Errors in the parameters of the rock-properties model introduce errors of comparable size in the reservoir-parameter estimates produced by joint inversion. Tests of joint inversion on synthetic 1D models demonstrate improved fluid saturation and porosity estimates for joint AVA-CSEM data inversion (compared with estimates from AVA or CSEM inversion alone). A comparison of inversions of AVA data, CSEM data, and joint AVA-CSEM data over the North Sea Troll field, at a location for which we have well control, shows that the joint inversion produces ...
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Journal of Medical …, 2009
... 2, WANG Long-xin,WANG He,YANG Xiao-jian,QIN Wei-jun,LIU He-liang,YUAN Jian-lin,YU Lei,ZHANG G... more ... 2, WANG Long-xin,WANG He,YANG Xiao-jian,QIN Wei-jun,LIU He-liang,YUAN Jian-lin,YU Lei,ZHANG Geng (Department of Urology,Xijing Hospital,the Fourth Military Medical University,Xi'an 710033,Shaanxi,China);Expression of ... 9, Huang Zicun, Yang Jian, Zhou Jianliang, ...
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
inversion of magnetotelluric data using a sharp boundary parameterization and application to a ge... more inversion of magnetotelluric data using a sharp boundary parameterization and application to a geothermal site
Bookmarks Related papers MentionsView impact
Journal of Geophysical Research: Biogeosciences
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Bookmarks Related papers MentionsView impact