Blar i NORCE vitenarkiv på forfatter "Luo, Xiaodong"
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4D seismic history matching: Assessing the use of a dictionary learning based sparse representation method
Soares, Ricardo; Luo, Xiaodong; Evensen, Geir; Bhakta, Tuhin (Peer reviewed; Journal article, 2020)It is possible to improve oil-reservoir simulation models by conditioning them on 4D seismic data. Computational issues may arise related to both storage and CPU time due to the size of the 4D seismic dataset. An approach ... -
Accounting for model errors of rock physics models in 4D seismic history matching problems: A perspective of machine learning
Luo, Xiaodong; Lorentzen, Rolf Johan; Bhakta, Tuhin (Journal article; Peer reviewed, 2021)Model errors are ubiquitous in practical history matching problems. A common approach in the literature to accounting for model errors is to treat them as random variables following certain presumed distributions. While ... -
Characterization of conductivity fields through iterative ensemble smoother and improved correlation-based adaptive localization
Xia, Chuan-An; Li, Jiayun; Riva, Monica; Luo, Xiaodong; Guadagnini, Alberto (Peer reviewed; Journal article, 2024)Localization is critical to the effective use of an (iterative) ensemble Kalman filter or ensemble smoother to estimate uncertain quantities of interest. Here, we propose a novel, fully adaptive, correlation-based localization ... -
Combining direct and indirect sparse data for learning generalizable turbulence models
Zhang, Xin-Lei; Xiao, Heng; Luo, Xiaodong; He, Guowei (Peer reviewed; Journal article, 2023)Learning turbulence models from observation data is of significant interest in discovering a unified model for a broad range of practical flow applications. Either the direct observation of Reynolds stress or the indirect ... -
Data assimilation with multiple types of observation boreholes via the ensemble Kalman filter embedded within stochastic moment equations
Xia, Chuan-An; Luo, Xiaodong; Hu, Bill X.; Riva, Monica; Guadagnini, Alberto (Peer reviewed; Journal article, 2021)We employ an approach based on the ensemble Kalman filter coupled with stochastic moment equations (MEs-EnKF) of groundwater flow to explore the dependence of conductivity estimates on the type of available information ... -
Data assimilation with soft constraints (DASC) through a generalized iterative ensemble smoother
Luo, Xiaodong; Chalub Cruz, William (Peer reviewed; Journal article, 2022)This work investigates an ensemble-based workflow to simultaneously handle generic, nonlinear equality and inequality constraints in reservoir data assimilation problems. The proposed workflow is built upon a recently ... -
Joint History Matching of Multiple Types of Field Data in a 3D Field-Scale Case Study
Chalub Cruz, William; Luo, Xiaodong; Petvipusit, Kurt Rachares (Peer reviewed; Journal article, 2022)This work presents an ensemble-based workflow to simultaneously assimilate multiple types of field data in a proper and consistent manner. The aim of using multiple field datasets is to improve the reliability of estimated ... -
Novel iterative ensemble smoothers derived from a class of generalized cost functions
Luo, Xiaodong (Peer reviewed; Journal article, 2021)Iterative ensemble smoothers (IES) are among the state-of-the-art approaches to solving history matching problems. From an optimization-theoretic point of view, these algorithms can be derived by solving certain stochastic ... -
Underground hydrogen storage (UHS) in natural storage sites: A perspective of subsurface characterization and monitoring
Luo, Xiaodong; Tveit, Svenn; Gholami, Raoof; Andersen, Pål Østebø (Journal article; Peer reviewed, 2024)With the long-standing efforts of green transition in our society, underground hydrogen storage (UHS) has emerged as a viable solution to buffering seasonal fluctuations of renewable energy supplies and demands. Like ...