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- W3194807655 abstract "Self-potential (SP) method has been increasingly popular in geophysical exploration of mineral resources using an assumption that the causative bodies have idealized geometry (horizontal and vertical cylinders, sphere, and 2-D inclined sheet). In this study, ensemble Kalman inversion (EKI) is proposed to analyze the data and hence determine the associated model parameters. As indicated by its name, the algorithm is constructed based on the iterative ensemble Kalman filter. EKI is applied perform inversion of noisy synthetic and field SP data. The field data were the Neem-ka-Thana and Surda SP anomalies obtained from India, Malachite mine anomaly from USA, and KTB anomaly from Germany containing information of single and multiple anomalous bodies. The EKI exhibits high effectively and accuracy in determination of model parameters and model uncertainty." @default.
- W3194807655 created "2021-08-30" @default.
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- W3194807655 date "2021-01-01" @default.
- W3194807655 modified "2023-09-26" @default.
- W3194807655 title "Ensemble Kalman Inversion for Determining Model Parameter of Self-potential Data in the Mineral Exploration" @default.
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- W3194807655 doi "https://doi.org/10.1007/978-3-030-79333-3_7" @default.
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