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Determining the effective permeability (keff) of geological formations has broad applications to site remediation, aquifer discharge or recharge, hydrocarbon production, and enhanced oil recovery. The objectives of this study are: (1) to…

Geophysics · Physics 2021-12-07 Barnabas Adeyemi , Behzad Ghanbarian , C. L. Winter , Peter R. King

Monitoring the rock-physics properties of the subsurface is of great importance for reservoir management. For either oil and gas applications or CO2 storage, seismic data are a valuable source of information for tracking changes in elastic…

Predicting microporosity and permeability in clastic reservoirs is a challenge in reservoir quality assessment, especially in formations where direct measurements are difficult or expensive. These reservoir properties are fundamental in…

Geophysics · Physics 2025-03-24 Muhammad Risha , Mohamed Elsaadany , Paul Liu

The ensemble Kalman inversion is widely used in practice to estimate unknown parameters from noisy measurement data. Its low computational costs, straightforward implementation, and non-intrusive nature makes the method appealing in various…

Numerical Analysis · Mathematics 2019-09-04 Dirk Blömker , Claudia Schillings , Philipp Wacker , Simon Weissmann

Accurate modeling of gas relative permeability has practical applications in oil and gas exploration, production and recovery of unconventional reservoirs. In this study, we apply concepts from the effective-medium approximation (EMA) and…

Geophysics · Physics 2020-04-08 Behzad Ghanbarian , Feng Liang , Hui-Hai Liu

Numerical models of geothermal reservoirs typically depend on hundreds or thousands of unknown parameters, which must be estimated using sparse, noisy data. However, these models capture complex physical processes, which frequently results…

We consider the solution of inverse problems in dynamic contrast-enhanced imaging by means of Ensemble Kalman Filters. Our quantity of interest is blood perfusion, i.e. blood flow rates in tissue. While existing approaches to compute blood…

Numerical Analysis · Mathematics 2018-10-23 Peter Zaspel

Reconstruction of turbulent flow based on data assimilation methods is of significant importance for improving the estimation of flow characteristics by incorporating limited observations. Existing works mainly focus on using only one…

Fluid Dynamics · Physics 2021-03-30 Xin-Lei Zhang , Heng Xiao , Guo-Wei He , Shi-Zhao Wang

This study investigates the use of score-based generative models for reservoir simulation, with a focus on reconstructing spatially varying permeability and saturation fields in saline aquifers, inferred from sparse observations at two well…

Machine Learning · Computer Science 2025-04-10 Shiqin Zeng , Haoyun Li , Abhinav Prakash Gahlot , Felix J. Herrmann

A sequential estimator based on the Ensemble Kalman Filter for Data Assimilation of fluid flows is presented in this research work. The main feature of this estimator is that the Kalman filter update, which relies on the determination of…

Computational Engineering, Finance, and Science · Computer Science 2021-07-28 Gabriel Moldovan , Guillame Lehnasch , Laurent Cordier , Marcello Meldi

Essential features of the Multigrid Ensemble Kalman Filter (G. Moldovan, G. Lehnasch, L. Cordier, M. Meldi, A multigrid/ensemble Kalman filter strategy for assimilation of unsteady flows, Journal of Computational Physics 443-110481)…

Fluid Dynamics · Physics 2022-10-20 Gabriel Moldovan , Guillaume Lehnasch , Laurent Cordier , Marcello Meldi

Relative permeability is commonly used to model immiscible fluid flow through porous materials. In this work we derive the relative permeability relationship from conservation of energy, assuming that the system to be non-ergodic at large…

We introduce a derivative-free computational framework for approximating solutions to nonlinear PDE-constrained inverse problems. The aim is to merge ideas from iterative regularization with ensemble Kalman methods from Bayesian inference…

Optimization and Control · Mathematics 2016-01-20 Marco A. Iglesias

Ensemble Kalman methods were initially developed to solve nonlinear data assimilation problems in oceanography, but are now popular in applications far beyond their original use cases. Of particular interest is climate model calibration. As…

Data Analysis, Statistics and Probability · Physics 2025-11-21 Rebecca Gjini , Matthias Morzfeld , Oliver R. A. Dunbar , Tapio Schneider

We propose a new method for construction of the absolute permeability map consistent with the interpreted results of well logging and well test measurements in oil reservoirs. Nadaraya-Watson kernel regression is used to approximate…

The Bayesian approach to inverse problems is widely used in practice to infer unknown parameters from noisy observations. In this framework, the ensemble Kalman inversion has been successfully applied for the quantification of uncertainties…

Numerical Analysis · Mathematics 2019-10-15 Neil K. Chada , Claudia Schillings , Simon Weissmann

Obtaining reliable permeability maps of oil reservoirs is crucial for building a robust and accurate reservoir simulation model and, therefore, designing effective recovery strategies. This problem, however, remains challenging, as it…

The costs for drilling offshore wells are high and hydrocarbons are often located in complex reservoir formations. To effectively produce from such reservoirs and reduce costs, optimized well placement in real-time (geosteering) is crucial.…

Ensemble Kalman methods are widely used for state estimation in the geophysical sciences. Their success stems from the fact that they take an underlying (possibly noisy) dynamical system as a black box to provide a systematic,…

Optimization and Control · Mathematics 2024-10-10 Edoardo Calvello , Sebastian Reich , Andrew M. Stuart

Pipelines for water supply are susceptible to burst-leakage due to fluid pressures of various nature. High pressure heads resulting in circumferential and (or) axial stresses larger than the material yield stress could cause pipe failure.…

Signal Processing · Electrical Eng. & Systems 2021-08-24 Radhika P , Anu Mol Joy
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