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Related papers: Joint inversion in hydrogeophysics and near-surfac…

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The application of process-based and data-driven hydrological models is crucial in modern hydrological research, especially for predicting key water cycle variables such as runoff, evapotranspiration (ET), and soil moisture. These models…

Geophysics · Physics 2024-08-14 Haiyang Shi

Joint inversion refers to the simultaneous inference of multiple parameter fields from observations of systems governed by single or multiple forward models. In many cases these parameter fields reflect different attributes of a single…

Numerical Analysis · Mathematics 2019-01-30 Benjamin Crestel , Georg Stadler , Omar Ghattas

This paper presents a new joint inversion approach to shape-based inverse problems. Given two sets of data from distinct physical models, the main objective is to obtain a unified characterization of inclusions within the spatial domain of…

Geophysical inversion should ideally produce geologically realistic subsurface models that explain the available data. Multiple-point statistics is a geostatistical approach to construct subsurface models that are consistent with…

Geophysics · Physics 2017-01-09 T. Zahner , T. Lochbühler , G. Mariethoz , N. Linde

Engineered infrastructure systems pose inverse problems in which hidden states, unknown parameters, and subsystem couplings must be inferred from sparse and noisy measurements. These problems are difficult because physical subsystems are…

Systems and Control · Electrical Eng. & Systems 2026-05-28 Esmaeil Ghorbani , Jürgen Hackl

This paper reviews recent results on hybrid inverse problems, which are also called coupled-physics inverse problems of multi-wave inverse problems. Inverse problems tend to be most useful in, e.g., medical and geophysical imaging, when…

Analysis of PDEs · Mathematics 2011-10-24 Guillaume Bal

4D seismic inversion is the leading method to quantitatively monitor fluid flow dynamics in the subsurface, with applications ranging from enhanced oil recovery to subsurface CO2 storage. The process of inverting seismic data for reservoir…

Geophysics · Physics 2023-10-25 Juan Romero , Nick Luiken , Matteo Ravasi

One of the most challenging aspects of multivariate geostatistics is dealing with complex relationships between variables. Geostatistical co-simulation and spatial decorrelation methods, commonly used for modelling multiple variables, are…

Methodology · Statistics 2025-03-07 Sultan Abulkhair , Peter A. Dowd , Chaoshui Xu

Spatially-indexed multivariate data appear frequently in geostatistics and related fields including oceanography and environmental science. To take full advantage of this data structure, cross-covariance functions are constructed to…

Methodology · Statistics 2025-03-07 Drew Yarger , Anindya Bhadra

The adjoint method is a popular method used for seismic (full-waveform) inversion today. The method is considered to give more realistic and detailed images of the interior of the Earth by the use of more realistic physics. It relies on the…

Geophysics · Physics 2024-08-28 Rafael Abreu

Solving multiphysics-based inverse problems for geological carbon storage monitoring can be challenging when multimodal time-lapse data are expensive to collect and costly to simulate numerically. We overcome these challenges by combining…

Geophysics · Physics 2023-10-24 Ziyi Yin , Rafael Orozco , Mathias Louboutin , Felix J. Herrmann

Magnetic data inversion is an important tool in geophysics, used to infer subsurface magnetic susceptibility distributions from surface magnetic field measurements. This inverse problem is inherently ill-posed, characterized by non-unique…

Subsurface applications including geothermal, geological carbon sequestration, oil and gas, etc., typically involve maximizing either the extraction of energy or the storage of fluids. Characterizing the subsurface is extremely complex due…

Computational Engineering, Finance, and Science · Computer Science 2018-06-07 M. K. Mudunuru , S. Karra , N. Makedonska , T. Chen

Structural seismic interpretation and quantitative characterization are historically intertwined processes. The latter provides estimates of properties of the subsurface which can be used to aid structural interpretation alongside the…

Geophysics · Physics 2021-10-13 Matteo Ravasi , Claire Emma Birnie

Physicists face major challenges in modelling multi-scale phenomena that are observed in geophysical flows (e.g. in the Earth's oceans and atmosphere, or liquid planetary cores). In particular, complexities arise because geophysical fluids…

Understanding the principles of geophysical phenomena is an essential and challenging task. "Model-driven" approaches have supported the development of geophysics for a long time; however, such methods suffer from the curse of…

Geophysics · Physics 2020-09-30 Siwei Yu , Jianwei Ma

Seismic imaging is the numerical process of creating a volumetric representation of the subsurface geological structures from elastic waves recorded at the surface of the Earth. As such, it is widely utilized in the energy and construction…

Geophysics · Physics 2024-11-05 Juan Romero , Wolfgang Heidrich , Nick Luiken , Matteo Ravasi

Aircraft-based surveying to collect airborne electromagnetic data is a key method to image large swaths of the Earth's surface in pursuit of better knowledge of aquifer systems. Despite many years of advancements, 3D inversion still poses…

Simulating the flow of two fluid phases in porous media is a challenging task, especially when fractures are included in the simulation. Fractures may have highly heterogeneous properties compared to the surrounding rock matrix,…

Numerical Analysis · Mathematics 2024-07-09 Enrico Ballini , Luca Formaggia , Alessio Fumagalli , Eirik Keilegavlen , Anna Scotti

This review examined the current advancements in data-driven methods for analyzing flow and transport in porous media, which has various applications in energy, chemical engineering, environmental science, and beyond. Although there has…

Fluid Dynamics · Physics 2024-07-01 Guang Yang , Ran Xu , Yusong Tian , Songyuan Guo , Jingyi Wu , Xu Chu