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Time-lapse electrical resistivity tomography (ERT) is a popular geophysical method to estimate three-dimensional (3D) permeability fields from electrical potential difference measurements. Traditional inversion and data assimilation methods…

Geophysics · Physics 2022-08-10 M. K. Mudunuru , E. L. D. Cromwell , H. Wang , X. Chen

Non-invasive surface wave methods have become a popular alternative to traditional invasive forms of site-characterization for inferring a site's subsurface shear wave velocity (Vs) structure. The advantage of surface wave methods over…

Geophysics · Physics 2021-04-06 Joseph P. Vantassel , Brady R. Cox

We present a method for obtaining efficient probabilistic solutions to geostatistical and linear inverse problems in spherical geometry. Our Spherical Direct Sequential Simulation (SDSSIM) framework combines information from possibly noisy…

Geophysics · Physics 2022-04-08 Mikkel Otzen , Christopher C. Finlay , Thomas Mejer Hansen

Reservoir computing typically relies on large, randomly generated reservoirs, enabling simple, often linear readouts. Over the past two decades, most constructions have exploited the freedom to select the reservoir, constrained primarily by…

Dynamical Systems · Mathematics 2026-05-26 G Manjunath , Juan-Pablo Ortega , Alma van der Merwe

This paper focuses on the denoising and enhancing of 3-D reflection seismic data. We propose a pre-processing step based on a non linear diffusion filtering leading to a better detection of seismic faults. The non linear diffusion…

Extracting subsurface velocity information from seismic data is mainly an undetermined problem that requires injecting a priori information to constrain the inversion process. Machine learning has offered a platform to do so through the…

Geophysics · Physics 2025-10-03 Xiao Ma , Shaowen Wang , Tariq Alkhalifah

Inversion of electromagnetic data finds applications in many areas of geophysics. The inverse problem is commonly solved with either deterministic optimization methods (such as the nonlinear conjugate gradient or Gauss-Newton) which are…

Geophysics · Physics 2019-12-03 Vladimir Puzyrev , Andrei Swidinsky

In this work we propose an ensemble 4D seismic history matching framework for reservoir characterization. Compared to similar existing frameworks in reservoir engineering community, the proposed one consists of some relatively new…

Data Analysis, Statistics and Probability · Physics 2017-04-25 Xiaodong Luo , Tuhin Bhakta , Morten Jakobsen , Geir Nævdal

In a previous paper, we introduced a framework for carrying out petrophysically and geologically guided geophysical inversions. In that framework, petrophysical and geological information is modelled with a Gaussian Mixture Model (GMM). In…

Geophysics · Physics 2022-03-29 Thibaut Astic , Lindsey J. Heagy , Douglas W. Oldenburg

Stochastic reservoir characterization, a critical aspect of subsurface exploration for oil and gas reservoirs, relies on stochastic methods to model and understand subsurface properties using seismic data. This paper addresses the…

Applications · Statistics 2024-03-07 Karen S Auestad , The Tien Mai , Mina Spremic , Jo Eidsvik

Full waveform inversion (FWI) is an advanced seismic inversion technique for quantitatively estimating subsurface properties. However, with FWI, it is hard to converge to a geologically-realistic subsurface model. Thus, we propose a…

Geophysics · Physics 2025-05-07 Yuanyuan Li , Hao Zhang , Zhuoqi Yan , Tariq Alkhalifah

The problem, of 2D canonical nature, examined herein in the space-frequency framework, concerns a SH-polarized plane body seismic wave propagating in a hard, non lossy half space (bedrock) containing a soft, lossy cylindrical basin of…

Geophysics · Physics 2025-07-15 Armand Wirgin

We consider the evolution of a family of 2D dispersive turbulence models. The members of this family involve the nonlinear advection of a dynamically active scalar field, the locality of the streamfunction-scalar relation is denoted by…

Fluid Dynamics · Physics 2009-02-20 Jai Sukhatme , Leslie M. Smith

For offshore structures like wind turbines, subsea infrastructure, pipelines, and cables, it is crucial to quantify the properties of the seabed sediments at a proposed site. However, data collection offshore is costly, so analysis of the…

Acoustic- and elastic-waveform inversion is an important and widely used method to reconstruct subsurface velocity image. Waveform inversion is a typical non-linear and ill-posed inverse problem. Existing physics-driven computational…

Signal Processing · Electrical Eng. & Systems 2019-06-07 Zhongping Zhang , Youzuo Lin

Rock discontinuities critically govern the mechanical behavior and stability of rock masses. Their internal distributions remain largely unobservable and are typically inferred from surface-exposed discontinuities using generative…

Machine Learning · Computer Science 2025-12-02 Han Meng , Gang Mei , Hong Tian , Nengxiong Xu , Jianbing Peng

The aim of this study is to develop and apply an autonomous approach for predicting the probability of hydrocarbon reservoirs spreading in the studied area. The methodology uses machine learning algorithms in the problem of binary…

Geophysics · Physics 2023-06-05 Dmitry Ivlev

The trade-off between image resolution and model field-of-view has long been a limitation for numerical simulations in digital rock models. A significant amount of sub-resolution pore space cannot be captured in the unresolved digital rock…

Geophysics · Physics 2025-08-27 Rui Li , Yi Yang , Wenbo Zhan , Jianhui Yang , Yingfang Zhou

Spectropolarimetric inversions are routinely used in the field of Solar Physics for the extraction of physical information from observations. The application to two-dimensional fields of view often requires the use of supercomputers with…

Solar and Stellar Astrophysics · Physics 2019-06-26 A. Asensio Ramos , C. Diaz Baso

Seismic full-waveform inversion is a core technology for obtaining high-resolution subsurface model parameters. However, its highly nonlinear characteristics and strong dependence on the initial model often lead to the inversion process…

Machine Learning · Computer Science 2026-03-25 Caiyun Liu , Siyang Pei , Qingfeng Yu , Jie Xiong
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