Browsing by Author "Pardo, D."
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1.5D BASED INVERSION OF LOGGINGWHILEDRILLING RESISTIVITY MEASUREMENTS IN 3D FORMATIONS
Pardo, D.; TorresVerdín, C. (201706)This manuscript describes an extension of a computer method developed for the fast inversion of loggingwhiledrilling (LWD) resistivity measurements Pardo and TorresVerdín (2015); Bakr et al. (2016). The method enables ... 
2.5D Deep Learning Inversion of LWD and DeepSensing em Measurements Across Formations with Dipping Faults
Noh, Kyubo; Pardo, D.; TorresVerdin, Carlos (20220101)Deep learning (DL) inversion of induction logging measurements is used in well geosteering for realtime imaging of the distribution of subsurface electrical conductivity. We develop a DL inversion workflow to solve 2.5D ... 
3D hpAdaptive Finite Element Simulations of Bend, Step, and MagicT Electromagnetic Waveguide Structures
GomezRevuelto, I.; GarciaCastillo, L.E.; LlorenteRomano, S.; Pardo, D. (201403)Metallic rectangular waveguides are often the preferred choice on telecommunication systems and medical equipment working on the upper microwave and millimeter wave frequency bands due to the simplicity of its geometry, ... 
Adjointbased formulation for computing derivatives with respect to bed boundary positions in resistivity geophysics
ChaumontFrelet, T.; Shahriari, M.; Pardo, D. (201902)In inverse geophysical resistivity problems, it is common to optimize for specific resistivity values and bed boundary positions, as needed, for example, in geosteering applications. When using gradientbased inversion ... 
An AgentOriented Hierarchic Strategy for Solving Inverse Problems
Smolka, M.; Schaefer, R.; Paszynski, M.; Pardo, D.; AlvarezAramberri, J. (20151231)The paper discusses the complex, agentoriented hierarchic memetic strategy (HMS) dedicated to solving inverse parametric problems. The strategy goes beyond the idea of twophase global optimization algorithms. The global ... 
Approximations for traveltime, slope, curvature, and geometrical spreading of elastic waves in layered transversely isotropic media
Abedi, M.M.; Pardo, D.; Stovas, A. (202110)Each seismic body wave, including quasi compressional, shear, and converted wave modes, carries useful subsurface information. For processing, imaging, amplitude analysis, and forward modeling of each wave mode, we need ... 
Arithmetic method of doubleinjectionelectrode model for resistivity measurement through metal casing
Chen, Q.; Pardo, D.; Li, H.B.; Wang, F.R.; Ye, Q.Z. (20101231)Throughcasing resistivity (TCR) measurement instruments such as Cased Hole Formation Resistivity are extensively used for the dynamic monitoring of oil reservoirs during the production phase in oil wells to evaluate the ... 
Asymptotic Models for the Electric Potential across a Highly Conductive Casing
Erdozain, A.; Péron, V.; Pardo, D. (201807)We analyze a configuration that involves a steelcased borehole, where the casing that covers the borehole is considered as a highly conductive thin layer. We develop an asymptotic method for deriving reduced problems ... 
Automatic RedChannel underwater image restoration
Galdran, A.; Pardo, D.; Picón, A.; AlvarezGila, A. (20151231)Underwater images typically exhibit color distortion and low contrast as a result of the exponential decay that light suffers as it travels. Moreover, colors associated to different wavelengths have different attenuation ... 
Bearing assessment tool for longitudinal bridge performance
GarciaSanchez, D.; FernandezNavamuel, A.; Zamora, D.; Alvear, D.; Pardo, D. (202009)This work provides an unsupervised learning approach based on a singlevalued performance indicator to monitor the global behavior of critical components in a viaduct, such as bearings. We propose an outlier detection ... 
Borehole Resistivity Simulations of OilWater Transition Zones with a 1.5D Numerical Solver
Shahriari, M.; Pardo, D. (2020)When simulating borehole resistivity measurements in a reservoir, it is common to consider an oilwater contact (OWC) planar interface. However, this consideration can lead to an unrealistic model since in the presence of ... 
Compensation effect analysis in DIE method for throughcasing measuring formation resistivity
Qing, C.; Pardo, D.; Hongbin, L.; Furong, W. (201108)The measuring technique based on DoubleInjectionElectrodes (DIE) and its compensation arithmetic method have been proven to be very useful for eliminating the errors caused by electrodescale mechanical tolerances in ... 
Computational cost estimates for parallel shared memory isogeometric multifrontal solvers
Wozniak, M.; Kuznik, K.; Paszynski, M.; Calo, V.M.; Pardo, D. (20141231)In this paper we present computational cost estimates for parallel shared memory isogeometric multifrontal solvers. The estimates show that the ideal isogeometric shared memory parallel direct solver scales as $\mathcal{O}( ... 
Computational cost of isogeometric multifrontal solvers on parallel distributed memory machines
Wozniak, M.; Paszynski, M.; Pardo, D.; Dalcin, L.; Calo, V.M. (20151231)This paper derives theoretical estimates of the computational cost for isogeometric multifrontal direct solver executed on parallel distributed memory machines. We show theoretically that for the $C^{p1}$ global continuity ... 
A Deep Learning Approach to the Inversion of Borehole Resistivity Measurements
Shahriari, M.; Pardo, D.; Picon, A.; Galdran, A.; Del Ser, J.; TorresVerdin, C. (202004)Borehole resistivity measurements are routinely employed to measure the electrical properties of rocks penetrated by a well and to quantify the hydrocarbon pore volume of a reservoir. Depending on the degree of geometrical ... 
Deep learning driven selfadaptive hp finite element method
Paszyński, M.; Grzeszczuk, R.; Pardo, D.; Demkowicz, L. (202106)The fi nite element method (FEM) is a popular tool for solving engineering problems governed by Partial Di fferential Equations (PDEs). The accuracy of the numerical solution depends on the quality of the computational ... 
Deep learning enhanced principal component analysis for structural health monitoring
FernandezNavamuel, A.; Magalhães, Filipe; ZamoraSánchez, Diego; Omella, Ángel J.; GarciaSanchez, David; Pardo, D. (20220101)This paper proposes a Deep Learning Enhanced Principal Component Analysis (PCA) approach for outlier detection to assess the structural condition of bridges. We employ partially explainable autoencoder architecture to ... 
A Deep Neural Network as Surrogate Model for Forward Simulation of Borehole Resistivity Measurements
Shahriari, M.; Pardo, D.; Moser, B. (202001)Inverse problems appear in multiple industrial applications. Solving such inverse problems require the repeated solution of the forward problem. This is the most timeconsuming stage when employing inversion techniques, ... 
Design of Loss Functions for Solving Inverse Problems using Deep Learning
Rivera, J.A.; Pardo, D.; Alberdi, E. (202005)Solving inverse problems is a crucial task in several applications that strongly a ffect our daily lives, including multiple engineering fields, military operations, and/or energy production. There exist different methods ... 
Dimensionally adaptive hpfinite element simulation and inversion of 2D magnetotelluric measurements
AlvarezAramberri, J.; Pardo, D. (20160901)Magnetotelluric (MT) problems often contain different subdomains where the conductivity of the media depends upon one, two, or three spatial variables. Traditionally, when a MT problem incorporates a threedimensional (3D) ...