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Journal articles on the topic 'Multiphysical inversion'
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Zheng, Yi-kang, Chong Wang, Hao-hong Liang, Yi-bo Wang, and Rong-shu Zeng. "3D seismic forward modeling from the multiphysical inversion at the Ketzin CO2 storage site." Applied Geophysics 21, no. 3 (September 2024): 593–605. http://dx.doi.org/10.1007/s11770-024-1132-5.
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Al-Yasiri, Zainab Riyadh Shaker, Hayder Majid Mutashar, Klaus Gürlebeck, and Tom Lahmer. "Damage Sensitive Signals for the Assessment of the Conditions of Wind Turbine Rotor Blades Using Electromagnetic Waves." Infrastructures 7, no. 8 (August 12, 2022): 104. http://dx.doi.org/10.3390/infrastructures7080104.
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One of the most important renewable energy technologies used nowadays are wind power turbines. In this paper, we are interested in identifying the operating status of wind turbines, especially rotor blades, by means of multiphysical models. It is a state-of-the-art technology to test mechanical structures with ultrasonic-based methods. However, due to the density and the required high resolution, the testing is performed with high-frequency waves, which cannot penetrate the structure in depth. Therefore, there is a need to adopt techniques in the fields of multiphysical model-based inversion schemes or data-driven structural health monitoring. Before investing effort in the development of such approaches, further insights and approaches are necessary to make the techniques applicable to structures such as wind power plants (blades). Among the expected developments, further accelerations of the so-called “forward codes” for a more efficient implementation of the wave equation could be envisaged. Here, we employ electromagnetic waves for the early detection of cracks. Because in many practical situations, it is not possible to apply techniques from tomography (characterized by multiple sources and sensor pairs), we focus here on the question of whether the existence of cracks can be determined by using only one source for the sent waves.
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Colombo, Daniele, Diego Rovetta, and Ersan Turkoglu. "CSEM-regularized seismic velocity inversion: A multiscale, hierarchical workflow for subsalt imaging." GEOPHYSICS 83, no. 5 (September 1, 2018): B241—B252. http://dx.doi.org/10.1190/geo2017-0454.1.
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Seismic imaging in salt geology is complicated by highly contrasted velocity fields and irregular salt geometries, which cause complex seismic wavefield scattering. Although the imaging challenges can be addressed by advanced imaging algorithms, a fundamental problem remains in the determination of robust velocity fields in high-noise conditions. Conventional migration velocity analysis is often ineffective, and even the most advanced methods for depth-domain velocity analysis, such as full-waveform inversion, require starting from a good initial estimate of the velocity model to converge to a correct result. Nonseismic methods, such as electromagnetics, can help guide the generation of robust velocity models to be used for further processing. Using the multiphysics data acquired in the deepwater section of the Red Sea, we apply a controlled-source electromagnetic (CSEM) resistivity-regularized seismic velocity inversion for enhancing the velocity model in a complex area dominated by nappe-style salt tectonics. The integration is achieved by a rigorous approach of multiscaled inversions looping over model dimensions (1D first, followed by 3D), variable offsets and increasing frequencies, data-driven and interpretation-supported approaches, leading to a hierarchical inversion guided by a parameter sensitivity analysis. The final step of the integration consists of the inversion of seismic traveltimes subject to CSEM model constraints in which a common-structure coupling mechanism is used. Minimization is performed over the seismic data residuals and cross-gradient objective functions without inverting for the resistivity model, which is used as a reference for the seismic inversion (hierarchical approach). Results are demonstrated through depth imaging in which the velocity model derived through CSEM-regularized hierarchical inversion outperforms the results of a seismic-only derived velocity model.
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Sun, Jiajia, Daniele Colombo, Yaoguo Li, and Jeffrey Shragge. "Geophysics introduces new section on multiphysics and joint inversion." Leading Edge 39, no. 10 (October 2020): 753–54. http://dx.doi.org/10.1190/tle39100753.1.
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Geophysicists seek to extract useful and potentially actionable information about the subsurface by interpreting various types of geophysical data together with prior geologic information. It is well recognized that reliable imaging, characterization, and monitoring of subsurface systems require integration of multiple sources of information from a multitude of geoscientific data sets. With increasing data volumes and computational power, new data types, constant development of inversion algorithms, and the advent of the big data era, Geophysics editors see multiphysics integration as an effective means of meeting some of the challenges arising from imaging subsurface systems with higher resolution and reliability as well as exploring geologically more complicated areas. To advance the field of multiphysics integration and to showcase its added value, Geophysics will introduce a new section “Multiphysics and Joint Inversion” in 2021. Submissions are accepted now.
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Gao, Guozhong, Aria Abubakar, and Tarek M. Habashy. "Joint petrophysical inversion of electromagnetic and full-waveform seismic data." GEOPHYSICS 77, no. 3 (May 1, 2012): WA3—WA18. http://dx.doi.org/10.1190/geo2011-0157.1.
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Accurate determination of reservoir petrophysical parameters is of great importance for reservoir monitoring and characterization. We developed a joint inversion approach for the direct estimation of in situ reservoir petrophysical parameters such as porosity and fluid saturations by jointly inverting electromagnetic and full-waveform seismic measurements. Full-waveform seismic inversions allow the exploitation of the full content of the data so that a more accurate geophysical model can be inferred. Electromagnetic data are linked to porosity and fluid saturations through Archie’s equations, whereas seismic data are linked to them through rock-physics fluid-substitution equations. For seismic modeling, we used an acoustic approximation. Sensitivity studies combined with inversion tests show that seismic data are mainly sensitive to porosity distribution, whereas electromagnetic data are more sensitive to fluid-saturation distribution. The separate inversion of electromagnetic or seismic data is highly nonunique and thus leads to great ambiguity in the determination of porosity and fluid saturations. In our approach, we used a Gauss-Newton algorithm equipped with the multiplicative regularization and proper data-weighting scheme. We tested the implemented joint petrophysical inversion method using various synthetic models for surface and crosswell measurements. We found that the joint inversion approach provides substantial advantage for an improved estimation of porosity and fluid-saturation distributions over the one obtained from the separate inversion of electromagnetic and seismic data. This advantage is achieved by significantly reducing the ambiguity on the determination of porosity and fluid saturations using multiphysics measurements. We also carried out a study on the effects of using inaccurate petrophysical transform parameters on the inversion results. Our study demonstrated that up to 20% errors in the saturation and porosity exponents in Archie’s equations do not cause significant errors in the inversion results. On the other hand, if the bulk modulus and density of the rock matrix have a large percentage of errors (i.e., more than 5%), the inversion results will be significantly degraded. However, if the density of the rock matrix has an error of less than 2%, the joint inversion can tolerate a large percentage of errors in the bulk modulus of the rock matrix.
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Louboutin, Mathias, Ziyi Yin, Rafael Orozco, Thomas J. Grady, Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte, Olav Møyner, Gerard J. Gorman, and Felix J. Herrmann. "Learned multiphysics inversion with differentiable programming and machine learning." Leading Edge 42, no. 7 (July 2023): 474–86. http://dx.doi.org/10.1190/tle42070474.1.
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We present the Seismic Laboratory for Imaging and Modeling/Monitoring open-source software framework for computational geophysics and, more generally, inverse problems involving the wave equation (e.g., seismic and medical ultrasound), regularization with learned priors, and learned neural surrogates for multiphase flow simulations. By integrating multiple layers of abstraction, the software is designed to be both readable and scalable, allowing researchers to easily formulate problems in an abstract fashion while exploiting the latest developments in high-performance computing. The design principles and their benefits are illustrated and demonstrated by means of building a scalable prototype for permeability inversion from time-lapse crosswell seismic data, which, aside from coupling of wave physics and multiphase flow, involves machine learning.
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Tu, Xiaolei, and Michael S. Zhdanov. "Joint Gramian inversion of geophysical data with different resolution capabilities: case study in Yellowstone." Geophysical Journal International 226, no. 2 (April 5, 2021): 1058–85. http://dx.doi.org/10.1093/gji/ggab131.
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SUMMARY Joint inversion of multiphysics data is a practical approach to the integration of geophysical data, which produces models of reduced uncertainty and improved resolution. The development of effective methods of joint inversion requires considering different resolutions of different geophysical methods. This paper presents a new framework of joint inversion of multiphysics data, which is based on a novel formulation of Gramian constraints and mitigates the difference in resolution capabilities of different geophysical methods. Our approach enforces structural similarity between different model parameters through minimizing a structural Gramian term, and it also balances the different resolutions of geophysical methods using a multiscale resampling strategy. The effectiveness of the proposed method is demonstrated by synthetic model study of joint inversion of the P-wave traveltime and gravity data. We apply a novel method based on Gramian constraints and multiscale resampling to jointly invert the gravity and seismic data collected in Yellowstone national Park to image the crustal magmatic system of the Yellowstone. Our results helped to produce a consistent image of the crustal magmatic system of the Yellowstone expressed both in low-density and low-velocity anomaly just beneath the Yellowstone caldera.
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Colombo, Daniele, Diego Rovetta, Taqi Al-Yousuf, Ernesto Sandoval, Ersan Turkoglu, and Gary McNeice. "Multiple joint wavefield inversions: Theory and field data implementations." Leading Edge 39, no. 6 (June 2020): 411–21. http://dx.doi.org/10.1190/tle39060411.1.
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Accurate velocity models for the near surface and overburden are needed for seismic processing and reliable depth imaging. Seismic with multiphysics data, well logs, and geology information need to be quantitatively integrated to obtain high-resolution velocity models. We detail our development and application of the joint wavefield inversion software platform, which enables flexible algorithmic schemes for the integration of multiparameter data and constraints. Inversion is performed in cascade or simultaneously using a variety of input data to constrain the velocity field reconstruction at multiple scales. Coupling mechanisms based on structure similarity together with rock-physics relations are optimally combined to boost resolution and enhance accuracy of the inverted velocity models. Ill-posed inversion problems are then solved using extensive geologic and rock-physics regularization instead of relying on smoothness constraints alone. We detail workflows and algorithms to guide the application of multiparameter joint inversion for velocity model building whether the input data are seismic traveltimes, electromagnetics (time/frequency domains), gravity, and/or surface waves. Extensive applications of multiparameter joint inversion are presented for a variety of complex geologic scenarios in which various multiparameter coupling strategies are illustrated. Robust velocity modeling and enhanced seismic imaging in time and depth domains are obtained as a result, proving the importance of multiphysics integration for reliable earth model parameter estimation.
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Zhdanov, Michael S., Michael Jorgensen, and Leif Cox. "Advanced Methods of Joint Inversion of Multiphysics Data for Mineral Exploration." Geosciences 11, no. 6 (June 21, 2021): 262. http://dx.doi.org/10.3390/geosciences11060262.
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Different geophysical methods provide information about various physical properties of rock formations and mineralization. In many cases, this information is mutually complementary. At the same time, inversion of the data for a particular survey is subject to considerable uncertainty and ambiguity as to causative body geometry and intrinsic physical property contrast. One productive approach to reducing uncertainty is to jointly invert several types of data. Non-uniqueness can also be reduced by incorporating additional information derived from available geological and/or geophysical data in the survey area to reduce the searching space for the solution. This additional information can be incorporated in the form of a joint inversion of multiphysics data. This paper presents an overview of the main ideas and principles of novel methods of joint inversion, developed over the last decade, which do not require a priori knowledge about specific empirical or statistical relationships between the different model parameters and/or their attributes. These approaches are designated as follows: (1) Gramian constraints; (2) Gramian-based structural constraints; (3) localized Gramian constraints; and (4) joint focusing constraints. We provide a short description of the mathematical foundations of each of these approaches and discuss the practical aspects of their applications in mineral exploration.
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Wu, Pingping, Handong Tan, Changhong Lin, Miao Peng, Huan Ma, and Zhengwen Yan. "Joint inversion of two-dimensional magnetotelluric and surface wave dispersion data with cross-gradient constraints." Geophysical Journal International 221, no. 2 (January 25, 2020): 938–50. http://dx.doi.org/10.1093/gji/ggaa045.
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SUMMARY Multiphysics imaging for data inversion is of growing importance in many branches of science and engineering. Cross-gradient constraint has been considered as a feasible way to reduce the non-uniqueness problem inherent in inversion process by finding geometrically consistent images from multigeophysical data. Based on OCCAM inversion algorithm, a direct inversion method of 2-D profile velocity structure with surface wave dispersion data is proposed. Then we jointly invert the profiles of magnetotelluric and surface wave dispersion data with cross-gradient constraints. Three synthetic models, including block homogeneous or heterogeneous models with consistent or inconsistent discontinuities in velocity and resistivity, are presented to gauge the performance of the joint inversion scheme. We find that owning to the complementary advantages of the two geophysical data sets, the models recovered with structure coupling constraints exhibit higher resolution in the classification of complex geologic units and settle some imaging problems caused by the separate inversion methods. Finally, a realistic velocity model from the NE Tibetan Plateau and its corresponding resistivity model calculated by empirical law are used to test the effectiveness of the joint inversion scheme in the real geological environment.
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Domenzain, Diego, John Bradford, and Jodi Mead. "Joint full-waveform ground-penetrating radar and electrical resistivity inversion applied to field data acquired on the surface." GEOPHYSICS 87, no. 1 (November 18, 2021): K1—K17. http://dx.doi.org/10.1190/geo2021-0161.1.
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We exploit the different but complementary data sensitivities of ground-penetrating radar (GPR) and electrical resistivity (ER) by applying a multiphysics, multiparameter, simultaneous 2.5D joint inversion without invoking petrophysical relationships. Our method joins full-waveform inversion (FWI) GPR with adjoint derived ER sensitivities on the same computational domain. We incorporate a stable source estimation routine into the FWI-GPR. We apply our method in a controlled alluvial aquifer using only surface-acquired data. The site exhibits a shallow groundwater boundary and unconsolidated heterogeneous alluvial deposits. We compare our recovered parameters to individual FWI-GPR and ER results, and we compare them to log measurements of capacitive conductivity and neutron-derived porosity. Our joint inversion provides a more representative depiction of subsurface structures because it incorporates multiple intrinsic parameters, and it is therefore superior to an interpretation based on log data, FWI-GPR, or ER alone.
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Miotti, Fabio, Andrea Zerilli, Paulo T. L. Menezes, João L. S. Crepaldi, and Adriano R. Viana. "A new petrophysical joint inversion workflow: Advancing on reservoir’s characterization challenges." Interpretation 6, no. 3 (August 1, 2018): SG33—SG39. http://dx.doi.org/10.1190/int-2017-0225.1.
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Reservoir characterization objectives are to understand the reservoir rocks and fluids through accurate measurements to help asset teams develop optimal production decisions. Within this framework, we develop a new workflow to perform petrophysical joint inversion (PJI) of seismic and controlled-source electromagnetic (CSEM) data to resolve for reservoirs properties. Our workflow uses the complementary information contained in seismic, CSEM, and well-log data to improve the reservoir’s description drastically. The advent of CSEM, measuring resistivity, brought the possibility of integrating multiphysics data within the characterization workflow, and it has the potential to significantly enhance the accuracy at which reservoir properties and saturation, in particular, can be determined. We determine the power of PJI in the retrieval of reservoir parameters through a case study, based on a deepwater oil field offshore Brazil in the Sergipe-Alagoas Basin, to augment the certainty with which reservoir lithology and fluid properties are constrained.
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Shahjahan, Abu Taib Mohammed, Khandaker Shabbir Ahmed, and Ismail Bin Said. "Study on Riparian Shading Envelope for Wetlands to Create Desirable Urban Bioclimates." Atmosphere 11, no. 12 (December 12, 2020): 1348. http://dx.doi.org/10.3390/atmos11121348.
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Climate change and rapid urbanization are adversely affecting the urban environment by exacerbating the widely reported urban heat island effect in Dhaka, Bangladesh. Two wetland areas with variable riparian shadings in the warm-humid conditions of urban Dhaka were investigated through field campaigns on microclimatic parameters for their cooling potential on the surrounding urban fabric. It was observed that an inversion layer of fully saturated air develops over the water surface of wetland, suppressing evaporation from the wetland water surface layer, which was effectively reducing the heat exchange between the water surface and the air layer above it through its action as an insulating vapor blanket. Due to this effect, the wetland was unable to render as a source of coolth for the surrounding overheated urban area. This effect of the inversion layer was more pronounced in the urban wetland without riparian shading either by the urban form or tree canopy. A multiphysics simulation study conducted on the selected urban wetlands indicates the effect of differential shading pattern on the relation between fetch and inversion layer thickness. This research hypothesizes that the wetland can act as an urban adaption measure against the urban heat island effect by potentially transforming them into an urban cooling island (UCI) towards a favorable urban bioclimate.
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Parnow, Saeed, Behrooz Oskooi, and Giovanni Florio. "Improved linear inversion of low induction number electromagnetic data." Geophysical Journal International 224, no. 3 (November 10, 2020): 1505–22. http://dx.doi.org/10.1093/gji/ggaa531.
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SUMMARY We define a two-step procedure to obtain reliable inverse models of the distribution of electrical conductivity at depth from apparent conductivities estimated by electromagnetic instruments such as GEONICS EM38, EM31 or EM 34-3. The first step of our procedure consists in the correction of the apparent conductivities to make them consistent with a low induction number condition, for which these data are very similar to the true conductivity. Then, we use a linear inversion approach to obtain a conductivity model. To improve the conductivity estimation at depth we introduced a depth-weighting function in our regularized weighted minimum length solution algorithm. We test the whole procedure on two synthetic data sets generated by the COMSOL Multiphysics for both the vertical magnetic dipole and horizontal magnetic dipole configurations of the loops. Our technique was also tested on a real data set, and the inversion result has been compared with the one obtained using the dipole-dipole DC electrical resistivity (ER) method. Our model not only reproduces all shallow conductive areas similar to the ER model, but also succeeds in replicating its deeper conductivity structures. On the contrary, inversion of uncorrected data provides a biased model underestimating the true conductivity.
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McAliley, Wallace Anderson, and Yaoguo Li. "Methods to Invert Temperature Data and Heat Flow Data for Thermal Conductivity in Steady-State Conductive Regimes." Geosciences 9, no. 7 (July 3, 2019): 293. http://dx.doi.org/10.3390/geosciences9070293.
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Temperature and heat flow data carry specific information about the distribution of thermal conductivity variations which is not available in other geophysical data sets. Thus, thermal data constitute important complementary data sets in the multiphysics-based imaging and characterization of earth’s subsurface. The quantitative interpretations that accompany this effort can be carried out by determining thermal conductivities from temperature or heat flow data. Towards this goal, we develop inversion methods based on Tikhonov regularization and numerical solution of the differential equations governing the steady-state heat equation. Numerical simulations using these methods yield insights into the information content in thermal data and indicate it is similar to that in potential-field data. We apply the temperature inversion method to borehole temperature data from the Cooper Basin in Australia, a well-studied geothermal prospect. The methods and insights presented in this study pave the way for imaging the subsurface through recovered thermal conductivities and for joint quantitative interpretations of thermal data with other common geophysical data sets in various geoscientific applications.
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Shahin, Alireza, Michael T. Myers, and Lori A. Hathon. "Borehole Geophysical Joint Inversion to Fully Evaluate Shaly Sandstone Formations." Applied Sciences 12, no. 3 (January 25, 2022): 1255. http://dx.doi.org/10.3390/app12031255.
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Simultaneous inversion of sonic, density, and electrical resistivity borehole-derived well logs, has been addressed in literature in recent years. However, this problem is not broadly studied for dual-porosity sandstone formations. In addition, most authors presumed salinity and matrix properties as known parameters in their studies. We integrate the conservation of mass to model density, a differential effective medium theory for elastic modeling, and a laboratory-supported model for electrical resistivity of dual-porosity sandstones. Utilizing this methodology, we simulate electrical resistivity, sonic, and density well-log data. We develop a stochastic global search engine to jointly invert petrophysical properties. We build a dual-porosity formation with associated petrophysical properties and show the proposed workflow accurately replicates true well-log responses in the oil column, water leg, and transition zone. Local petrophysical properties (microporosity, intergranular porosity, total porosity, and water saturation) and global model parameters (salinity, matrix properties, critical porosity, resistivity lithology exponents, and sonic length scales for different pore networks) are all well recovered. The developed multiphysics calibrated rock models will assist petrophysicists and seismic analysts to identify and distinguish sandstone facies characteristics from well-log and prestack seismic data.
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Liang, Lin, Aria Abubakar, and Tarek M. Habashy. "Reservoir property mapping and monitoring from joint inversion of time-lapse seismic, electromagnetic, and production data." GEOPHYSICS 81, no. 5 (September 2016): ID73—ID84. http://dx.doi.org/10.1190/geo2015-0620.1.
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We have developed a deterministic multiphysics joint inversion approach integrating seismic, electromagnetic (EM), and production data to map relevant reservoir properties, such as permeability and porosity, and the time evolution of the flooding front movement, i.e., saturation changes with time. These measurements are complementary in terms of their sensitivity to individual reservoir properties and their coverage of reservoir volumes. As a consequence, integration reduces ambiguities in the interpretation. In the workflow, a reservoir model is first built based on prior information. The production data are simulated by evolving the model in time based on the known well-control strategy. Simultaneously, the temporal and spatial distribution of fluid properties, such as saturation, salt concentration, density, and pressure are also obtained from the forward modeling. These properties, together with in situ rock properties, are transformed to formation resistivity and elastic properties using prescribed petrophysical relationships, such as Archie’s law and effective medium rock-physics models. From the transformation results, synthetic EM and full-waveform seismic data can be subsequently simulated. A Gauss-Newton optimization scheme is used to iteratively update the reservoir permeability and porosity fields until the mismatch between the synthetic data and the observed data becomes less than a predefined threshold. This inverse problem is usually highly underdetermined; hence, it is necessary to bring in prior information to further constrain the inversion. Different regularization approaches are investigated to facilitate incorporation of prior information into the joint inversion algorithm.
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Zhu, Hongyu, Noemi Petra, Georg Stadler, Tobin Isaac, Thomas J. R. Hughes, and Omar Ghattas. "Inversion of geothermal heat flux in a thermomechanically coupled nonlinear Stokes ice sheet model." Cryosphere 10, no. 4 (July 13, 2016): 1477–94. http://dx.doi.org/10.5194/tc-10-1477-2016.
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Abstract. We address the inverse problem of inferring the basal geothermal heat flux from surface velocity observations using a steady-state thermomechanically coupled nonlinear Stokes ice flow model. This is a challenging inverse problem since the map from basal heat flux to surface velocity observables is indirect: the heat flux is a boundary condition for the thermal advection–diffusion equation, which couples to the nonlinear Stokes ice flow equations; together they determine the surface ice flow velocity. This multiphysics inverse problem is formulated as a nonlinear least-squares optimization problem with a cost functional that includes the data misfit between surface velocity observations and model predictions. A Tikhonov regularization term is added to render the problem well posed. We derive adjoint-based gradient and Hessian expressions for the resulting partial differential equation (PDE)-constrained optimization problem and propose an inexact Newton method for its solution. As a consequence of the Petrov–Galerkin discretization of the energy equation, we show that discretization and differentiation do not commute; that is, the order in which we discretize the cost functional and differentiate it affects the correctness of the gradient. Using two- and three-dimensional model problems, we study the prospects for and limitations of the inference of the geothermal heat flux field from surface velocity observations. The results show that the reconstruction improves as the noise level in the observations decreases and that short-wavelength variations in the geothermal heat flux are difficult to recover. We analyze the ill-posedness of the inverse problem as a function of the number of observations by examining the spectrum of the Hessian of the cost functional. Motivated by the popularity of operator-split or staggered solvers for forward multiphysics problems – i.e., those that drop two-way coupling terms to yield a one-way coupled forward Jacobian – we study the effect on the inversion of a one-way coupling of the adjoint energy and Stokes equations. We show that taking such a one-way coupled approach for the adjoint equations can lead to an incorrect gradient and premature termination of optimization iterations. This is due to loss of a descent direction stemming from inconsistency of the gradient with the contours of the cost functional. Nevertheless, one may still obtain a reasonable approximate inverse solution particularly if important features of the reconstructed solution emerge early in optimization iterations, before the premature termination.
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Yang, Jixin, Pengliang Yu, Suran Wang, and Zheng Sun. "CO2 Storage Monitoring via Time-Lapse Full Waveform Inversion with Automatic Differentiation." Nanomaterials 14, no. 2 (January 7, 2024): 138. http://dx.doi.org/10.3390/nano14020138.
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In the field of CO2 capture utilization and storage (CCUS), recent advancements in active-source monitoring have significantly enhanced the capabilities of time-lapse acoustical imaging, facilitating continuous capture of detailed physical parameter images from acoustic signals. Central to these advancements is time-lapse full waveform inversion (TLFWI), which is increasingly recognized for its ability to extract high-resolution images from active-source datasets. However, conventional TLFWI methodologies, which are reliant on gradient optimization, face a significant challenge due to the need for complex, explicit formulation of the physical model gradient relative to the misfit function between observed and predicted data over time. Addressing this limitation, our study introduces automatic differentiation (AD) into the TLFWI process, utilizing deep learning frameworks such as PyTorch to automate gradient calculation using the chain rule. This novel approach, AD-TLFWI, not only streamlines the inversion of time-lapse images for CO2 monitoring but also tackles the issue of local minima commonly encountered in deep learning optimizers. The effectiveness of AD-TLFWI was validated using a realistic model from the Frio-II CO2 injection site, where it successfully produced high-resolution images that demonstrate significant changes in velocity due to CO2 injection. This advancement in TLFWI methodology, underpinned by the integration of AD, represents a pivotal development in active-source monitoring systems, enhancing information extraction capabilities and providing potential solutions to complex multiphysics monitoring challenges.
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Qamar, Aamir, Inzamam Ul Haq, Majed Alhaisoni, and Nadia Nawaz Qadri. "Detecting Grounding Grid Orientation: Transient Electromagnetic Approach." Applied Sciences 9, no. 24 (December 4, 2019): 5270. http://dx.doi.org/10.3390/app9245270.
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The configuration is essential to diagnose the status of the grounding grid, but the orientation of the unknown grounding grid is ultimately required to diagnose its configuration explicitly. This paper presents a transient electromagnetic method (TEM) to determine grounding grid orientation without excavation. Unlike the existing pathological solutions, TEM does not enhance the surrounding electromagnetic environment. A secondary magnetic field as a consequence of induced eddy currents is subjected to inversion calculation. The orientation of the grounding grid is diagnosed from the equivalent resistivity distribution against the circle perimeter. High equivalent resistivity at a point on the circle implies the grounding grid conductor and vice versa. Furthermore, various mesh configurations including the presence of a diagonal branch and unequal mesh spacing are taken into account. Simulations are performed using COMSOL Multiphysics and MATLAB to verify the usefulness of the proposed method.
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Tetik, Evrim, and Ibrahim Akduman. "3D Imaging of Dielectric Objects Buried under a Rough Surface by Using CSI." International Journal of Antennas and Propagation 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/179304.
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A 3D scalar electromagnetic imaging of dielectric objects buried under a rough surface is presented. The problem has been treated as a 3D scalar problem for computational simplicity as a first step to the 3D vector problem. The complexity of the background in which the object is buried is simplified by obtaining Green’s function of its background, which consists of two homogeneous half-spaces, and a rough interface between them, by using Buried Object Approach (BOA). Green’s function of the two-part space with planar interface is obtained to be used in the process. Reconstruction of the location, shape, and constitutive parameters of the objects is achieved by Contrast Source Inversion (CSI) method with conjugate gradient. The scattered field data that is used in the inverse problem is obtained via both Method of Moments (MoM) and Comsol Multiphysics pressure acoustics model.
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Astic, Thibaut, Dominique Fournier, and Douglas W. Oldenburg. "Joint inversion of potential-fields data over the DO-27 kimberlite pipe using a Gaussian mixture model prior." Interpretation 8, no. 4 (October 12, 2020): SS47—SS62. http://dx.doi.org/10.1190/int-2019-0283.1.
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We have carried out petrophysically and geologically guided inversions (PGIs) to jointly invert airborne and ground-based gravity data and airborne magnetic data to recover a quasi-geology model of the DO-27 kimberlite pipe in the Tli Kwi Cho (also referred to as TKC) cluster. DO-27 is composed of three main kimberlite rock types in contact with each other and embedded in a granitic host rock covered by a thin layer of glacial till. The pyroclastic kimberlite (PK), which is diamondiferous, and the volcanoclastic kimberlite (VK) have anomalously low density, due to their high porosity, and weak magnetic susceptibility. They are indistinguishable from each other based upon their potential-field responses. The hypabyssal kimberlite (HK), which is not diamondiferous, has been identified as highly magnetic and remanent. Quantitative petrophysical signatures for each rock unit are obtained from sample measurements, such as the increasing density of the PK/VK unit with depth and the remanent magnetization of the HK unit, and are represented as a Gaussian mixture model (GMM). This GMM guides the PGI toward generating a 3D quasi-geology model with physical properties that satisfies the geophysical data sets and the petrophysical signatures. Density and magnetization models recovered individually yield volumes that have physical property combinations that do not conform to any known petrophysical characteristics of the rocks in the area. A multiphysics PGI addresses this problem by using the GMM as a coupling term, but it puts a volume of the PK/VK unit at a location that is incompatible with geologic information from drillholes. To conform to that geologic knowledge, a fourth unit is introduced, PK-minor, which is petrophysically and geographically distinct from the main PK/VK unit. This inversion produces a quasi-geology model that presents good structural locations of the diamondiferous PK unit and can be used to provide a resource estimate or decide the locations of future drillholes.
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Zhdanov, Michael, Fouzan Alfouzan, Leif Cox, Abdulrahman Alotaibi, Mazen Alyousif, David Sunwall, and Masashi Endo. "Large-Scale 3D Modeling and Inversion of Multiphysics Airborne Geophysical Data: A Case Study from the Arabian Shield, Saudi Arabia." Minerals 8, no. 7 (June 27, 2018): 271. http://dx.doi.org/10.3390/min8070271.
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Gasperikova, Erika, and Yaoguo Li. "Time-lapse electromagnetic and gravity methods in carbon storage monitoring." Leading Edge 40, no. 6 (June 2021): 442–46. http://dx.doi.org/10.1190/tle40060442.1.
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For geologic carbon storage (GCS), monitoring of the storage reservoir and detection of secondary plumes if they accumulate outside of the reservoir are important to confirm that the injected CO2 stays where intended. Seismic methods are most often applied but are expensive. Due to cost considerations, especially for long-term monitoring, less expensive techniques play a role when designing monitoring networks. In this article, the merits of gravity and electromagnetic (EM) methods as monitoring tools for GCS are presented. Many of the technologies are well established, and several new technologies are on the horizon. EM and gravity techniques are complementary to seismic methods and together provide better subsurface monitoring. Time-lapse multiphysics joint inversion, including seismic, EM, and gravity, could be a game changer for carbon storage monitoring. The trade-off between the sensitivity or resolution to a given plume size and the associated costs will be an important factor in selecting efficient and reliable monitoring arrays at GCS sites. Complex digital models representing geology encountered at storage sites can be used for this purpose and present another cost savings.
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Rac-Rumijowska, Olga, Piotr Pokryszka, Tomasz Rybicki, Patrycja Suchorska-Woźniak, Maksymilian Woźniak, Katarzyna Kaczkowska, and Iwona Karbownik. "Influence of Flexible and Textile Substrates on Frequency-Selective Surfaces (FSS)." Sensors 24, no. 5 (March 6, 2024): 1704. http://dx.doi.org/10.3390/s24051704.
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Frequency-selective surfaces (FSS) are two-dimensional geometric structures made of conductive materials that selectively transmit or reflect electromagnetic waves. In this paper, flexible FSS made on textile and film substrates is presented and compared to show the effect of the texture associated with the type of substrate on the shielding properties. Three geometries of patterns of squares in the border, inversion of squares in the border, and circles with a border were used, and the patterns were made by the silver paste screen printing technique. Microscopic analysis (SEM and optical) was performed to determine the degree of substrate coverage and the actual geometry of the pattern. The resistance per square of the obtained patterns was about 50 mΩ/□. The shielding properties of FSS were simulated in Comsol Multiphysics 6.2 software and then measured by the antenna method. Selective textile filters were obtained, depending on the pattern used, with one or two modals with a transmission attenuation of about 15 dB. The paper analyzes the effect of the substrate and the screen printing technique used on the shielding properties of the flexible FSS.
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Maillard, Julia, Jean-Christophe Raut, and François Ravetta. "Evaluation and development of surface layer scheme representation of temperature inversions over boreal forests in Arctic wintertime conditions." Geoscientific Model Development 17, no. 8 (April 26, 2024): 3303–20. http://dx.doi.org/10.5194/gmd-17-3303-2024.
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Abstract. In this study, the Noah land surface model used in conjunction with the Mellor–Yamada–Janjić surface layer scheme (hereafter, Noah-MYJ) and the Noah multiphysics scheme (Noah-MP) from the Weather Research and Forecasting (WRF) 4.5.1 mesoscale model are evaluated with regard to their performance in reproducing positive temperature gradients over forested areas in the Arctic winter. First, simplified versions of the WRF schemes, recoded in Python, are compared with conceptual models of the surface layer in order to gain insight into the dependence of the temperature gradient on the wind speed at the top of the surface layer. It is shown that the WRF schemes place strong limits on the turbulent collapse, leading to lower surface temperature gradient at low wind speeds than in the conceptual models. We implemented modifications to the WRF schemes to correct this effect. The original and modified versions of Noah-MYJ and Noah-MP are then evaluated compared to long-term measurements at the Ameriflux Poker Flat Research Range, a forest site in interior Alaska. Noah-MP is found to perform better than Noah-MYJ because the former is a two-layer model which explicitly takes into account the effect of the forest canopy. Indeed, a non-negligible temperature gradient is maintained below the canopy at high wind speeds, leading to overall larger gradients than in the absence of vegetation. Furthermore, the modified versions are found to perform better than the original versions of each scheme because they better reproduce strong temperature gradients at low wind speeds.
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Khosro Anjom, Farbod, Thomas Jules Browaeys, and Laura Valentina Socco. "Multimodal surface-wave tomography to obtain S- and P-wave velocities applied to the recordings of unmanned aerial vehicle deployed sensors." GEOPHYSICS 86, no. 4 (June 10, 2021): R399—R412. http://dx.doi.org/10.1190/geo2020-0703.1.
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Exploration seismic surveys in hard-to-access areas such as foothills and forests are extremely challenging. The Multiphysics Exploration Technologies Integrated System (METIS) research project was initiated to design an exploration system, facilitating the acquisition in these areas by delivering the receivers from the sky using unmanned aerial vehicles. Air dropping of the sensors in vegetated areas results in an irregular geometry for the acquisition. This irregularity can limit the application of conventional surface wave methods. We have developed a surface wave workflow for estimating the S-wave velocity ([Formula: see text]) and P-wave velocity ([Formula: see text]) models and that supports the irregular geometry of the deployed sources and receivers. The method consists of a multimodal surface-wave tomography (SWT) technique to compute the [Formula: see text] model and a data transform method (the wavelength/depth [W/D] method) to determine the Poisson’s ratio and [Formula: see text] model. We applied the method to the METIS’s first pilot records, which were acquired in the forest of Papua New Guinea. Application of SWT to the data resulted in the first 90 m of the [Formula: see text] model. The W/D method provided the Poisson’s ratio averaged over the area and the [Formula: see text] model between 10 and 70 m from the surface. The impact of the acquisition scale and layout on the resolution of the estimated model and the advantages of including the higher modes of surface waves in the tomographic inversion are assessed in detail. The presence of shots from diverse site locations significantly improves the resolution of the obtained model. Including the higher modes enhances the data coverage and increases the investigation depth.
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Bolève, A., A. Revil, F. Janod, J. L. Mattiuzzo, and A. Jardani. "A new formulation to compute self-potential signals associated with ground water flow." Hydrology and Earth System Sciences Discussions 4, no. 3 (June 8, 2007): 1429–63. http://dx.doi.org/10.5194/hessd-4-1429-2007.
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Abstract. The classical formulation of the coupled hydroelectrical flow in porous media is based on a linear formulation of two coupled constitutive equations for the electrical current density and the seepage velocity of the water phase and obeying Onsager's reciprocity. This formulation shows that the streaming current density is controlled by the gradient of the fluid pressure of the water phase and a streaming current coupling coefficient that depends on the so-called zeta potential. Recently a new formulation has been introduced in which the streaming current density is directly connected to the seepage velocity of the water phase and to the excess of electrical charge per unit pore volume in the porous material. The advantages of this formulation are numerous. First this new formulation is more intuitive not only in terms of constitutive equation for the generalized Ohm's law but also in specifying boundary conditions for the influence of the flow field upon the streaming potential. With the new formulation, the streaming potential coupling coefficient shows a decrease of its magnitude with permeability in agreement with published results. The new formulation is also easily extendable to non-viscous laminar flow problems (high Reynolds number ground water flow in cracks for example) and to unsaturated conditions with applications to the vadose zone. We demonstrate here that this formulation is suitable to model self-potential signals in the field. We investigate infiltration of water from an agricultural ditch, vertical infiltration of water into a sinkhole, and preferential horizontal flow of ground water in a paleochannel. For the three cases reported in the present study, a good match is obtained between the finite element simulations performed with the finite element code Comsol Multiphysics 3.3 and field observations. Finally, this formulation seems also very promising for the inversion of the geometry of ground water flow from the monitoring of self-potential signals.
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Alvarez, Pedro, Amanda Alvarez, Lucy MacGregor, Francisco Bolivar, Robert Keirstead, and Thomas Martin. "Reservoir properties prediction integrating controlled-source electromagnetic, prestack seismic, and well-log data using a rock-physics framework: Case study in the Hoop Area, Barents Sea, Norway." Interpretation 5, no. 2 (May 31, 2017): SE43—SE60. http://dx.doi.org/10.1190/int-2016-0097.1.
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We have developed an example from the Hoop Area of the Barents Sea showing a sequential quantitative integration approach to integrate seismic and controlled-source electromagnetic (CSEM) attributes using a rock-physics framework. The example illustrates a workflow to address the challenges of multiphysics and multiscale data integration for reservoir characterization purposes. A data set consisting of 2D GeoStreamer seismic and towed streamer electromagnetic data that were acquired concurrently in 2015 by PGS provide the surface geophysical measurements that we used. Two wells in the area — Wisting Central (7324/8-1) and Wisting Alternative (7324/7-1S) — provide calibration for the rock-physics modeling and the quantitative integrated analysis. In the first stage of the analysis, we invert prestack seismic and CSEM data separately for impedance and anisotropic resistivity, respectively. We then apply the multi-attribute rotation scheme (MARS) to estimate rock properties from seismic data. This analysis verified that the seismic data alone cannot distinguish between commercial and noncommercial hydrocarbon saturation. Therefore, in the final stage of the analysis, we invert the seismic and CSEM-derived properties within a rock-physics framework. The inclusion of the CSEM-derived resistivity information within the inversion approach allows for the separation of these two possible scenarios. Results reveal excellent correlation with known well outcomes. The integration of seismic, CSEM, and well data predicts very high hydrocarbon saturations at Wisting Central and no significant saturation at Wisting Alternative, consistent with the findings of each well. Two further wells were drilled in the area and used as blind tests in this case: The slightly lower saturation predicted at Hanssen (7324/7-2) is related to 3D effects in the CSEM data, but the positive outcome of the well is correctly predicted. At Bjaaland (7324/8-2), although the seismic indications are good, the integrated interpretation result predicts correctly that this well was unsuccessful.
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Xu, Taibai, Qingmin Pan, and Yongzong Lu. "Heat Transfer Process of the Tea Plant under the Action of Air Disturbance Frost Protection." Agronomy 14, no. 5 (May 2, 2024): 959. http://dx.doi.org/10.3390/agronomy14050959.
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Wind machines based on the air disturbance method are progressively employed to mitigate frost damage within the agricultural machinery frost protection. These devices are utilized during radiative frost nights to disrupt near-surface thermal inversion through air mixing. Despite this application, the fundamental mechanisms underlying these mixing processes are not well comprehended. In this research, numerical simulations were conducted using COMSOL Multiphysics software version 6.0 to simulate the flow and heat transfer processes between the thermal airflow and both the tea canopy and stems. The results indicated that due to obstruction from the canopy cross-section, the airflow velocity on the contact surface rapidly increased. As the airflow further progressed, the high-speed region of the airflow gradually approached the canopy surface. Turbulent kinetic energy increased initially on the windward side of the canopy cross-section and near the top interface. On the windward side of the canopy, due to the initial impact of the thermal airflow, rapid heating occurred, resulting in a noticeable temperature difference between the windward and leeward sides within a short period. In the interaction between airflow and stems, with increasing airflow velocity, fluctuations and the shedding of wake occurred on the leeward side of the stems. The maximum sensible heat flux at the windward vertex of the stem increased significantly with airflow velocity. At an airflow velocity of 2.0 m/s, the maximum heat flux value was 2.37 times that of an airflow velocity of 1.0 m/s. This research utilized simulation methods to study the interaction between airflow and tea canopy and stems in frost protection, laying the foundation for further research on the energy distribution in tea ecosystem under the disturbance of airflow for frost protection.
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Lu, Yongling, Zhen Wang, Xueqiong Zhu, Chengbo Hu, Jinggang Yang, and Yipeng Wu. "Vibration Energy Harvesting from the Subwavelength Interface State of a Topological Metamaterial Beam." Micromachines 13, no. 6 (May 30, 2022): 862. http://dx.doi.org/10.3390/mi13060862.
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Topological metamaterial has been a research hotpot in both physics and engineering due to its unique ability of wave manipulation. The topological interface state, which can efficiently and robustly centralize the elastic wave energy, is promising to attain high-performance energy harvesting. Since most of environmental vibration energy is in low frequency range, the interface state is required to be designed at subwavelength range. To this end, this paper developed a topological metamaterial beam with local resonators and studied its energy-harvesting performance. First, the unit cell of this topological metamaterial beam consists of a host beam with two pairs of parasitic beams with tip mass. Then, the band structure and topological features are determined. It is revealed that by tuning the distance between these two pairs of parasitic beams, band inversion where topological features inverse can be obtained. Then, two sub-chains, their design based on two topologically distinct unit cells, are assembled together with a piezoelectric transducer placed at the conjunction, yielding the locally resonant, topological, metamaterial, beam-based piezoelectric energy harvester. After that, its transmittance property and output power were obtained by using the frequency domain analysis of COMSOL Multiphysics. It is clear that the subwavelength interface state is obtained at the band-folding bandgap. Meanwhile, in the interface state, elastic wave energy is successfully centralized at the conjunction. From the response distribution, it is found that the maximum response takes place on the parasitic beam rather than the host beam. Therefore, the piezoelectric transducer is recommended to be placed on the parasitic beam rather than host beam. Finally, the robustness of the topological interface state and its potential advantages on energy harvesting were studied by introducing a local defect. It is clear that in the interface state, the maximum response is always located at the conjunction regardless of the defect degree and location. In other words, the piezoelectric transducer placed at the conjunction can maintain a stable and high-efficiency output power in the interface state, which makes the whole system very reliable in practical implementation.
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Wiese, Bernd, Wolfgang Weinzierl, and Cornelia Schmidt-Hattenberger. "Towards a Multiphysical Model and Inversion of the Ketzin CO2 Storage Site Full Operational Period." SSRN Electronic Journal, 2019. http://dx.doi.org/10.2139/ssrn.3366206.
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Zhang, Rongzhe, Tonglin Li, and Cai Liu. "Joint Inversion of Multiphysical Parameters Based on a Combination of Cosine Dot-Gradient and Joint Total Variation Constraints." IEEE Transactions on Geoscience and Remote Sensing, 2021, 1–10. http://dx.doi.org/10.1109/tgrs.2021.3071498.
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Yin, Ziyi, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann. "Solving multiphysics-based inverse problems with learned surrogates and constraints." Advanced Modeling and Simulation in Engineering Sciences 10, no. 1 (October 11, 2023). http://dx.doi.org/10.1186/s40323-023-00252-0.
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AbstractSolving 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 computationally cheap learned surrogates with learned constraints. Not only does this combination lead to vastly improved inversions for the important fluid-flow property, permeability, it also provides a natural platform for inverting multimodal data including well measurements and active-source time-lapse seismic data. By adding a learned constraint, we arrive at a computationally feasible inversion approach that remains accurate. This is accomplished by including a trained deep neural network, known as a normalizing flow, which forces the model iterates to remain in-distribution, thereby safeguarding the accuracy of trained Fourier neural operators that act as surrogates for the computationally expensive multiphase flow simulations involving partial differential equation solves. By means of carefully selected experiments, centered around the problem of geological carbon storage, we demonstrate the efficacy of the proposed constrained optimization method on two different data modalities, namely time-lapse well and time-lapse seismic data. While permeability inversions from both these two modalities have their pluses and minuses, their joint inversion benefits from either, yielding valuable superior permeability inversions and CO2 plume predictions near, and far away, from the monitoring wells.
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Zhdanov, Michael S., Michael Jorgensen, and Mo Tao. "Probabilistic approach to Gramian inversion of multiphysics data." Frontiers in Earth Science 11 (February 28, 2023). http://dx.doi.org/10.3389/feart.2023.1127597.
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We consider a probabilistic approach to the joint inversion of multiphysics data based on Gramian constraints. The multiphysics geophysical survey represents the most effective technique for geophysical exploration because different physical data reflect distinct physical properties of the various components of the geological system. By joint inversion of the multiphysics data, one can produce enhanced subsurface images of the physical properties distribution, which improves our ability to explore natural resources. One powerful method of joint inversion is based on Gramian constraints. This technique enforces the relationships between different model parameters during the inversion process. We demonstrate that the Gramian can be interpreted as a determinant of the covariance matrix between different physical models representing the subsurface geology in the framework of the probabilistic approach to inversion theory. This interpretation opens the way to use all the power of the modern probability theory and statistics in developing novel methods for joint inversion of the multiphysics data. We apply the developed joint inversion methodology to inversion of gravity gradiometry and magnetic data in the Nordkapp Basin, Barents Sea to image salt diapirs.
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Zhdanov, Michael S., Xiaolei Tu, and Martin Čuma. "Cooperative inversion of multiphysics data using joint minimum entropy constraints." Near Surface Geophysics, March 26, 2022. http://dx.doi.org/10.1002/nsg.12203.
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Tu, Xiaolei, and Michael S. Zhdanov. "Joint focusing inversion of marine controlled-source electromagnetic and full tensor gravity gradiometry data." GEOPHYSICS, June 16, 2022, 1–57. http://dx.doi.org/10.1190/geo2021-0691.1.
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We present an approach for integrating the interdependent information of different geophysicalmethods to obtain a self-consistent geophysical model in offshore exploration. Electromagneticand gravity data complement seismic data by providing information about thephysical properties of prospective reservoir rocks. We have combined marine electromagneticand gravity gradiometry geophysical data in joint inversion using a joint focusingstabilizer. The method enforces coupling between different physical models and simultaneouslypromotes focused images of the targets. We also consider the importance of usingrobust norms to analyze data collected by marine controlled-source electromagnetic (MCSEM)surveys. The practical effectiveness of the developed method is illustrated by a casestudy of integrating and imaging marine multiphysics data collected in the Nordkapp Basin,Barents Sea, Norway.
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Liu, Baichuan, Nicole James, Amir-Sina Hamedi, Adrian Yao, Stephen E. Trask, Brian A. Mazzeo, and Dean Wheeler. "Direct Measurements of Ionic Transport Behavior of Dual-Layer Porous Electrodes." Journal of The Electrochemical Society, January 26, 2023. http://dx.doi.org/10.1149/1945-7111/acb66a.
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Abstract To improve power and cycling performance of lithium-ion batteries, dual-layer or porosity-gradient electrodes have been proposed. By using a higher porosity close to the separator, the intention is to improve ion transport where it is most needed. Here, MacMullin numbers of two dual-layer anode samples are tested using an impedance measurement technique developed previously. To characterize the microstructure of each layer independently, we developed an improved transmission-line model that accounts for each layer's properties. Virtual experiments in which impedance measurements were simulated using COMSOL Multiphysics were used to examine and improve the accuracy of experimental inversion process. The results for the two dual-layer anodes studied show that MacMullin numbers follow expected trends, though the anodes are quite different from each other.
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Albusairi, Mohammad, and Carlos Torres-Verdín. "Rapid modeling of borehole measurements of nuclear magnetic resonance via spatial sensitivity functions." GEOPHYSICS, May 28, 2021, 1–149. http://dx.doi.org/10.1190/geo2020-0755.1.
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Borehole measurements of nuclear magnetic resonance (NMR) are routinely used to estimate in situ rock and fluid properties. Conventional NMR interpretation methods often neglect bed-boundary and layer-thickness effects in the calculation of fluid volumetric concentrations and NMR relaxation-diffusion correlations. Such effects introduce notable spatial averaging of intrinsic rock and fluid properties across thinly bedded formations or in the vicinity of boundaries between layers exhibiting large property contrasts. Forward modeling and inversion methods can mitigate the aforementioned effects and improve the accuracy of true layer properties in the presence of mud-filtrate invasion and borehole environmental effects across spatially complex formations. We have developed a fast and accurate algorithm to simulate borehole NMR measurements using the concept of spatial sensitivity functions (SSFs) that honor NMR physics and incorporate tool, borehole, and formation geometry. Tool sensitivity maps are derived from a 3D multiphysics forward model that couples NMR tool properties, magnetization evolution, and electromagnetic propagation. In addition, a multifluid relaxation model based on Brownstein-Tarr’s equation is introduced to estimate layer NMR porosity decays and relaxation-diffusion correlations from pore-size-dependent rock and fluid properties. The latter model is convolved with the SSFs to reproduce borehole NMR measurements. The results indicate that NMR spatial sensitivity is controlled by porosity, electrical conductivity, excitation pulse duration, and tool geometry. We benchmark and verify the SSF-derived forward approximation against 3D multiphysics simulations for a series of synthetic cases with variable bed thickness and petrophysical properties, and in the presence of mud-filtrate invasion in a vertical well. Results indicate that the approximation can be executed in a few seconds in a central processing unit, by a factor of 1000 times faster than rigorous multiphysics calculations, with maximum root-mean-square errors of 1%.
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Prócel, Luis Miguel, and Lionel Trojman. "Simulación TCAD para un MOSFET de silicio en aislante, ultra fino con óxido enterrado y completamente agotado: una comparación entre COMSOL y Sentaurus." ACI Avances en Ciencias e Ingenierías 6, no. 1 (June 13, 2014). http://dx.doi.org/10.18272/aci.v6i1.163.
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En el presente trabajo, se desarrolla un modelo para simular un dispositivo MOSFET de silicio en aislante, ultra delgados con oxido enterrado (20m) y agotados completamente con SiO2 (5nm) como compuerta. El software que se usa es TCAD-Sentaurus. Se desarrollaron simulaciones DC para estudiar el comportamiento del voltaje de encendido y la transconductancia. Además, se desarrollaron simulaciones AC para estudiar la capacitancia y carga de inversión. Los resultados fueron comparados con un trabajo previo en el que se usó como simulador al programa COMSOL-Multiphysics. Los resultados obtenidos son muy similares entre ambos trabajos. Sin embargo, Sentaurus ofrece características más interesantes como introducir modelos más reales para los mecanismos físicos de dispositivos complejos.
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Meju, Max A., Bernd Kulessa, Luis Gallardo, Sarah Thompson, Alastair Ruffell, and Kieran Parker. "Improved imaging of ground deformation and brine seepage around abandoned flooded salt mines by joint inversion of multiphysics data." Journal of Applied Geophysics, November 2023, 105217. http://dx.doi.org/10.1016/j.jappgeo.2023.105217.
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Di Fiore, F., P. C. Berri, and L. Mainini. "Diagnosing Incipient Faults for a Faster Adoption of Sustainable Aerospace Technologies." AIAA Journal, July 1, 2024, 1–16. http://dx.doi.org/10.2514/1.j063413.
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Next-generation aircraft require the development and integration of a deal of innovative green technologies to meet the ambitious sustainability goals set for aviation. Those transformational efforts are associated with a tremendous increase in the complexity of the onboard systems and their multiphysics-coupled behaviors and dynamics. A critical aspect relates to the identification of the coupled faults resulting from the integration of those green technologies, which introduce damage identifiability issues and demand new approaches for the efficient and accurate identification of non-nominal fault conditions. Model-based fault detection and identification (FDI) methodologies have been proven essential to identify onboard the damages affecting the systems from physical signal acquisitions, but existing methods are typically computationally expensive and fail to capture incipient coupled faults, which prevents their adoption and scaling with the increasing complexity of novel multiphysics systems. This work introduces a multifidelity framework to accelerate the identification of fault modes affecting complex systems. An original two-stage compression computes an optimally informative and highly reduced representation of the monitoring signals for the minimum demand of onboard resources. A multifidelity scheme for Bayesian inversion is developed to infer multidomain fault parameters from the compressed signals: variable cost and fidelity models are optimally queried for a major reduction of the overall computational expense. The framework is demonstrated and validated for aerospace electromechanical actuators affected by incipient multimodal faults. Remarkable accelerations of the FDI procedure are observed, and the exact identification of the incipient fault condition was achieved one order of magnitude faster than with standard algorithms.
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Puel, Simone, Thorsten W. Becker, Umberto Villa, Omar Ghattas, and Dunyu Liu. "Volcanic arc rigidity variations illuminated by coseismic deformation of the 2011 Tohoku-oki M9." Science Advances 10, no. 23 (June 7, 2024). http://dx.doi.org/10.1126/sciadv.adl4264.
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Rock strength has long been linked to lithospheric deformation and seismicity. However, independent constraints on the related elastic heterogeneity are missing, yet could provide key information for solid Earth dynamics. Using coseismic Global Navigation Satellite Systems (GNSS) data for the 2011 M9 Tohoku-oki earthquake in Japan, we apply an inverse method to infer elastic structure and fault slip simultaneously. We find compliant material beneath the volcanic arc and in the mantle wedge within the partial melt generation zone inferred to lie above ~100 km slab depth. We also identify low-rigidity material closer to the trench matching seismicity patterns, likely associated with accretionary wedge structure. Along with traditional seismic and electromagnetic methods, our approach opens up avenues for multiphysics inversions. Those have the potential to advance earthquake and volcano science, and in particular once expanded to InSAR type constraints, may lead to a better understanding of transient lithospheric deformation across scales.
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Flé, Guillaume, Elijah Van Houten, Guillaume Gilbert, and Guy Cloutier. "Simulation of a synchronized methodology for MR-based electromechanical property imaging during transcranial electrical stimulation." Frontiers in Physics 12 (April 11, 2024). http://dx.doi.org/10.3389/fphy.2024.1324659.
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Introduction: Recent investigations into the biomechanics of the brain have unveiled alteration in tissue stiffness triggered by external stimuli. For instance, visual stimulation effects can be measured in elasticity images of the cortex generated by functional magnetic resonance elastography (MRE). Such a mechanical characterization method combined with non-invasive brain stimulation (NIBS), a technique that seeks to selectively modulate particular parts of the brain using weak electrical currents, has the potential to influence research on various neurological disorders. In this in silico study, we aimed to elucidate individual and interdependent aspects related to a synchronized biomechanical imaging and non-invasive brain stimulation methodology. Magnetic resonance electrical impedance tomography (MREIT) was incorporated to the pipeline, providing a promising way of evaluating NIBS-induced electrical current patterns in the brain while leveraging MRE and transcranial alternating current stimulation (tACS) experimental settings.Methods: A mouse head model was assembled using open-access atlases to include five anatomical structures: skin/subcutaneous tissue, skull, cerebrospinal fluid (CSF), brain white and grey matters. MRE, tACS, and MREIT experiments were simulated using Comsol Multiphysics with Matlab Livelink. Synthetic MRE and MREIT data were processed using the subzone non-linear inversion and harmonic Bz algorithm, respectively, to reconstruct images of the distributed complex shear modulus and electrical conductivity.Results and Discussion: Lorentz body forces arising from simultaneous MRE and tACS elicited elastic waves of negligible amplitude compared with the extrinsic actuation levels reported in the literature, which allowed accurate reconstructions of the complex shear modulus. Qualitative electrical conductivity maps retrieved by MREIT accurately delineated anatomical regions of the brain model and could be used to recover reasonably accurate distributions of tACS-induced currents. This multi-physics approach has potential for translation to human brain imaging, and may provide more possibilities for the characterization of brain function together than in isolation.
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Azizoglu, Zulkuf, Artur Posenato Garcia, Chelsea Newgord, and Zoya Heidari. "Simultaneous Assessment of Wettability and Water Saturation Through Integration of 2D NMR and Electrical Resistivity Measurements." SPE Reservoir Evaluation & Engineering, August 1, 2022, 1–14. http://dx.doi.org/10.2118/201519-pa.
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Summary Nuclear magnetic resonance (NMR) transverse relaxation (T2) measurements are sensitive to fluid saturations and wettability of the rocks. However, quantifying wettability index solely from NMR T2 models relies on accurate estimates of water saturation. It has been shown that integrating resistivity measurements and NMR T2 distributions enables simultaneous assessment of wettability and water saturation. Nevertheless, there still exist significant uncertainties in this approach in the presence of multiple types of fluids with overlapping transverse relaxation times or multimodal pore-size distribution. Thus, the objectives of this paper are (a) to introduce a new multiphysics workflow integrating 2D NMR with resistivity measurements to simultaneously quantify wettability index and water/hydrocarbon saturation and (b) to verify the reliability of the introduced workflow with core measurements in different rock types. The workflow starts by using 2D diffusivity-transverse relaxation (D-T2) or longitudinal-transverse relaxation (T1-T2) measurements to estimate fluid saturations. We use a nonlinear inversion algorithm to fit a multimodal Gaussian distribution to the 2D NMR measurements. We then calculate water and hydrocarbon saturations using the fluid volumes estimated from the multimodal Gaussian distribution. This estimate of water/hydrocarbon saturation is an input to our new physics-based resistivity model that explicitly incorporates the influence of wettability. The inputs to the resistivity model include water saturation, resistivity index, and pore-geometry-related parameters. In the core-scale verification step, we compare the results of wettability and fluid saturations obtained from the new workflow with gravimetrically assessed water saturation and Amott index measurements on core sample. We successfully verified the reliability of the new workflow with experimental measurements. Estimated water saturation using the introduced workflow resulted in an average relative error of less than 7% compared to the gravimetrically assessed water saturations. Wettability indices obtained from the workflow were in agreement with those estimated using Amott indices. The average absolute error between the estimated wettability indices and the Amott indices was 0.27. In conclusion, results demonstrated that integration of 2D NMR and electrical resistivity measurements enables reliable and simultaneous assessment of wettability and water saturation in different rock types. The method introduced in this paper is promising for reliable and real-time wettability assessment, both in the laboratory and in-situ condition. It provides a physics-based and robust method to accurately and simultaneously estimate water/hydrocarbon saturation and wettability in hydrocarbon-bearing rocks.