Three-Dimensional Electromagnetic Modelling and Inversion from Theory to Application

Avdeev, Dmitry B.

doi:10.1007/s10712-005-1836-x

Cited by 247 publications

(98 citation statements)

References 146 publications

(148 reference statements)

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“…Therefore, at some large enough distance of the boundaries from the anomalous domain, we may neglect the values of the anomalous field at the boundaries (including those located above the sea level in the air). However, in a general case, a more accurate boundary condition can be used (e.g., Zhdanov, 2002;Avdeev, 2005;Newman, 2014). …”

Section: Formulation Of a Hybrid Fd-ie Methods Fd Modeling Of The Anommentioning

confidence: 99%

“…There are several popular numerical approaches for 3D EM modeling: integral-equation (IE), finite-difference (FD), and finiteelement (FE) methods (Zhdanov, 2002(Zhdanov, , 2009(Zhdanov, , 2015Avdeev, 2005).…”

Section: Introductionmentioning

confidence: 99%

“…One of the key elements of our inversion algorithm is computing the Fréchet derivative matrix. A conventional approach to solving this problem is based on using the adjoint operator (e.g., Avdeev, 2005;Abubakar et al, 2011;Zhdanov, 2002Zhdanov, , 2015. However, in a case of a large-scale problem, typical for a towed streamer EM method, when the survey covers hundreds and even thousands of line kilometers, this approach becomes impractical.…”

Section: Introductionmentioning

confidence: 99%

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A hybrid finite-difference and integral-equation method for modeling and inversion of marine controlled-source electromagnetic data

et al. 2016

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One of the major problems in the modeling and inversion of marine controlled-source electromagnetic (CSEM) data is related to the need for accurate representation of very complex geoelectrical models typical for marine environment. At the same time, the corresponding forward-modeling algorithms should be powerful and fast enough to be suitable for repeated use in hundreds of iterations of the inversion and for multiple transmitter/receiver positions. To this end, we have developed a novel 3D modeling and inversion approach, which combines the advantages of the finitedifference (FD) and integral-equation (IE) methods. In the framework of this approach, we have solved Maxwell's equations for anomalous electric fields using the FD approximation on a staggered grid. Once the unknown electric fields in the computation domain of the FD method are computed, the electric and magnetic fields at the receivers are calculated using the IE method with the corresponding Green's tensor for the background conductivity model. This approach makes it possible to compute the fields at the receivers accurately without the need of very fine FD discretization in the vicinity of the receivers and sources and without the need for numerical differentiation and interpolation. We have also developed an algorithm for 3D inversion based on the hybrid FD-IE method. In the case of the marine CSEM problem with multiple transmitters and receivers, the forward modeling and the Fréchet derivative calculations are very time consuming and require using large memory to store the intermediate results.To overcome those problems, we have applied the moving sensitivity domain approach to our inversion. A case study for the 3D inversion of towed streamer EM data collected by PGS over the Troll field in the North Sea demonstrated the effectiveness of the developed hybrid method.

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Section: Formulation Of a Hybrid Fd-ie Methods Fd Modeling Of The Anommentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A hybrid finite-difference and integral-equation method for modeling and inversion of marine controlled-source electromagnetic data

et al. 2016

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“…They also require storing merely several pairs of so-called correction vectors that dramatically diminish the storage requirements. A more complete review on this subject may be found in [4].…”

Section: Introductionmentioning

confidence: 99%

A Rigorous Three-Dimensional Magnetotelluric Inversion

Avdeev¹,

Avdeeva²

2006

PIER

Self Cite

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Abstract-The limited-memory quasi-Newton optimization method with simple bounds has been applied to develop a novel fully threedimensional (3-D) magnetotelluric (MT) inversion technique. This nonlinear inversion is based on iterative minimization of a classical Tikhonov-type regularized penalty functional. But instead of the usual model space of log resistivities, the approach iterates in a model space with simple bounds imposed on the conductivities of the 3-D target. The method requires storage that is proportional to n cp ×N , where the N is the number of conductivities to be recovered and n cp is the number of the correction pairs (practically, only a few). This is much less than requirements imposed by other Newton type methods (that usually require storage proportional to N ×M , or N ×N , where M is the number of data to be inverted). Using an adjoint method to calculate the gradients of the misfit drastically accelerates the inversion. The inversion also involves all four entries of the MT impedance matrix. The integral equation forward modelling code x3d by Avdeev et al. [1,2] is employed as an engine for this inversion. Convergence, performance and accuracy of the inversion are demonstrated on a 3D MT synthetic, but realistic, example.

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“…Techniques that succeed in relatively inaccurate solutions to inverse problems combine the forward and inverse design step and iterate it numerous times. A survey of such schemes is presented in [44,45] -in summary, best known systems achieve to solve some ill-defined inverse problems with prior knowledge of solution structure for K ≈ 10 3 in substantial amount of time. As formal analysis of such methodologies is not provided, we conjecture that solving Pr.1 is a task which is well beyond reach of modern inverse design tools.…”

Section: Inverse Designmentioning

confidence: 99%

RF-DNA: Radio-Frequency Certificates of Authenticity

DeJean

Kirovski

Lecture Notes in Computer Science

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Abstract.A certificate of authenticity (COA) is an inexpensive physical object that has a random and unique multidimensional structure S which is hard to near-exactly replicate. An inexpensive device should be able to scan object's physical "fingerprint," i.e., obtain a set of features in the form of a multidimensional signal x that pseudo-uniquely represents S. For a given "fingerprint" x and without access to S, it should be computationally difficult to construct an object of fixed dimensions with a "fingerprint" y which is at a bounded proximity from x according to a standardized distance metric. We introduce objects that behave as COAs in the electromagnetic field. The objective is to complement RFIDs so that they are physically, not only digitally, unique and hard to replicate. By enabling this feature, we introduce a tag whose information about the product can be read within a relative far-field, and also whose authenticity can be reliably verified within its near-field. In order to counterfeit a tag, the adversary faces two difficulties -a computational and a manufacturing one. The computational difficulty stems from the hardness of solving linear inverse problems in the electromagnetic field. In order to create an actual tag, the adversary must also manufacture a multidimensional object with a specific three-dimensional topology, dielectric properties, and conductivity.

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Three-Dimensional Electromagnetic Modelling and Inversion from Theory to Application

Cited by 247 publications

References 146 publications

A hybrid finite-difference and integral-equation method for modeling and inversion of marine controlled-source electromagnetic data

A hybrid finite-difference and integral-equation method for modeling and inversion of marine controlled-source electromagnetic data

A Rigorous Three-Dimensional Magnetotelluric Inversion

RF-DNA: Radio-Frequency Certificates of Authenticity

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