Three Dimensional Imaging of Marine CSEM Data

Carazzone, James J.; Burtz, Olivier; Green, K.E.; Pavlov, D. A.; Xia, C.

doi:10.1190/1.2144386

Cited by 36 publications

(22 citation statements)

References 3 publications

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“…While one-dimensional (1D) modeling and inversion is relatively easy and trial and error 3D forward modeling seemingly straight forward (Hoversten et al 2006;4 Weiss & Constable 2006, Green et al, 2005, the need for 3D imaging is necessary as the search for hydrocarbons now increasingly occurs in highly complex situations where hydrocarbon effects are subtle aspects of the total offshore geological environment. Further complicating matters is the realization that electrical anisotropy also needs to be incorporated directly into the imaging process Carazzone et al 2008;Jing et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Imaging CSEM data in the presence of electrical anisotropy

2010

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Formation anisotropy should be incorporated into the analysis of controlled source electromagnetic (CSEM) data because failure to do so can produce serious artifacts in the resulting resistivity images for certain data configurations of interest. This finding is demonstrated in model and case studies. Sensitivity to horizontal resistivity will be strongest in the broadside electric field data where detectors are offset from the tow line. Sensitivity to the vertical resistivity is strongest for over flight data where the transmitting antenna passes directly over the detecting antenna. Consequently, consistent treatment of both over flight and broadside electric field measurements requires an anisotropic modeling assumption. To produce a consistent resistivity model for such data we develop and employ a 3D CSEM imaging algorithm that treats transverse anisotropy. The algorithm is based upon non-linear conjugate gradients and full wave equation modeling. It exploits parallel computing systems to effectively treat 3D imaging problems and CSEM data volumes of industrial size. Here we use it to demonstrate the anisotropic imaging process on model and field data sets from the North Sea and offshore Brazil.We also verify that isotropic imaging of over flight data alone produces an image generally consistent with the vertical resistivity. However, superior data fits are obtained when the same over flight data are analyzed assuming an anisotropic resistivity model. 2

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Section: Introductionmentioning

confidence: 99%

Imaging CSEM data in the presence of electrical anisotropy

2010

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“…Operating frequencies of transmitters in CSEM may range between 0.1 and 10 Hz, and the choice depends on the dimensions of a model. In most studies, typical frequencies vary from 0.25 to 1 Hz, which means that for source-receiver offsets of 1012 km, the penetration depth of the method can extend to several kilometres below the seabed [1], [4], [5], [15]. The disadvantage of marine CSEM is its relatively low resolution compared to seismic imaging.…”

Section: Methodsmentioning

confidence: 99%

Parallel and numerical issues of the edge finite element method for 3D controlled-source electromagnetic surveys

Castillo-Reyes

Puente

Puzyrev

et al. 2015

2015 International Conference on Computing Systems and Telematics (ICCSAT)

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Abstract-This paper deals with the most relevant parallel and numerical issues that arise when applying the Edge Element Method in the solution of electromagnetic problems in exploration geophysics. In this sense, in recent years the application of land and marine controlled-source electromagnetic (CSEM) surveys has gained tremendous interest among the offshore exploration community. This method is especially significant in detecting hydrocarbon in shallow/deep waters. On the other hand, in Finite Element Methods for solving electromagnetic field problems, the use of Edge Elements has become very popular. In fact, Edge Elements are often said to be a cure to many difficulties that are encountered (particularly eliminating spurious solutions) and are claimed to yield accurate results. CSEM, linear vectorial edge basis functions and its implementation on unstructured tetrahedral meshes are discussed. The use of it's kind of discretisation enables the representation of complex geological structures and allows local refinement in order to improve the solution's accuracy. A parallel shared memory approach is proposed to meet the high computational cost of EM modeling. Performance results and an convergence study are presented in order to validate our numerical method.

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“…As EM measurements enable a distinction between highly resistive bodies and their surrounding structures, the method attracted the attention of the oil industry because hydrocarbon reservoirs are far more resistive than brine-filled formations. As reported by many authors, controlled-source electromagnetic (CSEM) measurements may indicate the presence of hydrocarbons Ellingsrud et al, 2002;Amundsen et al, 2004;Carazzone et al, 2005;Srnka et al, 2006;Choo et al, 2006;Darnet et al, 2007;MacGregor et al, 2007 Marine CSEM surveys typically employ a high-powered electric source close to the seafloor to induce low-frequency EM signals that penetrate into the subsurface. An array of EM receivers placed on the seafloor records the horizontal electric and magnetic field components.…”

Section: Introductionmentioning

confidence: 99%

Controlled-source electromagnetics for reservoir monitoring on land

Wirianto¹

2012

Geophysics

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Three Dimensional Imaging of Marine CSEM Data

Cited by 36 publications

References 3 publications

Imaging CSEM data in the presence of electrical anisotropy

Imaging CSEM data in the presence of electrical anisotropy

Parallel and numerical issues of the edge finite element method for 3D controlled-source electromagnetic surveys

Controlled-source electromagnetics for reservoir monitoring on land

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