Integration of electromagnetic and seismic data to assess residual gas risk in the toe-thrust belt of deepwater Niger Delta

Moser, Jochen; Poupon, Manuel; Meyer, Hans-Jurg; Wojcik, Chris; Rosenquist, Mark; Adejonwo, Abayomi; Smit, Dirk

doi:10.1190/1.2335165

Cited by 10 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We choose to apply it to simulated controlled‐source electromagnetic (CSEM) data because this best demonstrates the ability of the proposed method to deal with dissipation. Although the spatial resolution of CSEM data is much lower than that of seismic data, the main advantage of CSEM prospecting is its power to detect a hydrocarbon accumulation in a reservoir due to its high conductivity contrast (Ellingsrud et al 2002; Moser et al 2006). Amundsen et al (2006) showed that decomposition of CSEM data into down going and up going fields improves the detectability of hydrocarbon reservoirs.…”

Section: Numerical Example Of Csem Interferometrymentioning

confidence: 99%

Seismic and electromagnetic controlled‐source interferometry in dissipative media

Wapenaar

Slob

Snieder

2008

Geophysical Prospecting

146

172

View full text Add to dashboard Cite

A B S T R A C TSeismic interferometry deals with the generation of new seismic responses by crosscorrelating existing ones. One of the main assumptions underlying most interferometry methods is that the medium is lossless. We develop an 'interferometry-bydeconvolution' approach which circumvents this assumption. The proposed method applies not only to seismic waves, but to any type of diffusion and/or wave field in a dissipative medium. This opens the way to applying interferometry to controlledsource electromagnetic (CSEM) data. Interferometry-by-deconvolution replaces the overburden by a homogeneous half space, thereby solving the shallow sea problem for CSEM applications. We demonstrate this at the hand of numerically modeled CSEM data.

show abstract

Section: Numerical Example Of Csem Interferometrymentioning

confidence: 99%

Seismic and electromagnetic controlled‐source interferometry in dissipative media

Wapenaar

Slob

Snieder

2008

Geophysical Prospecting

146

172

View full text Add to dashboard Cite

show abstract

“…9a). Although the spatial resolution of CSEM data is much lower than that of seismic data, an important advantage of CSEM prospecting is its potential to detect a hydrocarbon accumulation in a reservoir due to its high conductivity contrast (Ellingsrud et al 2002; Moser et al 2006). Fig.…”

Section: Applications In Controlled‐source Interferometrymentioning

confidence: 99%

Seismic interferometry by crosscorrelation and by multidimensional deconvolution: a systematic comparison

Wapenaar

Neut

Ruigrok

et al. 2011

Geophysical Journal International

195

199

View full text Add to dashboard Cite

S U M M A R YSeismic interferometry, also known as Green's function retrieval by crosscorrelation, has a wide range of applications, ranging from surface-wave tomography using ambient noise, to creating virtual sources for improved reflection seismology. Despite its successful applications, the crosscorrelation approach also has its limitations. The main underlying assumptions are that the medium is lossless and that the wavefield is equipartitioned. These assumptions are in practice often violated: the medium of interest is often illuminated from one side only, the sources may be irregularly distributed, and losses may be significant. These limitations may partly be overcome by reformulating seismic interferometry as a multidimensional deconvolution (MDD) process. We present a systematic analysis of seismic interferometry by crosscorrelation and by MDD. We show that for the non-ideal situations mentioned above, the correlation function is proportional to a Green's function with a blurred source. The source blurring is quantified by a so-called interferometric point-spread function which, like the correlation function, can be derived from the observed data (i.e. without the need to know the sources and the medium). The source of the Green's function obtained by the correlation method can be deblurred by deconvolving the correlation function for the point-spread function. This is the essence of seismic interferometry by MDD. We illustrate the crosscorrelation and MDD methods for controlled-source and passive-data applications with numerical examples and discuss the advantages and limitations of both methods.

show abstract

Characteristics of marine CSEM responses in complex geologic terrain of Niger Delta Oil province: Insight from 2.5D finite element forward modeling

Folorunso

Liu

2015

Journal of African Earth Sciences

View full text Add to dashboard Cite

Integration of electromagnetic and seismic data to assess residual gas risk in the toe-thrust belt of deepwater Niger Delta

Cited by 10 publications

References 0 publications

Seismic and electromagnetic controlled‐source interferometry in dissipative media

Seismic and electromagnetic controlled‐source interferometry in dissipative media

Seismic interferometry by crosscorrelation and by multidimensional deconvolution: a systematic comparison

Characteristics of marine CSEM responses in complex geologic terrain of Niger Delta Oil province: Insight from 2.5D finite element forward modeling

Contact Info

Product

Resources

About