Anisotropic elastic full-waveform inversion of walkaway vertical seismic profiling data from the Arabian Gulf

Owusu, J.C.; Podgornova, Olga; Charara, Marwan; Leaney, Scott; Campbell, A.; Ali, Shujaat; Borodin, I.; Nutt, L.; Menkiti, Henry

doi:10.1111/1365-2478.12227

Cited by 28 publications

(13 citation statements)

References 29 publications

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“…Raknes & Arntsen 2014;Ovcharenko et al 2018). Since elastic anisotropic waveform inversions have higher computational costs to their isotropic counterparts, they only recently became the focus of attention (Köhn et al 2015;Podgornova et al 2015;Owusu et al 2016;Bergslid et al 2015;Oh & Alkhalifah 2016;Kamath & Tsvankin 2016). Feasibility and resolution studies for 3-D inversions are still computationally expensive, therefore they are often performed either in 2-D (Podgornova et al 2015) or with very few simultaneous (encoded) shots (Köhn et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Waveform inversion for orthorhombic anisotropy with P waves: feasibility and resolution

Kazei

Alkhalifah

2018

Geophysical Journal International

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Summary Various parameterizations have been suggested to simplify inversions of first arrivals, or P −waves, in orthorhombic anisotropic media, but the number and type of retrievable parameters have not been decisively determined. We show that only six parameters can be retrieved from the dynamic linearized inversion of P −waves. These parameters are different from the six parameters needed to describe the kinematics of P −waves. Reflection-based radiation patterns from the P − P scattered waves are remapped into the spectral domain to allow for our resolution analysis based on the effective angle of illumination concept. Singular value decomposition of the spectral sensitivities from various azimuths, offset coverage scenarios, and data bandwidths allows us to quantify the resolution of different parameterizations, taking into account the signal-to-noise ratio in a given experiment. According to our singular value analysis, when the primary goal of inversion is determining the velocity of the P −waves, gradually adding anisotropy of lower orders (isotropic, vertically transversally isotropic, orthorhombic) in hierarchical parameterization is the best choice. Hierarchical parametrization reduces the tradeoff between the parameters and makes gradual introduction of lower anisotropy orders straightforward. When all the anisotropic parameters affecting P −wave propagation need to be retrieved simultaneously, the classic parameterization of orthorhombic medium with elastic stiffness matrix coefficients and density is a better choice for inversion. We provide estimates of the number and set of parameters that can be retrieved from surface seismic data in different acquisition scenarios. To set up an inversion process, the singular values determine the number of parameters that can be inverted and the resolution matrices from the parameterizations can be used to ascertain the set of parameters that can be resolved.

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Section: Introductionmentioning

confidence: 99%

Waveform inversion for orthorhombic anisotropy with P waves: feasibility and resolution

Kazei

Alkhalifah

2018

Geophysical Journal International

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“…Owusu et al . [] performed FWI of VSP data with a wavelet derived from far‐field measurements of an airgun array. Pratt [] and Roberts et al .…”

Section: Workflowmentioning

confidence: 99%

“…There are different strategies for selecting a proper source wavelet for the inversion. Owusu et al [2016] performed FWI of VSP data with a wavelet derived from far-field measurements of an airgun array. Pratt [1999] and Roberts et al [2008] introduced different source wavelet inversion algorithms in frequency domain and successfully used them for the inversion of experimental data.…”

Section: Source Wavelet Estimationmentioning

confidence: 99%

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Time‐lapse full waveform inversion of vertical seismic profile data: Workflow and application to the CO2CRC Otway project

Egorov

Pevzner

Bóna

et al. 2017

Geophysical Research Letters

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Vertical seismic profile (VSP) is one of the technologies for monitoring hydrocarbon production and CO2 geosequestration. However, quantitative interpretation of time‐lapse VSP is challenging due to its irregular distribution of source‐receiver offsets. One way to overcome this challenge is to use full waveform inversion (FWI), which does not require regular offsets. We present a workflow of elastic FWI applied to offset vertical seismic profile data for the purpose of identification and estimation of time‐lapse changes introduced by injection of 15,000 t of CO2‐rich gas mixture at 1.5 km depth. Application of this workflow to both synthetic and field data shows that elastic FWI is able to detect and quantify the time‐lapse anomaly in P wave velocity with the magnitude of 100–150 m/s.

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“…The applications of Downloaded 07/08/17 to 186.88.151.214. Redistribution subject to SEG license or copyright; see Terms of Use at http://library.seg.org/ FWI to the description and interpretation of sedi mentary strata exploits the prestack seismic re flection amplitudes in offset domain (Vigh and Starr, 2008;Barnes and Charara, 2009;Barnes et al, 2008;Guitton et al, 2012;Asnaashari et al, 2013;Queiber and Singh, 2013;Owusu et al, 2015;Mancini et al, 2016) and timelapse seismic (Raknes and Arntsen, 2014;. In these exam ples, the goal of FWI is similar to that of reflec tion seismic inversion.…”

Section: M1-16 Encyclopedia Of Exploration Geophysicsmentioning

confidence: 99%

7. Seismic, rock physics, spatial models, and their integration in reservoir geophysics

Bosch

Mukerji²,

González

2014

Encyclopedia of Exploration Geophysics

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seismic inversion and rock physics models. Furthermore well logs allow for local validation of the estimations and constraint for the struc ture and properties. Combining the spatially dis tributed information provided by seismic surveys with the localized information obtained from well logging tools requires handling disparate property support scales and use of spatial statisti cal models. Most common models are based on the spatial homogeneity of the mean (one point statistics) and the spatial covariance (two point statistics). Cokriging estimation and multivariate Gaussian simulation are examples of these meth ods, which are very useful in the spatial combina tion of information. In addition, methods based on multipoint statistics are used to model com plex morphology. The integration of the overall data, information, geophysical, and geological knowledge into a reliable reservoir model is elab orated via diverse workflows. A basic sequence includes seismic interpretation, seismic inver sion, reservoir characterization, geostatistical es timation, geostatistical simulation, and dynamic fluid flow modeling. It is common to cycle within the sequence to update the model as additional information about the reservoir arrives. Some workflows proceed in a stepwise manner, while others, with increasing computational require ments, employ joint inversion formulations where multiproperty models are estimated to jointly satisfy the complete set of available data.

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Anisotropic elastic full-waveform inversion of walkaway vertical seismic profiling data from the Arabian Gulf

Cited by 28 publications

References 29 publications

Waveform inversion for orthorhombic anisotropy with P waves: feasibility and resolution

Waveform inversion for orthorhombic anisotropy with P waves: feasibility and resolution

Time‐lapse full waveform inversion of vertical seismic profile data: Workflow and application to the CO2CRC Otway project

7. Seismic, rock physics, spatial models, and their integration in reservoir geophysics

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