Multi-layer Non-linear Slope Tomography

Lambaré, Gilles; Guillaume, P.; Zhang, X.; Prescott, A.; Reinier, M.; Montel, J.; Cavalié, A.

doi:10.3997/2214-4609.20130032

Cited by 8 publications

(3 citation statements)

References 16 publications

(9 reference statements)

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“…• We assume the maximum-likelihood model has been obtained by a nonlinear slope tomography with tilted transverse isotropy (TTI) (Montel et al, 2010;Guillaume et al, 2013). Uncertainties relating to velocity-model parameters can be evaluated by developing a probability density function (PDF) around this maximum-likelihood model.…”

Section: Methods For Estimating Uncertainties In a Tomography Modelmentioning

confidence: 99%

“…Our tomography model space is described by cardinal cubic B-splines (with a range of 500,000 to 50 million parameters). We use nonlinear slope tomography (Guillaume et al, 2013) where the linear system to be solved is made up of both a data misfit term and all additional constraints. From this system, we can generate equiprobable velocity-model perturbations by exploring the envelope of the standarddeviation confidence interval.…”

Section: Methods For Estimating Uncertainties In a Tomography Modelmentioning

confidence: 99%

“…A geologically plausible prestack depth migration model was built using multilayer nonlinear slope tomography (Guillaume et al, 2013), and the resulting maximum-likelihood model showed excellent well ties at wells distributed homogeneously throughout the survey area. To initiate the tomography-derived uncertainty analysis, 500 tomographically consistent and equiprobable perturbations were generated around the maximum-likelihood velocity model within a standard-deviation confidence interval.…”

Section: Methods For Estimating Uncertainties In a Tomography Modelmentioning

confidence: 99%

See 2 more Smart Citations

Extracting seismic uncertainties from tomographic velocity inversion and their use in reservoir risk analysis

et al. 2017

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Structural information in subsurface seismic images is critical for reservoir delineation, reserve estimation, and well planning. However, by its very nature, it is also uncertain. One cause of the image uncertainty is the migration velocity model that directly affects the position of migrated events, both laterally and vertically. (The term "velocity" is meant in the broad sense; i.e., it also includes the anisotropy parameters.) We present a method that accounts for uncertainties in a velocity model estimated by tomography and translates them into the migrated domain. Standard-deviation attributes on target horizon positions or layer thicknesses are extracted. The method includes quality controls for validating the estimated uncertainty attributes before integration with other downstream or interpretative information. The method is demonstrated on a North Sea area covered by data from multiple seismic surveys. We observe that uncertainties increase with model complexity or depth and decrease as the illumination diversity increases. The computed uncertainty maps constitute a valuable source of information for hierarchizing (both qualitatively and quantitatively) different areas in the survey. For the purpose of reservoir risk analysis, we combine our technique with other information (e.g., interpretation uncertainties) to map how uncertainties in the depth of the structural spill point impact the gross rock volume (GRV) estimation of a reservoir.

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Section: Methods For Estimating Uncertainties In a Tomography Modelmentioning

confidence: 99%

Section: Methods For Estimating Uncertainties In a Tomography Modelmentioning

confidence: 99%

Section: Methods For Estimating Uncertainties In a Tomography Modelmentioning

confidence: 99%

See 1 more Smart Citation

Extracting seismic uncertainties from tomographic velocity inversion and their use in reservoir risk analysis

et al. 2017

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Stereotomography of seismic data acquired on undulant topography

Jin

Zhang

2018

GEOPHYSICS

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Stereotomography is a robust method for building velocity models from seismic reflection data, and it has been applied to offshore seismic data, but there is almost no stereotomographic study with rugged topographic conditions. We study the topographic effects on the slopes of locally coherent events of seismic data and develop an approach to calculate the slopes on an undulant observation surface using the horizontal and vertical components of slowness vectors estimated. Then, we develop an extended stereotomography with undulant observation surface based on the conventional one. Tests on synthetic data validate the extended stereotomography. Application to the ﬁeld seismic data in a foothill belt in Xinjiang of the West China indicates that the extended stereotomography is an effective tool to build velocity models for prestack depth migration of seismic data acquired on rugged topography.

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On tomography velocity uncertainty in relation with structural imaging

2021

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Evaluating structural uncertainties associated with seismic imaging and target horizonscan be of critical importance for decision-making related to oil and gas exploration andproduction. An important breakthrough for industrial applications has been madewith the development of industrial approaches to velocity model building. We proposean extension of these approaches, sampling an equi-probable contour of the tomographyposterior probability density function (pdf) rather than the full pdf, and usingnon-linear slope tomography. Our approach allows to assess the quality of uncertainty relatedassumptions (linearity and Gaussian hypothesis within the Bayesian theory)and estimate volumetric migration positioning uncertainties (a generalization of horizonuncertainties), in addition to the advantages in terms of computational efficiency.We derive the theoretical concepts underlying this approach and unify our derivationswith those of previous publications. As the method works in the full model space ratherthan in a preconditioned one, we split the analysis into the resolved and unresolvedtomography spaces. We argue that the resolved space uncertainties are to be used infurther steps leading to decision-making and can be related to the output of methodsthat work in a preconditioned model space. The unresolved space uncertainties representa qualitative byproduct specific to our method, strongly highlighting the mostuncertain gross areas, thus useful for QCs. These concepts are demonstrated on asynthetic dataset. In addition, the industrial viability of the method is illustrated ontwo different 3D field datasets. The first one consists of a merge of different seismic surveys in the North Sea and shows corresponding structural uncertainties. The second one consists of a marine dataset and shows the impact of structural uncertainties on gross-rock volume computation.

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Multi-layer Non-linear Slope Tomography

Cited by 8 publications

References 16 publications

Extracting seismic uncertainties from tomographic velocity inversion and their use in reservoir risk analysis

Extracting seismic uncertainties from tomographic velocity inversion and their use in reservoir risk analysis

Stereotomography of seismic data acquired on undulant topography

On tomography velocity uncertainty in relation with structural imaging

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