Elastic properties from seismic data are important to determine subsurface hydrocarbon presence and have become increasingly important for detailed reservoir characterization that aids to ...

Anisotropic 3D elastic full-wavefield inversion to directly estimate elastic properties and its role in interpretation

Method for selecting an acquisition geometry for a seismic survey based on ability to resolve an a priori velocity model. Two or more candidate acquisition geometries are selected (301, 302), differing in areal coverage and cost to perform. Then compute a synthetic seismic dataset for each geometry using a detailed geometrical reference model of the subsurface (301). Invert the synthetic seismic datasets preferably using simultaneous source FWI, and preferably with Volume of Investigation constraints, to determine model updates (303, 304). Quantitatively assess the value of the additional traces in a fuller dataset relative to a subset (306), using one or more statistics based on the accuracy of the updated models, such as improved match to the reference model, better fit of seismic data, or rate of change in improvement with iterations. Inversions may be cascaded for further efficiency (314).

Seismic survey design using full wavefield inversion

Method for reconstructing subsurface Q depth profiles from common offset gathers ( 92 ) of reflection seismic data by performing migration ( 40 ), ray tracing ( 100 ), CDP-to-Data Domain surface takeoff angle finding ( 96, 98 ), kernel matrix construction ( 110 ), depth-to-time conversion and wavelet stretching correction ( 80 ), source amplitude spectrum fitting, centroid frequency shift calculation ( 90 ), and box-constrained optimization ( 120 ).

Reflection seismic data q tomography

A method, including: obtaining an initial geophysical model; modeling a forward wavefield with viscoacoustic or viscoelastic wave equations; modeling an adjoint wavefield with adjoint viscoacoustic or adjoint viscoelastic wave equations, wherein the adjoint viscoacoustic wave equations are based on an auxiliary variable that is a function of both pressure and a memory variable or the adjoint viscoelastic wave equations are based on a combination of stress and a memory variable, respectively; obtaining a gradient of a cost function based on a combination of a model of the forward wavefield and a model of the adjoint wavefield; and using the gradient of the cost function to update the initial geophysical model and obtain an updated geophysical model.

Fast viscoacoustic and viscoelastic full-wavefield inversion

Method for reducing computational time in inversion of geophysical data to infer a physical property model ( 91 ), especially advantageous in full wavefield inversion of seismic data. An approximate Hessian is pre-calculated by computing the product of the exact Hessian and a sampling vector composed of isolated point diffractors ( 82 ), and the approximate Hessian is stored in computer hard disk or memory ( 83 ). The approximate Hessian is then retrieved when needed ( 99 ) for computing its product with the gradient ( 93 ) of an objective function or other vector. Since the approximate Hessian is very sparse (diagonally dominant), its product with a vector may therefore be approximated very efficiently with good accuracy. Once the approximate Hessian is computed and stored, computing its product with a vector requires no simulator calls (wavefield propagations) at all. The pre-calculated approximate Hessian can also be reused in the subsequent steps whenever necessary.

Accelerating Full Wavefield Inversion with Nonstationary Point-Spread Functions

Method for multi-parameter inversion using elastic inversion. This method decomposes data into offset/angle groups and performs inversion on them in sequential order. This method can significantly speed up convergence of the iterative inversion process, and is therefore most advantageous when used for full waveform inversion (FWI). The present inventive approach draws upon relationships between reflection energy and reflection angle, or equivalently, offset dependence in elastic FWI. The invention uses recognition that the amplitudes of small angle (near offset) reflections are largely determined by acoustic impedance alone (1), independent for the most part of Vp/Vs. Large angle (middle and far offset) reflections are affected by Ip, Vp/Vs (2) and other earth parameters such as density (3) and anisotropy. Therefore, the present inventive method decomposes data into angle or offset groups in performing multi-parameter FWI to reduce crosstalk between the different model parameters being determined in the inversion.

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Multi-parameter inversion through offset dependent elastic fwi

FIELD: physics, measurement equipment.SUBSTANCE: invention refers to the field of geophysics and can be used for processing seismic data. The method for multiparameter inversion using elastic inversion is claimed. This method decomposes the data to the shift/angular groups and performs their inversion in sequential order. This method can greatly speed up the convergence of the iterative inversion process, and therefore, is most advantageous when used for full-wave inversion (FWI). This inventive approach is based on the relationship between reflection energy and reflection angle, or on the dependence on the shear for elastic FWI, which is the same. The invention uses the recognition that the small reflection angle amplitudes (close shear) are largely determined by one acoustic impedance, regardless of the greater part of Vp/Vs. Large angle reflections (middle and far shear) depend on Ip, Vp/Vs (2) and other terrestrial parameters such as density (3) and anisotropy. Therefore, this inventive method divides data into angular and shift groups performing multiparametric FWI, to reduce crosstalk between different model parameters, which are determined in the inversion.EFFECT: invention provides improved accuracy and reliability of obtained data.10 cl, 6 dwg

Lazaratos Spiridon K

Papers

Multi-parameter inversion through offset dependent elastic fwi

Multiparameter inversion through elastic full-wave inversion (fwi) dependent on shear