Reflection moveout inversion in azimuthally anisotropic media

Al-Dajani, AbdulFattah; Alkhalifah, Tariq

doi:10.1190/1.1885620

Cited by 4 publications

(4 citation statements)

References 2 publications

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“…5c). The ratio of the interval time thickness between the horizons to the total time thickness is about 0.14, while according to Al-Dajani and Alkhalifah (1997), acceptably stable estimates of 10%, and higher, anisotropy can be obtained only for thickness ratios greater than 0.2. The reservoir has a moderate porosity but very high permeability due to horizontal and vertical fractures.…”

Section: R E a L D Ata E X A M P L Ementioning

confidence: 94%

Dense 3D residual moveout analysis as a tool for HTI parameter estimation

Kozlov

Varivoda

2004

Geophysical Prospecting

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A B S T R A C TThree-dimensional residual moveout analysis is the basic step in velocity model refinement. The analysis is generally carried out using horizontal and/or vertical semblances defined on a sparse set of in-lines or cross-lines with densely sampled sourcereceiver offsets. An alternative approach, which we call dense residual moveout analysis (DRMA), is to use all the bins of a three-dimensional survey but sparsely sampled offsets. The proposed technique is very fast and provides unbiased and statistically efficient estimates of the residual moveout. Indeed, for the sparsest possible offset distribution, when only near-and far-angle stacks are used, the variance of the residual moveout estimate is only 1.4 times larger than the variance of the least-squares estimate obtained using all offsets.The high performance of DRMA makes it a useful tool for many applications, of which azimuthal velocity analysis is considered here. For a horizontal transverse isotropy (HTI) model, a deterministic procedure is proposed to define, at every point of residual moveout estimation, the azimuthal angle of the HTI axis of symmetry, the Thomsen anisotropy coefficients, and the interval (or root-mean-square) velocities in both the HTI isotropy and symmetry planes. The procedure is not restricted by DRMA assumptions; for example, it is also applicable to semblance-based residual moveout estimates.The high resolution of the technique is illustrated by azimuthal velocity analysis over an oilfield in West Siberia. I N T R O D U C T I O NThe conventional technique of three-dimensional velocity model refinement consists of residual moveout estimation by creating and interpreting horizontal semblances of prestack migrated gathers at a rather sparse set of in-lines or cross-lines. An alternative approach, which we call dense residual moveout analysis (DRMA), is to transfer from a system of sparse lines to a system of sparse offsets, as in the map manipulation technique proposed by Jones and Folstad (2002). The map manipulation technique may be considered as a close prototype of DRMA. It consists of taking near-and far-trace stacks with an interpreted time horizon as a key reservoir marker. Then, using the interpretation as the centre for a windowed operator, a cross-correlation of the near and far stacks is performed and the estimate of the residual time shift between the far and near stacked traces is converted to root-mean-square velocity assuming parabolicity of the residual moveout (Castle 1994). The DRMA differs in that (i) near-and far-angle stacks are taken as convenient representations of near and far offsets; (ii) cross-correlation is replaced with a special three-dimensional picking procedure implemented by Paradigm Geophysical's interpretation software; and (iii) special steps, *

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Section: R E a L D Ata E X A M P L Ementioning

confidence: 94%

Dense 3D residual moveout analysis as a tool for HTI parameter estimation

Kozlov

Varivoda

2004

Geophysical Prospecting

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“…The covariance for the least‐squares estimates of the model parameters (from the NMO ellipse) can be formulated as ( Tarantola 1987; Al‐Dajani and Alkhalifah 1997)…”

Section: Error Analysismentioning

confidence: 99%

“…orthorhombic media), using three P‐wave NMO‐velocity measurements along three distinct survey directions (azimuths), we can unambiguously identify the orientation and the semi‐axes of the NMO‐velocity ellipse (the NMO velocities along the symmetry planes). Unlike the HTI inverse problem ( Al‐Dajani and Alkhalifah 1997), we do not have the capability either to distinguish between the two symmetry planes or to obtain the anisotropic parameters individually. However, we can estimate the difference between the anisotropic parameters δ (1) and δ (2) .…”

Section: Error Analysismentioning

confidence: 99%

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Reflection moveout inversion in azimuthally anisotropic media: accuracy, limitations and acquisition

Al-Dajani

Alkhalifah

Morgan

1999

Geophysical Prospecting

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Parameter estimation from the elliptical variations in the normal‐moveout (NMO) velocity in azimuthally anisotropic media is sensitive to the angular separation between the survey lines in 2D, or equivalently, the source‐to‐receiver azimuth in 3D, and to the set of azimuths used in the inversion procedure. The accuracy in estimating the orientation of an NMO ellipse, in particular the parameter α, is also sensitive to the magnitude of anisotropy. On the other hand, the accuracy in estimating the semi‐axes of the NMO‐velocity ellipse is about the same for any magnitude of anisotropy. To invert for the NMO ellipse parameters at least three NMO‐velocity measurements along distinct azimuth directions are needed. In order to maximize the accuracy and stability in parameter estimation, it is best to have the azimuths for the three source‐to‐receiver directions 60° apart. Having more than three distinct source‐to‐receiver azimuths (e.g. full azimuthal coverage) provides a useful data redundancy that enhances the quality of the estimates. In order to maximize quality in the inversion process, it is recommended to design the seismic data acquisition such that it contains small sectors (≤10°) with adequate fold and offset distribution. Using three NMO‐velocity measurements, 60° apart, an azimuthally anisotropic layer overlain by an azimuthally isotropic overburden (as might occur for fractured reservoirs) should have a relative thickness (in time) with respect to the total thickness at least equal to the ratio of the error in the NMO (stacking) velocity to the interval anisotropy of the fractured layer. Coverage along more than three azimuths, however, improves this limitation, which is imposed by Dix differentiation, by at most 50%, depending on the number of observations (NMO velocities) that enter the inversion procedure.

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Moveout inversion ofP-wave data for horizontal transverse isotropy

1999

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The transversely isotropic model with a horizontal symmetry axis (HTI media) has been extensively used in seismological studies of fractured reservoirs. In this paper, a parameter-estimation technique originally developed by Grechka and Tsvankin for the more general orthorhombic media is applied to horizontal transverse isotropy. Our methodology is based on the inversion of azimuthally-dependent P-wave normal-moveout (NMO) velocities from horizontal and dipping reflectors. If the NMO velocity of a given reflection event is plotted in each azimuthal direction, it forms an ellipse determined by three combinations of medium parameters. The NMO ellipse from a horizontal reflector in HTI media can be inverted for the azimuth β of the symmetry axis, the vertical velocity V P0 , and the Thomsen-type anisotropic parameter δ (V). We describe a technique for obtaining the remaining (for P-waves) anisotropic parameter η (V) (or (V)) from the NMO ellipse corresponding to a dipping reflector of arbitrary azimuth. The interval parameters of vertically inhomogeneous HTI media are recovered using the generalized Dix equation that operates with NMO ellipses for horizontal and dipping events. High accuracy of our method is confirmed by inverting a synthetic multiazimuth P-wave data set generated by ray tracing for a layered HTI medium with depth-varying orientation of the symmetry axis. Although estimation of η (V) can be carried out by the algorithm developed for orthorhombic media, for more stable results the HTI model has to be used from the outset of the inversion procedure. It should be emphasized that P-wave conventional-spread moveout data provide enough information to distinguish between HTI and lower-symmetry models. We show that if the medium has the orthorhombic symmetry and is sufficiently different from HTI, the best-fit HTI model cannot match the NMO ellipses for both a horizontal and a dipping event. The anisotropic coefficients responsible for P-wave moveout can be combined to estimate the crack density and predict whether the cracks are fluid-filled or dry. A unique feature of the HTI model that distinguishes it from both vertical transverse isotropy and orthorhombic media is that moveout inversion provides not just zerodip NMO velocities and anisotropic coefficients, but also the true vertical velocity. As a result, reflection P-wave data acquired over HTI formations can be used to build velocity models in depth and perform anisotropic depth processing.

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Reflection moveout inversion in azimuthally anisotropic media

Cited by 4 publications

References 2 publications

Dense 3D residual moveout analysis as a tool for HTI parameter estimation

Dense 3D residual moveout analysis as a tool for HTI parameter estimation

Reflection moveout inversion in azimuthally anisotropic media: accuracy, limitations and acquisition

Moveout inversion ofP-wave data for horizontal transverse isotropy

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