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• W2012351921 abstract "Ashley Francis, managing director of UK consultancy Earthworks Environment & Resources, provides the first of a two-part tutorial on the theory of deterministic and stochastic inversion with some comparison of the pros and cons of the two methods. The second part will appear in the December issue of First Break. Seismic inversion tools designed to estimate impedance have been available to geophysicists for over 20 years. Most of the available methods are based on forward convolution of a reflectivity model with the estimated wavelet, comparison of the modelled output with the observed seismic trace and then updating the reflectivity model (inverting) to minimize the difference between the modelled and observed traces. Whether generalized linear inversion, sparse spike, or simulated annealing, all the algorithms work on this basic principle of minimization. Methods based on minimization are commonly referred to as ‘deterministic’. The output of a deterministic inversion is a relatively smooth (or blocky) estimate of the impedance. Because of its smoothness deterministic inversion is generally unsuited for constraining reservoir models used for volumetric calculations, estimation of connectivity, or fluid flow simulation. Stochastic seismic inversion generates a suite of alternative heterogeneous impedance representations that agree with the 3D seismic volume. Taken together, the suite of possible impedance models or realizations capture the uncertainty or non-uniqueness associated with the seismic inversion process. Stochastic seismic inversion is complementary to deterministic inversion. The deterministic seismic inversion is the average of all the possible non-unique stochastic realizations. Although the principles of stochastic seismic inversion were published over 12 years ago, commercial implementation and application have only started to grow in the last five years or so. For many geophysicists, understanding and being able to make a discerning judgement on the possible benefits of this new technique is difficult. A number of misconceptions concerning stochastic seismic inversion have arisen, particularly related to resolution. A commonplace but incorrect statement is that stochastic techniques can ‘…allow substantially increased resolution, capturing details well beyond seismic bandwidth’. It is the purpose of this tutorial to provide a clear theoretical basis for deterministic and stochastic inversion and assist the geophysicist in making an informed decision concerning the application of stochastic seismic inversion to his or her particular reservoir description problem. In order to understand stochastic seismic inversion we will have to understand some of the limitations of conventional seismic inversion (often referred to as ‘deterministic’ inversion), provide a grounding in some geostatistical concepts, and also consider the general problem of estimation at unmeasured locations. This tutorial will only consider seismic inversion in the sense of estimating an impedance model of the subsurface. ‘Impedance’ will be taken in a very general sense to refer to any rock property estimated from surface seismic data. This could include acoustic or elastic impedance, extended elastic impedance, or any other more elaborate pre-stack inversion scheme to estimate Vp, Vs, and density. Stochastic inversion may be applied to any of these objectives and the aim of this tutorial is to describe only the general limitations of deterministic inversion and the possible advantages of a stochastic inversion framework and not to consider the specifics of pre-or post-stack inversion objectives." @default.
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• W2012351921 date "2006-11-01" @default.
• W2012351921 modified "2023-09-30" @default.
• W2012351921 title "Understanding stochastic inversion: part 1" @default.
• W2012351921 doi "https://doi.org/10.3997/1365-2397.2006026" @default.
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