Bayesian seismic inversion for stratigraphic horizon, lithology, and fluid prediction
نویسندگان
چکیده
منابع مشابه
Bayesian lithology/fluid inversion—comparison of two algorithms
Algorithms for inversion of seismic prestack AVO data into lithology-fluid classes in a vertical profile are evaluated. The inversion is defined in a Bayesian setting where the prior model for the lithology-fluid classes is a Markov chain, and the likelihood model relates seismic data and elastic material properties to these classes. The likelihood model is approximated such that the posterior ...
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We consider a Bayesian model for doing lithology–fluid prediction from prestack (amplitude versus offset) seismic data. Related to the Bayesian model, we look at two inversion algorithms. The first algorithm simulates from the posterior distribution with no approximations, but the algorithm is quite computer demanding. The second inversion algorithm introduces an approximation in the likelihood...
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The focus of our study is lithology/fluid inversion with spatial coupling from prestack seismic amplitude variation with offset AVO data and well observations. The inversion is defined in a Bayesian setting where the complete solution is the posterior model. The prior model for the lithology/fluid LF characteristics is defined as a profile Markov randomfield model with lateral continuity. Each ...
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Here in, an application of a new seismic inversion algorithm in one of Iran’s oilfields is described. Stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. This method integrates information from different data sources with different scales, as prior informat...
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Joint inversion of different geophysical data sets has recently received considerable attention. Different geophysical methods are sensitive to different physical properties and their variations on different scales, and joint inversion provides a way to combine these complementary information contained in each data set by integrating all the geophysical data into a single inversion scheme. The ...
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ژورنال
عنوان ژورنال: GEOPHYSICS
سال: 2020
ISSN: 0016-8033,1942-2156
DOI: 10.1190/geo2019-0170.1