Joint inversion of AVA data for elastic parameters by bootstrapping
نویسنده
چکیده
A joint inversion method is developed to estimate the elastic constants of two elastic, homogeneous, isotropic media separated by a flat horizontal boundary. The method jointly uses P and S-converted wave reflection amplitude-versusangle (AVA) data and seeks the Poisson’s ratios of each layer, ratios of the densities and bulk modulus of the layers. The generalized linear inversion (GLI) method is used as a mathematical tool and the Zoeppritz equations defining the seismic energy partitioning at a boundary are used as the physical model. The P and S-converted wave velocity terms in the Zoeppritz equations were replaced by the bulk modulus ðk1; k2Þ, Poisson’s ratios ðs1; s2Þ, and densities ðr1; r2Þ of each layer. After expressing the equations in these six elastic constants, reflection coefficients of P and S-converted waves ðRpp;RpsÞ are obtained as functions of ratios of bulk modulus and densities of the lower layer to those of the upper layer (k2=k1 and r2=r1) and Poisson’s ratios of the upper and lower layers (s1 and s2Þ. Using the ratios of bulk modulus and densities, the number of unknown parameters is reduced from 6 to 4 and this improves the success of inversion. The other contribution is that the calculation of Rpp and Rps and their derivatives with respect to elastic constants and their ratios in the inversion are calculated analytically and coded in the Fortran programming language. In this way, the approach has an important advantage among the other AVA inversion methods, which are mostly based on numerical solutions or approximations to the Zoeppritz equations. A bootstrapping method of statistical analysis is combined with the GLI method to find the most likely elastic parameters and their confidence limits for repeated inversions for a large number of times by rearranging the noise distribution of the AVA data. r 2006 Elsevier Ltd. All rights reserved.
منابع مشابه
Estimation of facies probabilities on the Snorre field using geostatistical AVA inversion
We have done a geostatistical inversion of seismic data to facies probabilities. As a first step, we invert the seismic data for elastic parameters using the Bayesian AVA inversion method of Buland et. al. (2003). Next, we use an analysis of the uncertainty in the posterior distribution to filter the elastic parameters given in well logs. By comparing these filtered well logs with facies logs, ...
متن کاملCapability of the Stochastic Seismic Inversion in Detecting the Thin Beds: a Case Study at One of the Persian Gulf Oilfields
The aim of seismic inversion is mapping all of the subsurface structures from seismic data. Due to the band-limited nature of the seismic data, it is difficult to find a unique solution for seismic inversion. Deterministic methods of seismic inversion are based on try and error techniques and provide a smooth map of elastic properties, while stochastic methods produce high-resolution maps of el...
متن کاملIterative linearized migration and inversion
The objective of seismic imaging is to obtain an image of the subsurface reflectors, which is very important for estimating whether a reservoir is beneficial for oil/gas exploration or not. It can also provide the relative changes or absolute values of three elastic parameters: compressional wave velocity Vp, shear wave velocity Vs , and density ρ. Two ways can achieve the objectives. In approa...
متن کاملAmplitude Variation with Offset Inversion Analysis in One of the Western Oilfields of the Persian Gulf
Reservoir characterization has a leading role in the reservoir geophysics and reservoir management. Since the interests of the reservoir geophysics and reservoir managements are the elastic properties and reservoir properties of the subsurface rock for their purposes, a robust method is required for converting seismic data into elastic properties. Accordingly, by employing a rock physics model ...
متن کاملJoint Bayesian Stochastic Inversion of Well Logs and Seismic Data for Volumetric Uncertainty Analysis
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...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Computers & Geosciences
دوره 33 شماره
صفحات -
تاریخ انتشار 2007