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Bayesian seismic inversion method based on [tau] distribution

A seismic inversion and inversion technology, which is applied in the field of geophysical inversion and oil and gas reservoir prediction, can solve the problems of low accuracy and resolution of inversion physical parameters, and achieve the effect of improving accuracy and resolution

Active Publication Date: 2018-10-16
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

[0004] The purpose of the present invention is: the present invention provides a Bayesian seismic inversion method based on τ distribution, which solves the problem that the existing seismic inversion adopts Gaussian distribution to simulate seismic reflection coefficient distribution, which leads to low accuracy and resolution of inversion physical parameters question

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  • Bayesian seismic inversion method based on [tau] distribution
  • Bayesian seismic inversion method based on [tau] distribution
  • Bayesian seismic inversion method based on [tau] distribution

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Embodiment 1

[0054] When the inversion parameter is wave impedance, the inversion is as follows:

[0055] Step 1.1: Input well bypass seismic data, original seismic record data s~ and wavelet data w, and interpolate and filter the well bypass parameters to be inverted obtained from well bypass seismic data to obtain the initial model of parameters to be inverted

[0056] Step 1.2: Based on the to-be-inverted parameters of the well-side channel, obtain the wave impedance z of the well-side channel through the recursive relationship between the to-be-inverted parameters of the well-side channel and wave impedance 0 ;

[0057] Step 1.3: From the initial model with parameters to be inverted Select the initial model of the parameters to be inverted corresponding to the side channel in the well, and obtain the initial model z of the wave impedance of the side channel through recursion s , to calculate the side channel wave impedance z 0 and the initial model z of wellside channel wave impeda...

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Abstract

The invention discloses a Bayesian seismic inversion method based on [tau] distribution, and relates to the geophysical inversion and oil and gas reservoir prediction field. The method comprises the following steps: 1, inputting data to obtain an initial model of parameters to be inverted and determining parameters of [tau] distribution; 2, selecting an initial model of the t-th channel parameteras an iteration initial model, determining a prior probability density distribution function by parameterized [tau] distribution, inputting data to obtain posterior probability density function and performing MCMC inversion to obtain an inversion result; and 3, determining whether t is greater than seismic data in the input data, if yes, ending inversion to obtain a to-be-inverted wave impedance profile based on the inversion result, and if not, accumulating t and jumping to the step 2 for continuous inversion. The method solves the problem that the existing seismic inversion uses the Gaussiandistribution to simulate the seismic reflection coefficient distribution, resulting in the low precision and resolution of inversion physical parameters, and achieves the effect of improving the accuracy and resolution of the inversion physical parameters.

Description

technical field [0001] The invention relates to the field of geophysical inversion and prediction of oil and gas reservoirs, in particular to a Bayesian seismic inversion method based on τ distribution. Background technique [0002] Seismic inversion is an important step in predicting oil and gas reservoirs. It establishes an optimization problem based on the seismic record data known to the detector, through the seismic record data and the mathematical model of the physical quantity to be obtained, and solves the optimization problem through the inversion method , so as to obtain the process of optimal estimation of the physical quantity to be sought. [0003] Bayesian seismic inversion is a seismic inversion technology. It analyzes the known well data and establishes prior information to constrain the optimization problem. According to the Bayesian theory, the process of establishing the optimization problem in the form of the posterior probability density function, Taran...

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Application Information

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IPC IPC(8): G01V1/30G01V1/28
Inventor 彭真明吴昊张明英杨佳晴李曙陈颖频赵学功杨春平何艳敏
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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