Multi-pore reservoir pre-stack seismic probabilistic multi-channel inversion method

A pre-stack seismic and seismic reflection technique used in the fields of quantitative characterization of hydrocarbon-bearing reservoirs, petrophysical modeling and pre-stack seismic inversion

Active Publication Date: 2021-06-15
CHINA UNIV OF PETROLEUM (EAST CHINA)
View PDF6 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the inversion problem of rock physical parameters in multi-porous reservoirs, the present invention fully considers the influence of rock pore structure on rock elastic modulus and seismic AVO reflection amplitude, and provid

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Multi-pore reservoir pre-stack seismic probabilistic multi-channel inversion method
  • Multi-pore reservoir pre-stack seismic probabilistic multi-channel inversion method
  • Multi-pore reservoir pre-stack seismic probabilistic multi-channel inversion method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0214] Embodiment 1: theoretical model test, see for details Figure 8 , Figure 9 , Figure 10 .

[0215] In order to more clearly illustrate the noise resistance and reliability of the AVO inversion algorithm in this paper, this patent uses the well logging data resampled by the side channel to carry out a theoretical model test. Figure 8 The middle white dotted line represents the petrophysical parameters calculated from the well logging data. Figure 8 and Figure 9 are the estimated petrophysical parameters when there is no noise and the signal-to-noise ratio is equal to 4, and the white scattered points are the posterior mean of 60 random simulations.

[0216] From Figure 8 It can be seen that the stability of the porosity and hard pore volume fraction inversion results is the highest, which has a strong similarity with the real model, and the degree of dispersion of random sample points generated from the posterior probability density distribution is low. In add...

Embodiment 2

[0218] Embodiment 2: actual data test, see for details Figure 11 , Figure 12 .

[0219] Figure 11 The petrophysical parameters interpreted according to the actual logging data are shown, and the positions of the rectangular dotted boxes represent the positions of four oil-bearing sandstone reservoirs. Figure 12 It is the petrophysical parameter predicted by the inversion of the present invention, the gray line represents the stochastic simulation results of 20 Markov chains, the white scattered point represents the posterior mean solution estimated by the present invention, the dotted line represents the 95% confidence interval of the inversion result, and the white Solid lines represent fluid bulk moduli estimated using conventional prestack seismic inversion methods.

[0220] On the basis of verifying the feasibility of the method and the stability of the algorithm, the present invention applies the method to the seismic exploration example of the Z Oilfield to verify...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

PropertyMeasurementUnit
Depthaaaaaaaaaa
Login to view more

Abstract

The invention discloses a multi-pore reservoir pre-stack seismic probabilistic multi-channel inversion method. The method comprises the following steps: 1, deducing a rock elastic modulus expression containing multiple pore spaces; 2, deducing a seismic reflection coefficient equation represented by the physical property parameters of a multi-pore reservoir; 3, verifying the precision and inversion feasibility of the reflection coefficient of the multi-pore reservoir; 4, constructing posterior probability density distribution and a target functional of to-be-inverted model parameters; 5, researching and developing a pre-stack seismic multi-channel step-by-step inversion algorithm of multi-Markov chain random sampling; and 6, researching and developing a rock physical parameter inversion method based on a step-by-step simulation strategy. According to the method, the influence of the reservoir pore structure on the seismic reflection coefficient is considered, the seismic reflection coefficient parameterization method of the multi-pore reservoir and the pre-stack seismic probabilization multi-channel inversion technology are researched and developed, and stable inversion of parameters such as the multi-pore volume fraction, the fluid volume modulus and the porosity is achieved.

Description

technical field [0001] The invention aims at the field of oil and gas seismic exploration, and relates to petrophysical modeling and pre-stack seismic inversion methods for complex pore reservoirs, especially the quantitative characterization of oil and gas reservoirs such as tight sandstone, carbonate rock and shale. Background technique [0002] Complex oil and gas reservoirs represented by tight sandstone, carbonate rock, and shale have become an important research field for oil and gas exploration and development in recent years. Such reservoirs usually develop pore spaces of various geometric shapes, which are typical multiple-pore reservoirs. layer. The physical parameters and oil and gas properties of multi-porosity reservoirs are closely related to oil and gas reserves and reservoir productivity. In seismic quantitative interpretation, effective prediction and evaluation of physical parameters and hydrocarbon-bearing properties of complex pore reservoirs is a hot to...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G01V1/28G01V1/30
CPCG01V1/282G01V1/306G01V2210/512G01V2210/624G01V2210/6244
Inventor 李坤印兴耀宗兆云
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products