Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Facies-controlled porosity inversion method based on Bayesian classification

A technology of porosity inversion and Bayesian classification, which is applied in the field of petroleum geological exploration, can solve the problems of restricting wide application, and achieve the effect of reducing multi-solution and improving accuracy

Active Publication Date: 2017-04-05
PETROCHINA CO LTD
View PDF6 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that many parameters need to be provided in advance. In addition to the four parameters in the Gassmann equation other than porosity, stress, pore pressure, fluid viscosity coefficient, and seismic wave attenuation coefficient are also required. Too many input parameters are limited. The wide application of this method

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
  • Facies-controlled porosity inversion method based on Bayesian classification
  • Facies-controlled porosity inversion method based on Bayesian classification
  • Facies-controlled porosity inversion method based on Bayesian classification

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0066] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0067] see figure 1 , which shows a flowchart of a phase-controlled porosity inversion method based on Bayesian classification according to an embodiment of the present invention. The phase-controlled porosity inversion method based on Bayesian classification includes the following steps:

[0068] (1) Intersection analysis is performed on the log curves of the rock porosity obtained from the actual measurement of the target reservoir area and the log curves of various rock elastic parameters obtained through laboratory tests, so as to obtain at least one parameter sensitive to the rock porosity Rock elastic parameter data;

[0069] (2) Screening rock porosity and rock elastic parameter data under constraint conditions to obtain scree...

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

No PUM Login to View More

Abstract

The invention discloses a facies-controlled porosity inversion method based on Bayesian classification and belongs to the technical field of petroleum geology exploration. The facies-controlled porosity inversion method includes the following steps: 1. perform cross analysis on a well logging curve of rock porosity and the well logging curve of a plurality of rock elastic parameters which is acquired through experiment tests to acquire the rock elastic parameter data sensitive to the rock porosity; 2. acquiring the screened porosity and the screened elastic parameter data; 3. establishing a borehole-seism initial model and also acquiring the prior probability distribution of the screened porosity; 4. acquiring resample porosity and also acquiring fitting screening elastic parameter data and fitting resampling elastic parameter data; 5. acquiring resampling errors; 6. acquiring reconstructed elastic parameter data; 7. acquiring the prior sample series and conducting Bayesian classification to acquire the prior probability distribution and posterior probability distribution; and 8. conducting Bayesian inversion to transform a known elastic parameter data volume to a porosity data volume.

Description

technical field [0001] The invention relates to the technical field of petroleum geological exploration, in particular to a phase-controlled porosity inversion method based on Bayesian classification. Background technique [0002] Porosity is one of the important parameters to characterize the characteristics of oil and gas reservoirs. Reservoir porosity is a key parameter in oil and gas exploration and development, and plays a key role in reservoir prediction and structural interpretation. Seismic porosity can be used for lateral prediction of reservoirs in the seismic exploration stage; while in development, the porosity can be calibrated by well logging to describe the reservoir, and the porosity is also an important reference for reserve estimation. [0003] Currently, there are two main types of seismic porosity inversion methods. One is to use the velocity to calculate the porosity according to the relationship between porosity and seismic wave propagation velocity. ...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G01V1/30
CPCG01V1/306
Inventor 田建章刘力辉秦凤启孙莹频常建华杜维良张传宝闫宝义王雪萍马红岩屈伟玉魏岩叶秋焱
Owner PETROCHINA CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com