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

Multi-parameter amalgamation gas deposit detection method for earthquake

A detection method, multi-parameter technology, applied in seismic signal processing, seismology for logging records, etc. question

Active Publication Date: 2011-05-25
PETROCHINA CO LTD
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Due to the complex underground environment, incomplete geophysical data collection and measurement errors, the acquisition of geophysical signals is uncertain
There are two defects in the above seismic gas reservoir detection methods: one is that they lack the ability to accurately describe the uncertainty of observation data and detection results; Inconsistent, i.e. low accuracy

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-parameter amalgamation gas deposit detection method for earthquake
  • Multi-parameter amalgamation gas deposit detection method for earthquake
  • Multi-parameter amalgamation gas deposit detection method for earthquake

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0050] There are two targets in the system, which are gas reservoirs (target a) and non-gas reservoirs (target b), then the identification frame of gas reservoirs is Θ={a, b}, and the focal elements are {a}, {b} and {a, b}. There are 4 properties, Lame constant, shear modulus, density and Poisson's ratio, with A i said, A i ={Lame constant, shear modulus, density, Poisson's ratio}. Let's take the Lame constant as an example (other attribute parameters are similar), and the specific implementation steps are:

[0051] 1. Collect seismic data, perform conventional pre-stack denoising, surface consistent amplitude compensation, static correction and dynamic correction to form gather data.

[0052] 2. Use the conventional pre-stack seismic inversion method to invert the Lame constant, shear modulus, and density (observation data) of the formation from the gather data, and calculate Poisson's ratio, and use the following formula to calculate Lame constant, shear modulus Gaussian...

example 2

[0080] The gas field in Example 2 is a braided river deposit, with large lateral variation and poor continuity of the reservoir. The difference between Example 2 and Example 1 is that it has three attributes, namely, P-wave velocity, S-wave velocity and Poisson's ratio. Obtain m in the same way as Example 1 vp (a), m vp (b), m vp (a, b), m vs (a), m vs (b), m vs (a, b) and m σ (a), m σ (b), m σ (a,b). to m vp (a), m vs (a) and m σ (a) is fused to get m(a); for m vp (b), m vs (b) and m σ (b) fusion, get m(b); m vp (a, b), m vs (a, b) and m σ (a, b) is fused to get m(a, b). Gas reservoir detection is performed according to the values ​​of m(a), m(b) and m(a, b). Figure 4 The gas reservoir prediction results of a survey line are shown. There are only 2 wells on this line, both of which are gas wells, consistent with the predicted results.

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

A seismic multi-parameter fusion gas reservoirs detection method belongs to hydrocarbon detection in the geophysical exploration. The method comprises the following steps: acquiring and processing seismic data, extracting various attribute parameters, calculating a membership grade function, acquiring conventional sonic logging data and density logging data to form a synthetic trace by seismic wavelet convolution, and calculating the matching degree between observation data and the gas reservoirs or non-gas reservoirs and the confidence values of various observation data, and fusing the confidence values of all attribute parameters to obtain the multi-parameter fusion gas reservoirs, the non-gas reservoirs and the confidence value of an uncertain region and determine the gas reservoirs. The method exactly depicts the uncertainty of the seismic data by the membership grade function in a fuzzy set theory, and a support interval, a confidence interval and a rejection interval in an evidence theory and an evidence fusion law. The method improves the prediction accuracy rate to above 80% from 70% in the conventional methods, which significantly improves the success rate of the gas reservoirs drilling.

Description

technical field [0001] The invention relates to a geophysical prospecting hydrocarbon detection technology, and is a seismic multi-parameter fusion gas reservoir detection method. Background technique [0002] In the hydrocarbon detection technology of geophysical exploration, besides the "bright spot" technology and AVO technology for natural gas reservoir detection using seismic data, more and more people pay more and more attention to the comprehensive detection method of multiple information. [0003] Commonly used multi-parameter fusion gas reservoir detection methods include pattern recognition and neural network. The pattern recognition method is to obtain the well logging data first, and then use the well logging data as learning samples, classify the learning samples according to the well testing results, and extract the seismic attributes of well side channels through calibration and combine them. Determine the coefficients of each attribute according to the princ...

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 Patents(China)
IPC IPC(8): G01V1/40G01V1/28G01V1/30G01V1/36
Inventor 石玉梅
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