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

Semi-quantitative post-stack seismic fracture prediction method

A crack prediction, semi-quantitative technology, applied in seismology, seismic signal processing, measurement devices, etc., can solve problems such as seldom azimuth processing

Pending Publication Date: 2021-09-14
CHENGDU NORTH OIL EXPLORATION DEV TECH
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Seismic acquisition in many oilfields is not wide-azimuth. Even if the wide-azimuth data is collected, it is rarely processed by azimuth. Therefore, the fracture prediction of pre-stack seismic data also has great limitations.

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
  • Semi-quantitative post-stack seismic fracture prediction method
  • Semi-quantitative post-stack seismic fracture prediction method
  • Semi-quantitative post-stack seismic fracture prediction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0033] A method for predicting semi-quantitative post-stack seismic fractures, comprising the following steps: S1 acquiring initial seismic data, performing structure-guided filtering on the initial seismic data to obtain first seismic data S 1 ; S2 to the first seismic data S 1 Perform power exponent operation to obtain the second seismic data S 2 , to increase the participation of weak reflections in the first seismic data, namely where x is the weak reflection enhancement index; S3 uses the third-generation coherent algorithm to analyze the second seismic data S 2 Carry out coherence analysis and dip scanning to obtain the maximum similarity coefficient C of each sample point in the seismic data and the corresponding dip and direction of the maximum similarity coefficient C, and the maximum similarity coefficient C of all sample points is set as the similarity number body; S4 squares the maximum similarity coefficient C of each sample point in the similarity coefficient ...

Embodiment 2

[0036] The present embodiment is further limited on the basis of embodiment 1:

[0037] The value range of the weak reflection enhancement index x is 0.1-0.5, if the strong and weak reflection difference of the first seismic data is large, then the value of x is less than or equal to 0.3; if the strong and weak reflection difference of the first seismic data is small, then x The value is greater than 0.3. The determination of the degree of difference between strong and weak reflections of seismic data is selected according to the actual situation of seismic data. For example, if the difference between strong and weak reflections of seismic data is greater than 5 times or more, it is defined as a large difference between strong and weak reflections of seismic data.

[0038] The specific steps to obtain the maximum similarity coefficient C of each sample point in the seismic data and the dip angle and direction corresponding to the maximum similarity coefficient C are as follows...

Embodiment 3

[0045] Such as Figure 1-Figure 12 , taking the seismic data of an oilfield in the Middle East as an example, in order to carry out fracture prediction, according to a semi-quantitative post-stack seismic fracture prediction method provided by the present invention, the following steps are implemented:

[0046] S1 performs structure-oriented filtering on seismic data to reduce the influence of seismic reflection discontinuity caused by noise in acquisition and processing, static correction and other factors, and highlight the discontinuity characteristics caused by faults and cracks. as attached figure 1 As shown, the original seismic section is relatively not smooth, with figure 2 For the structurally guided seismic section, the continuity of the seismic reflection event is greatly enhanced at the non-fault fractures, and the breakpoints are clearer.

[0047] S2 performs power exponential function calculation S on the seismic data obtained in S1 x , S is the seismic signa...

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 semi-quantitative post-stack seismic fracture prediction method, which relates to the technical field of signal processing methods in the field of oil and gas seismic data interpretation. The method comprises the following steps of S1, obtaining initial seismic data, and carrying out structure guiding filtering on the initial seismic data to obtain first seismic data, S2, performing power exponent operation on the first seismic data S1 to obtain second seismic data S2 so as to improve the participation degree of weak reflection in the first seismic data, S3, using a third-generation coherence algorithm to perform coherence analysis on the second seismic data S2 based on dip angle scanning to obtain the maximum similarity coefficient C of each sample point in the seismic data and the corresponding dip angle and trend, and gathering the maximum similarity coefficients C of all sample points into a similarity number body, S4, enabling the maximum similarity coefficient C of each sample point in the similarity coefficient body obtained in the step S3 to be subjected to power respectively, and naming the index of power operation as a discontinuous sharpening index, and S5, completing drawing of a crack prediction result map by adopting a vector statistical mapping method.

Description

technical field [0001] The invention relates to the technical field of signal processing methods in the field of oil and gas seismic data interpretation, in particular to a semi-quantitative post-stack seismic fracture prediction method. Background technique [0002] Fractures are important spaces and channels for oil and gas migration, oil and gas storage, and oil and gas seepage. Fracture prediction is a very important work for the understanding of oil and gas reservoirs in the process of oil and gas field exploration and development. Fracture prediction methods mainly include outcrop geological observation method, core analysis method, imaging logging analysis method, seismic fracture prediction method, etc. The seismic prediction method has the characteristics of wide distribution of data sampling in time and space, and can predict fractures for multiple sets of formations in the entire oilfield within the seismic work area, while the data range of other analysis and pr...

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): G01V1/30G01V1/36G01V1/34
CPCG01V1/307G01V1/362G01V1/345Y02P90/30
Inventor 洪余刚米中荣卢立泽王贺华杨鸿柳世成黄凯张正红袁浩郝成顺杨滔李鑫成一梁利文罗春树瞿建华任本兵刘卉王鹤邓琪张博宁肖勇吕新东曹献平黄静陈哲
Owner CHENGDU NORTH OIL EXPLORATION DEV TECH
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