Glutenite sedimentary facies seismic prediction method based on complete ensemble empirical mode decomposition

An overall empirical mode, earthquake prediction technology, applied in seismic signal processing and other directions, can solve the problems of lack of earthquake prediction technology, unclear seismic response characteristics, lack of facies zone identification and classification standards, etc.

Active Publication Date: 2019-06-14
CHINA PETROLEUM & CHEM CORP +1
View PDF6 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] (1) The sedimentary sub-(micro) facies of glutenite have small differences in well logging and various petrophysical parameters, and there is a lack of fine facies belt identification and division standards
[0010] (2) The seismic response characteristics of various sedimentary sub (micro) facies of glutenite are unclear, and the differences in sensitive characteristic parameters are unclear
[0011] (3) Seismic prediction technology for sedimentary sub-(micro) facies is lacking

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
  • Glutenite sedimentary facies seismic prediction method based on complete ensemble empirical mode decomposition
  • Glutenite sedimentary facies seismic prediction method based on complete ensemble empirical mode decomposition
  • Glutenite sedimentary facies seismic prediction method based on complete ensemble empirical mode decomposition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0120] Example: Seismic identification and plane division of sedimentary microfacies near the shore of the subaqueous fan in the Daxie 722 well area of ​​the actual work area.

[0121] Step 1, the original seismic data volume ( Image 6 ), using the complete overall empirical mode decomposition method to decompose the seismic data into multiple intrinsic mode function components ( Figure 7 , Figure 8 ).

[0122]Step 2, using the reconstruction algorithm to obtain the modal function components with certain frequency components ( Figure 9 );

[0123] Step 3: Perform structure-preserving smoothing filtering on the reconstructed modal function components in the time-space domain, filter out random noise added in the process of empirical mode decomposition, and improve the signal-to-noise ratio (SNR) of each modal function component ( Figure 10 );

[0124] Step 4: Research on the algorithm of seismic attribute extraction along the bed for the original seismic data volume a...

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 glutenite sedimentary facies seismic prediction method based on complete ensemble empirical mode decomposition. The method comprises the following steps that: S1: aiming at apost-stack three-dimensional seismic data volume, adopting a complete ensemble empirical mode decomposition method to decompose the seismic data into a plurality of natural mode function components;S2: adopting a reconfiguration algorithm to obtain each mode function component with certain frequency ingredients; S3: carrying out protection construction smooth filtering on each mode function component obtained by reconstruction in a time-space domain; S4: carrying out horizon seismic attribute extraction algorithm researching, and establishing a glutenite seismic facies identification mark; and S5: constructing a glutenite seismic facies sensitive characteristic parameter to realize glutenite sedimentary facies seismic prediction. By use of the glutenite sedimentary facies seismic prediction method based on the complete ensemble empirical mode decomposition, the inherent rich information of the seismic data is used, and a glutenite sedimentary facies prediction ability is improved.

Description

technical field [0001] The invention relates to the field of geological exploration and development of glutenite seismic identification and prediction, in particular to a glutenite sedimentary facies seismic prediction method based on complete overall empirical mode decomposition. Background technique [0002] Glutenite reservoirs are very complex, with large differences in reservoir physical properties, oil content and productivity, making efficient exploration and development difficult. For example, Well Daxie 722 in the Taoerhe area of ​​the Chengnan fault zone saw good industrial oil flow in the Lower Sha 3, but then in Well Da 722-1 drilled in its northeast, the reservoir thinned rapidly and its physical properties deteriorated lead to failure. According to the analysis, the drastic vertical and horizontal changes of glutenite sedimentary sub-(micro) facies lead to strong heterogeneity of reservoirs and large differences in productivity. The key to glutenite reservoir...

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
Inventor 宋亮于正军韩宏伟张秀娟张鹏夏志威孙淑英孙兴刚
Owner CHINA PETROLEUM & CHEM CORP
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