Carbonate fluid identification method based on fuzzy c-means clustering

A mean-value clustering and fluid identification technology, applied in the field of petroleum exploration, can solve problems such as difficulty, error, accuracy, etc., achieve the ability to strongly search for the global optimal solution, solve initialization-sensitive problems, and improve fuzzy classification capabilities. Effect

A mean-value clustering and fluid identification technology, applied in the field of petroleum exploration, can solve problems such as difficulty, error, accuracy, etc., achieve the ability to strongly search for the global optimal solution, solve initialization-sensitive problems, and improve fuzzy classification capabilities. Effect

CN103257360BInactive Publication Date: 2016-05-11CHINA UNIV OF PETROLEUM (BEIJING)
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  • Carbonate fluid identification method based on fuzzy c-means clustering
  • Carbonate fluid identification method based on fuzzy c-means clustering
  • Carbonate fluid identification method based on fuzzy c-means clustering

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Embodiment Construction

[0023] The specific embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0024] figure 1 It is a schematic flow chart of the carbonate rock fluid identification method based on fuzzy C-means clustering of the present invention:

[0025] Step 1: Perform pre-stack amplitude-preserving migration on seismic data, and extract CRP gathers of common reflection points;

[0026] Step 2: Perform pre-stack AVO inversion, and calculate various fluid factors based on the inversion results: P-wave impedance, S-wave impedance, and density data volume;

[0027] Step 3: According to the actual situation of the fluid properties revealed by drilling, select the wells drilled in the study area as training samples, and extract the fluid factors corresponding to the reservoir sections of each well for pairwise intersection. Based on the principles of sensitivity and independence, optimize the fluid The combination of sensitive fluid identif...

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Abstract

The invention provides a method for identifying carbonate rock fluid based on a fuzzy C mean cluster in oil exploration. According to the method, chaotic quantum particle swarm optimization (CQPSO) and a fuzzy C mean (FCM) algorithm are organically bonded, chaotic particle swarm optimization is utilized to initialize a membership matrix, the problem that a traditional fuzzy C mean algorithm is sensitive to initialization can be effectively solved, high capability for searching global optimal solution is possessed, and fuzzy classification capability is remarkably improved. The method is introduced into carbonate rock fluid identification, the problem that rock physical analysis results and seismic inversion results are not matched due to frequency dispersion of seismic data can be effectively solved, and identification accuracy of the carbonate rock fluid is improved. Besides, by means of the method, probability of properties of various fluids can be calculated, evaluation on indeterminacy of fluid identification can be conducted so that exploration risks can be effectively reduced, and a new research thought for fully utilizing various prestack elastic information to achieve carbonate rock reservoir fluid identification is provided.

Description

technical field [0001] The invention belongs to the field of petroleum exploration, and relates to the combination of a chaotic quantum particle swarm optimization algorithm and a fuzzy C-means clustering algorithm, and introduces it into carbonate rock fluid identification, so as to fully utilize various pre-stack elastic information to realize carbonate rock Fluid identification provides a new research idea. Background technique [0002] Fluid identification using seismic data is the most important research work in oil and gas exploration. Because pre-stack AVO / AVA inversion retains the shear wave information of the formation, it is sensitive to the characteristics of reservoir fluid changes. Therefore, AVO technology has become an important geophysical tool for fluid detection. One of the means. [0003] Some scholars at home and abroad have done a lot of in-depth research on fluid identification using pre-stack elastic information, and proposed the use of multiple sensi...

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Application Information

Patent Timeline
11 May 2016
Publication
CN103257360B
IPC
G01V1/28; G01V1/30
Inventors
刘立峰; 孙赞东