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Multi-parameter amalgamation gas deposit detection method for earthquake

A detection method and multi-parameter technology, applied in seismic signal processing, seismology for logging records, etc., which can solve the problems of inconsistent detection results of multiple observations, incomplete collection of geophysical data, and complex underground environment.

Active Publication Date: 2009-05-13
PETROCHINA CO LTD
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  • 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

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  • 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

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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

[0081] 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.

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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

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Application Information

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IPC IPC(8): G01V1/40G01V1/28G01V1/30G01V1/36
Inventor 石玉梅
Owner PETROCHINA CO LTD
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