Pre-stack non-linear inversion method based on particle swarm optimization algorithm

A nonlinear and inversion technology, applied in the field of oil and gas field exploration, can solve problems such as complex group behavior, reduce human error and improve accuracy

Inactive Publication Date: 2013-01-02
CHINA UNIV OF PETROLEUM (BEIJING)
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Problems solved by technology

Many creatures in nature have certain group behaviors, such as flocks of birds, fish schools, etc. Although a single individual in the group has only simple behavior rules, the behavior of the group formed is very complicated

Method used

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  • Pre-stack non-linear inversion method based on particle swarm optimization algorithm
  • Pre-stack non-linear inversion method based on particle swarm optimization algorithm
  • Pre-stack non-linear inversion method based on particle swarm optimization algorithm

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Embodiment Construction

[0052] Illustrate with a synthetic gather:

[0053] Firstly, the Zoplitz equation was used to perform forward modeling on the model, and the reflection coefficients of each layer within the range of 1° to 30° were calculated every 3°. The calculated 10 reflection coefficient sequences are respectively convoluted with the 40Hz zero-phase Reker wavelet, and the synthetic seismic records obtained, that is, the angle gather data are as follows: figure 2 shown.

[0054] These ten angle gather data are used as input for inversion. To solve the calculated longitudinal wave reflection coefficient R pp The minimum error function E between the actual seismic record is used as the objective function. The steps of pre-stack inversion using particle swarm optimization algorithm are as follows:

[0055] (1) The angle gather record obtained by the forward modeling of the model is taken as the observed value (true value).

[0056] (2) Use the particle swarm optimization algorithm to gen...

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Abstract

The invention relates to a pre-stack non-linear inversion method based on a particle swarm optimization algorithm. Along with the sustained and steady growth of the economy of the country, the need for energy sources is also sustainedly and quickly increased and a serious test of shortage of oil and natural gas resources can inevitably appear. Reservoir prediction is an important research link in oil exploration production; information (contained in a seismic data) about structure, lithology and the like of subsurface formation needs to be fully utilized to find high-quality reservoirs; the information is frequently obtained through seismic inversion; but the conventional inversion is based on a linear and simplified model and is disturbed by a plurality of human factors, and high-precision reservoir parameters frequently cannot be obtained. According to the method, a research on the topic of the particle swarm optimization algorithm is carried out; the Zoeppritz equation is deduced and simplified on the basis of the idea and the principle of the particle swarm optimization algorithm to ensure that the equation is suitable for the solution of the particle swarm optimization algorithm; the particle swarm optimization algorithm is used for the pre-stack inversion; and the pre-stack inversion is respectively carried out on the two-dimensional theoretical model and a offshore seismic data so as to obtain a satisfactory result.

Description

technical field [0001] The invention relates to the technical field of oil and gas field exploration, belongs to the category of seismic data inversion, and specifically solves the non-linear seismic inversion problem through particle swarm optimization algorithm. Background technique [0002] Reservoir lithology identification and fluid prediction using seismic data has always been the goal pursued by geophysicists. The theoretical basis of seismic prestack inversion (AVO inversion) is the famous Zoeppritz equations. Ostrander (1984) found that "the reflection amplitude of gas-bearing sandstone increases with the increase of offset, and the reflection amplitude of water-bearing sandstone decreases with the increase of offset" in the process of studying the seismic amplitude characteristics of "bright spot" sandstone reservoirs. This phenomenon has greatly improved the ability of hydrocarbon detection, drawn people's attention from post-stack to pre-stack, and marked the em...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01V1/28
Inventor 孙赞东陈蕾张远银
Owner CHINA UNIV OF PETROLEUM (BEIJING)
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