Signal classification based seismic image horizon tracking method

Abstract

The invention discloses a signal classification based seismic image horizon tracking method. Optimization selection and clustering are carried out on obtained characteristic parameters by using an FSSCEM algorithm without manual intervention, inclination texture attributes are combined with related searching methods and applied to subsequent processing after clustering, full horizon tracking on a two-dimensional profile is realized, then a semi-supervised classification method, inclination pointing and a correlation based horizon tracking algorithm are combined, and horizon curved surface precise tracking in a three-dimensional seismic image is realized. The method disclosed by the invention does not need a lot of manual intervention, ensures the reliability of clustering while reducing the calculation amount of a clustering algorithm, and enhances the continuity of horizon identification.

Description

technical field [0001] The invention relates to the field of seismic image processing, in particular to a method for layer tracking of seismic images based on signal classification. Background technique [0002] With the development of the economy, the social demand for oil, natural gas and other resources is increasing. However, to exploit oil and gas, the underground geological structure must first be clear, so seismic interpretation plays an important role in the process of geological exploration. Seismic horizon tracing plays a very important role in seismic interpretation. By means of seismic horizon tracing, strata that may contain oil and gas and the storage depth of oil and gas can be found. [0003] Since the event in the seismic image is a mapping of the geological horizons in the actual geological structure of the exploration area, seismic horizon tracking can be realized by tracking the event in the seismic image. In the process of downward propagation, due to t...

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Problems solved by technology

[0007] (3) Genetic Algorithm Level Tracking Algorithm: The specific idea is to use a model-based method to deal with the problem of crossing faults, and then convert the problem into a constrained optimization problem, and then use the genetic algorithm to solve it. There are two methods in this method: Problems: One is the degree of approximation to complex geological conditions; the other is the problem of solution accuracy and suboptimal solutions

[0008] (4) The full horizon tracking algorithm based on finite mixture Gaussian is suitable for complex geological environments, but requires manual intervention and cannot fully realize the automatic extraction and separation of horizons

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