Fracture detection method and system based on time-frequency decomposition

Abstract

The invention discloses a fracture detection method and system based on time-frequency decomposition, and relates to the field of oil and gas physical geography. The method comprises the following steps: obtaining post-stack seismic data of a target layer segment; performing time-frequency decomposition processing on the post-stack seismic data to obtain an amplitude spectrum that changes with thedominant frequency; and performing fracture detection processing on the target layer segment according to the amplitude spectrum that changes with the dominant frequency to obtain a fracture distribution condition of the target layer segment. According to the fracture detection method and system disclosed by the invention, an adaptive spectrum analysis method is imported to serve as a prior processing process based on the calculation of the geometric property of the fracture detection to obtain the amplitude spectrum that changes with the dominant frequency, and the fracture detection processing is performed on the target layer segment according to the amplitude spectrum that changes with the dominant frequency to achieve the fast and accurate detection and identification of formation fracture that changes with the depth.

Description

technical field [0001] The invention relates to the field of oil and gas geophysics, in particular to a fracture detection method and system based on time-frequency decomposition. Background technique [0002] The development and distribution of faults or fractures (referred to as faults) is very important to the storage and accumulation of oil and gas, and is an important factor affecting high-yield reservoirs. In order to better carry out oil and gas detection for reservoir evaluation, the detection and identification of faults is very important. For post-stack seismic data, fault detection technology based on geometric attributes can better identify seismic waveform changes to identify fault boundaries, and is widely used. [0003] However, the geometric attributes will be affected by the quality of seismic data during the calculation process. Seismic data with poor data quality will lead to low signal-to-noise ratio or resolution of fault detection results. Contents o...

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Problems solved by technology

[0003] However, the geometric attributes will be affected by the quality of seismic data during the calculation process. Seismic data with poor data quality will lead to low signal-to-noise ratio or resolution of fault detection results.

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