DTW seismic body attribute analysis method for automatically and rapidly identifying geological structures

Abstract

The invention discloses a DTW seismic body attribute analysis method for automatically and rapidly identifying geological structures. A distributed parallel algorithm is adopted for dividing a workingcell; under the coarse mesh density, DTW time offsets of feature point sequences of seismic channels and model reference channels are calculated, so that horizons and seismic isochronal stratigraphicframeworks can be quickly interpreted and constructed; on the basis of well layering, interlayer equal-proportion method based subdivision is performed to form a seismic layered data body, so that the number of sample points for DTW calculation is reduced, the data independence is guaranteed, the advantages of distributed operation can be effectively brought into play, and the calculation time ofDTW attributes is greatly shortened. The DTW calculation of the adjacent channels is performed in two directions of Inline and Xline; and abnormal characteristics of weak continuity and low similarity between seismic data of a target layer section are highlighted, so that fine identification of the structures with different scales is realized.

Description

technical field [0001] The invention discloses a DTW seismic body attribute analysis method for automatically and quickly identifying geological structures, belonging to the technical field of seismic exploration. Background technique [0002] Seismic attributes refer to the kinematics, dynamics and statistical measurements extracted from the time series of artificial earthquakes. Compared with the initial seismic profile data, the attribute data can highlight the travel time and amplitude of seismic waves caused by geological structures such as faults and collapse columns. Abnormal horizontal and vertical discontinuity and low similarity of , frequency and phase. According to the attribute dimension, it can be divided into two types: two-dimensional and three-dimensional. Two-dimensional attributes are usually instantaneous or fixed hour window attributes calculated along a certain level, and volume attributes are data volumes in three-dimensional space. Based on three-di...

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Problems solved by technology

[0004] At present, using reflection seismic exploration data and seismic multi-attribute analysis technology for structural interpretation, faults with a drop of 5m and above, and collapse columns with a diameter of 30m and above can be identified. However, it is still far from the requirements of comprehensive mechanized mining for modern coal mineralization. Structural interpretations such as faults and subsidence columns smaller than the above-mentioned scales have strong multi-solutions and are greatly affected by empirical factors.

[0005] The dynamic time warping algorithm (DTW) can analyze the similarity of two time series more finely, but its fine solution grows geometrically as the length of the time series increases, and the calculation efficiency is extremely low, which has not been seen for 3D seismic massive data. feasible solution

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