A method for identifying hidden faults

Abstract

The invention discloses a concealed fault identification method based on fault growth mechanism and seismic attribute prediction. The method includes the following steps: (a) interpreting the structure of seismic data, counting the growth and development characteristics of regional faults, and determining the main fault; (b) according to the relationship between the main fault throw and distance position change determined in step (a), Make a "fault distance-distance" curve; (c) find the point where the fault distance value of the "fault distance-distance" curve decreases, and preliminarily predict the location of hidden fault development; (d) scan and extract fault attributes for the post-stack space 3D seismic body Feature map, judge the fault path according to the abnormal response in the map; (e) When the predicted position in step (c) also meets the step (d) fault attribute map to identify the fault path response, it is interpreted as a hidden fault. Compared with the existing identification methods, this method is more effective in identifying hidden faults.

Description

Technical field: [0001] The invention relates to a fault identification method, in particular to a method for accurately identifying concealed faults based on fault growth mechanism and seismic attribute optimization algorithm. Background technique: [0002] Fracture structures are also called fractures. Rocks are subjected to in-situ stress, and when the force exceeds the compressive strength of the rock itself, it will break in the weak areas of the rock. It is a process that occurs over a very wide range of scales and is a major factor in the deformation of sedimentary basins. Large-scale faults can usually be identified through two-dimensional or three-dimensional seismic data interpretation, but there are still some small faults with short extension lengths, small fault throws, and low grades, which are called hidden faults. Subtle faults refer to faults below the resolution range of seismic reflection data, that is, due to their small scale or poor quality of seismic ...

AI Technical Summary

Problems solved by technology

②By adopting the coherent body technology that adds formation dip angle, direction adjustment and filter analysis, and using random line scanning to confirm the occurrence of faults, the interpretation efficiency and accuracy can be effectively improved, but the identification is difficult and cannot be automatically identified. Only relying on Manual experience identification is difficult to operate; ③neural network training identification method can greatly improve the efficiency of fault identification, but the fault combination is difficult and needs to be carefully screened by interpreters in the later stage. At the same time, there is a problem of weak generalization. High data, fault identification is very difficult, and the effect is not ideal

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