首页|Automatic tracking for seismic horizons using convolution feature analysis and optimization algorithm
Automatic tracking for seismic horizons using convolution feature analysis and optimization algorithm
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NSTL
Seismic horizon tracking is a fundamental aspect of seismic data interpretation. However, seismic horizons are typically obtained using manual tracking or a combination of manual tracking and traditional auto-tracking techniques, either of which is a time-consuming and error-prone process. To improve the efficiency and the accuracy of seismic horizon tracking, we developed a convolution feature analysis method on the basis of the traditional coherent technology combined with the Viterbi algorithm, and proposed a method for auto-tracking seismic horizons in complex exploration areas. Firstly, the local seismic waveform data of the target horizon passing through the drilling area have been extracted as the convolution kernel (i.e. the standard seismic trace). Then, the waveform data of each seismic trace in the whole region have been treated with the convolution to obtain the convolution feature in a sliding time window (i.e, the similarity seismic attribute profile). Finally, the convolution feature data have been taken as the inputs, and constraint optimization is performed for the automatic tracking of the seismic horizon. It has the ability to search for the maximum value by integrating the maximum similarity forward and searching for the shortest path method on synthetic and real seismic data. The obtained results show that the proposed method performs effectively for seismic horizons auto-tracking of low signal-to-noise ratio seismic data in complex exploration areas, and also traces the seismic horizons with good continuity and high accuracy.
College of Earth Sciences and Engineering, Shandong University of Science and Technology, Qingdao, Shandong, 266590, China
Key Lab of Submarine Geosciences and Prospecting Techniques, MOE and College of Marine Geosciences, Ocean University of China, Qingdao, Shandong, 266100, China
NSTL
