Oil Seismic Monitoring Data Compression Method Study

Seismic data is one of the important parameters of oil exploration and production in the acquisition, which can effectively reflect the geology of oil fields and oil content changes. Due to the enormous amount of seismic data and the need for real-time delivery to provide the analytical basis for the transmission of oil exploration and production, has brought a lot of problems in computer storage and data transmission. To promote the oilfield automatic integration process, meet the needs of real-time data transmission, to address the problem, this paper studies the oil seismic data compression methods.The paper analyzes the present situation of the compression method, according to the characteristics of petroleum seismic data and the characteristics of DB4, wavelet transformation has the multi-resolution analysis function, transform the oil seismic data to the wavelet domain, and decomposition of seismic signals with wavelet transformation, select soft threshold compression algorithm to process the low-frequency coefficients of wavelet, wavelet threshold quantization the data to achieve the purpose of noise reduction This paper further investigates the basic principle of traditional LZ77lossless compression algorithm, discusses the existing problems and the insufficiency of the traditional compression methods, proposed changing the unique code output form and method of extended sliding Dictionary to optimize traditional algorithms. By simulation of compression time, compression ratio, reduction time and compression ratio, which demonstrated that applying this optimization methods in petroleum seismic data the compression effect was improved than the traditional method.By setting the minimum matching multiple to reduce the redundancy of oil seismic data, this article introduced Huffman coding to store the data. The simulation of seismic data compression algorithm proves that the optimized compression effect is relatively good, computing speed, the reconstruction accuracy is relatively high, proves better results in solving the problem of oilseismic data compression.