Research On Low SNR Micro Seismic Monitoring Methods And Technology

With the development of oil and gas exploration, hydraulic fracturing and micro-seismic monitoring technology is widely used in the late development of traditional oil and gas fields and the emerging unconventional oil and gas field development. Oil and gas development in the water, gas injection, hot drive or fracturing, the subterranean formation to crack or fracture, producing seismic waves. The technology in adjacent wells through the detector to monitor the process fracturing wells fracturing induced micro-seismic waves to describe the process of crack growth fracture geometry and spatial distribution. The technology monitor the induced micro-seismic waves from fracturing by the detector in the adjacent well to describe the geometry and spatial distribution of crack growth. It can provide real-time fracturing produce fissures height, length and azimuth, with what we can optimize fracturing design, optimization of well field development network or other measures to improve oil recovery. Compared with natural earthquakes and conventional seismic exploration, micro-seismic has low intensity, high frequency, and short duration.This paper describes the mechanism and character of the formation, acquisition, processing and interpretation techniques of micro-seismic monitoring. Fracturing and acquisition program design, signal processing, wave field separation, polarization analysis, first break picking, forward and inverse analysis, are all important steps in micro-seismic monitoring, In the micro-seismic monitoring, subject to the influence of high noise, micro-seismic signals received are often low signal to noise ratio, so the micro-seismic signal processing, identification and first break picking of micro-seismic event has become the most critical aspect in the entire process.Methods of data processing and interpretation of micro-seismic monitoring are from natural earthquakes and conventional seismic exploration, In this paper, the noise generated records of earthquakes, types and characteristics were analyzed, introduced the commonly used denoise methods of seismic data. In this paper, a KL transform method of processing micro-seismic data were discussed, and the traditional frequency analysis methods are reviewed since the Fourier transform, S Transform respectively is derived from both the short time Fourier transform and wavelet transform, characteristics summarized:Directly contact with the Fourier transform, the process is non-destructive reversible; A linear time-frequency representation, between wavelet transform and short time Fourier transform, without interference cross terms. Resolution is directly related to signal frequency; without the admissibility conditions of basic wavelet. In this paper, these time-frequency analysis methods are comprehensively compared, the S transform frequency resolution has obvious advantages in linear transformations, no cross-term interference with respect to the quadratic transformation. Combined with the Micro seismic signal characteristics, the paper choose S transform for micro seismic events recognition and signal reconstruction.Unpredictable spectral of random noise and overlap between the micro wave seismic signal makes processing difficult. After denoising processing of low SNR signals, it is easy distorted. In the process of signal processing, signal fidelity and the SNR improve is an important balance in the implementation of the algorithm.Conventional seismic phase picking methods include an energy ratio method, AIC method, fractal dimension, neural networks, et al. This paper discusses algorithm of energy ratio method, AIC method and other traditional first break picking methods of micro seismic signal, summarizes the strengths and weaknesses of algorithms:energy ratio method is simple, effective, but affected by the length of time window. AIC method could accurately pick, but could not effectively identify whether the signal include micro-seismic events or not. On the basis of higher signal to noise ratio micro-seismic signal reconstructed by the S transform, This paper designs a two-step method:first with the energy ratio method to identify micro-seismic events, and then picked up by AIC method for accurate. This method isn’t affected by the length of time window, pick up the first break of reconstructed signals efficiently and accurately.Aiming low SNR micro seismic signals, the S transform is used for time-frequency analysis and signal reconstruction. A two-step method of the first break picking is designed to get more accurate information for the fracturing effect inversion and interpretation, thus achieving to optimize fracturing programs.