First Arrival Time Picking For Microseismic Data Based On DWSW Algorithm

As an important method of oil and gas reservoir exploration,the first arrival time picking technology uses fluid fracturing techniques to dispose the data of crack height,length and direction which come from the Three-component detector near the target well,then imaging the fracturing leading edge of water conservancy and the monitoring of fracture and gas resource status is realized.The microseismic technique has unique advantages in order to give reasonable evaluation and explanation for the fracturing effect and underground crack in hydraulic fracturing.Therefore,microseismic monitoring technology can provide technical support and corresponding theoretical basis for the adjustment of hydraulic fracturing technology.However,the actual microseismic data are generally low in signal-to-noise ratio,the weak effective signal energy,high frequency and short distance of transmission.It becomes an most important issue to seek an accurate,fast and effective first arrival time picking method in the field of microseismic signal processing.The traditional first arrival time picking method such as the short time and longtime average(STA/LTA)algorithm,Akaike information criterion(AIC)algorithm and kurtosis algorithm can pick the time when dealing with the microseismic data of high signal-to-noise ratio(SNR).When the signal-to-noise ratio(SNR)is low,however,it is difficult to get the first arrival time accurately with traditional methods.In order to solve the problems existing in the traditional algorithms,this paper proposes a new method-DWSW algorithm for first arrival time picking based on W test statistical measurement and combined with SW algorithm,it aims at study the differences in statistical characteristics between the effective signals and background noise of microseismic.Compared with the traditional algorithm,the DWSW method is used to detect the first arrival time by making full use of the differences between background noise and effective signals in the statistical properties.Specifically speaking,we obtain the moment corresponding to the maximum as the first arrival time of microseismic data when the statistic of our method reaches its maximum.Hence,we get the accurate picking time when the SNR of microseismic is low.In addition,the parameters of DWSW algorithm are illustrated and demonstrated,in this way,the validity and reliability of parameter setting are proved.To verify the accurate and reliable of DWSW algorithm,we make a large number analysis of the statistical characteristics of effective signal and noise statistical characteristics.The conclusion of the analysis verified that the effective signal and background noise has obvious differences in statistical properties.Then we apply STA/LTA algorithm,AIC algorithm,kurtosis algorithm and our algorithm to both synthetic and field microseismic data with different SNR,respectively.The experimental results show that the picking accuracy of our method is better than the other three method.What's more,in our method,there is no need to select the threshold,which makes the algorithm more facility when the SNR of microseismic data is low.We make and analyzed the accuracy distribution histogram of the above methods.Analysis results indicate that the accuracy rate of the proposed method is superior to the other three method when the SNR is as low as-10 d B and the error range is smaller than the other three algorithms.All in all,DWSW algorithm can solve the problem of time picking when the SNR is low.