Microseismic effects during the transmission of seismic waves in coal and rock mass associated with mining operation were studied by on-site blasting tests and microseismic monitoring in LW704 of Southern Colliery,Aus...Microseismic effects during the transmission of seismic waves in coal and rock mass associated with mining operation were studied by on-site blasting tests and microseismic monitoring in LW704 of Southern Colliery,Australia,by using spread velocities,amplitudes and frequency contents as the main analysis parameters.The results show that the average P-wave velocity,mean values of combined maximal amplitudes and frequencies of the first arrivals are all reduced significantly along with goaf expanding and intensity weakening of overlying strata during mining process.A full roof fracturing can make the average P-wave velocities,combined maximal amplitudes and frequencies of first arrivals reduce to about 69.8%,92.2% and 60.0%,respectively.The reduction of the above seismic parameters reveals dynamic effects of the variation of strata structure and property to the wave transmission and energy dissipation of blasting wave.The research greatly benefits further study on stability of surrounding rock under the destructive effort by mine tremor,blasting,etc,and provides experimental basis for source relocation and parameter optimization of seismic monitoring as well.展开更多
Though traditional methods could recognize some facies, e.g. lagoon facies, backshoal facies and foreshoal facies, they couldn't recognize reef facies and shoal facies well. To solve this problem, back propagation...Though traditional methods could recognize some facies, e.g. lagoon facies, backshoal facies and foreshoal facies, they couldn't recognize reef facies and shoal facies well. To solve this problem, back propagation neural network(BP-ANN) and an improved BP-ANN with better stability and suitability, optimized by a particle swarm optimizer(PSO) algorithm(PSO-BP-ANN) were proposed to solve the microfacies' auto discrimination of M formation from the R oil field in Iraq. Fourteen wells with complete core, borehole and log data were chosen as the standard wells and 120 microfacies samples were inferred from these 14 wells. Besides, the average value of gamma, neutron and density logs as well as the sum of squares of deviations of gamma were extracted as key parameters to build log facies(facies from log measurements)-microfacies transforming model. The total 120 log facies samples were divided into 12 kinds of log facies and 6 kinds of microfacies, e.g. lagoon bioclasts micrite limestone microfacies, shoal bioclasts grainstone microfacies, backshoal bioclasts packstone microfacies, foreshoal bioclasts micrite limestone microfacies, shallow continental micrite limestone microfacies and reef limestone microfacies. Furthermore, 68 samples of these 120 log facies samples were chosen as training samples and another 52 samples were gotten as testing samples to test the predicting ability of the discrimination template. Compared with conventional methods, like Bayes stepwise discrimination, both the BP-ANN and PSO-BP-ANN can integrate more log details with a correct rate higher than 85%. Furthermore, PSO-BP-ANN has more simple structure, smaller amount of weight and threshold and less iteration time.展开更多
基金Foundation item: Project(2010CB226805) supported by the National Basic Research Program of ChinaProject(2010QNA30) supported by the Fundamental Research Funds for the Central Universities of China+1 种基金Project supported by the Priority Academic Development Program of Jiangsu Higher Education,ChinaProjects(SZBF2011-6-B35,2012BAK04B06) supported by the National Twelfth Five-year Key Science & Technology Foundation of China
文摘Microseismic effects during the transmission of seismic waves in coal and rock mass associated with mining operation were studied by on-site blasting tests and microseismic monitoring in LW704 of Southern Colliery,Australia,by using spread velocities,amplitudes and frequency contents as the main analysis parameters.The results show that the average P-wave velocity,mean values of combined maximal amplitudes and frequencies of the first arrivals are all reduced significantly along with goaf expanding and intensity weakening of overlying strata during mining process.A full roof fracturing can make the average P-wave velocities,combined maximal amplitudes and frequencies of first arrivals reduce to about 69.8%,92.2% and 60.0%,respectively.The reduction of the above seismic parameters reveals dynamic effects of the variation of strata structure and property to the wave transmission and energy dissipation of blasting wave.The research greatly benefits further study on stability of surrounding rock under the destructive effort by mine tremor,blasting,etc,and provides experimental basis for source relocation and parameter optimization of seismic monitoring as well.
基金Project(41272137) supported by the National Natural Science Foundation of China
文摘Though traditional methods could recognize some facies, e.g. lagoon facies, backshoal facies and foreshoal facies, they couldn't recognize reef facies and shoal facies well. To solve this problem, back propagation neural network(BP-ANN) and an improved BP-ANN with better stability and suitability, optimized by a particle swarm optimizer(PSO) algorithm(PSO-BP-ANN) were proposed to solve the microfacies' auto discrimination of M formation from the R oil field in Iraq. Fourteen wells with complete core, borehole and log data were chosen as the standard wells and 120 microfacies samples were inferred from these 14 wells. Besides, the average value of gamma, neutron and density logs as well as the sum of squares of deviations of gamma were extracted as key parameters to build log facies(facies from log measurements)-microfacies transforming model. The total 120 log facies samples were divided into 12 kinds of log facies and 6 kinds of microfacies, e.g. lagoon bioclasts micrite limestone microfacies, shoal bioclasts grainstone microfacies, backshoal bioclasts packstone microfacies, foreshoal bioclasts micrite limestone microfacies, shallow continental micrite limestone microfacies and reef limestone microfacies. Furthermore, 68 samples of these 120 log facies samples were chosen as training samples and another 52 samples were gotten as testing samples to test the predicting ability of the discrimination template. Compared with conventional methods, like Bayes stepwise discrimination, both the BP-ANN and PSO-BP-ANN can integrate more log details with a correct rate higher than 85%. Furthermore, PSO-BP-ANN has more simple structure, smaller amount of weight and threshold and less iteration time.
