Micro-seismic monitoring is one of the most critical technologies that guide hydraulic fracturing in hot dry rock resource development. Micro-seismic monitoring requires high precision detection of micro-seismic event...Micro-seismic monitoring is one of the most critical technologies that guide hydraulic fracturing in hot dry rock resource development. Micro-seismic monitoring requires high precision detection of micro-seismic events with a low signal-to-noise ratio. Because of this requirement, we propose a recurrent neural network model named gated recurrent unit and support vector machine(GRU;VM). The proposed model ensures high accuracy while reducing the parameter number and hardware requirement in the training process. Since micro-seismic events in hot dry rock produce large wave amplitudes and strong vibrations, it is difficult to reverse the onset of each individual event. In this study, we utilize a support vector machine(SVM) as a classifier to improve the micro-seismic event detection accuracy. To validate the methodology, we compare the simulation results of the short-term-average to the long-term-average(STA/LTA) method with GRU;VM method by using hot dry rock micro-seismic event data in Qinghai Province, China. Our proposed method has an accuracy of about 95% for identifying micro-seismic events with low signal-to-noise ratios. By ignoring smaller micro-seismic events, the detection procedure can be processed more efficiently, which is able to provide a real-time observation on the types of hydraulic fracturing in the reservoirs.展开更多
Because of the various elements that come into play in natural soil formation, the impact of varied proportions of mineral composition and fines amount on Atterberg limits and compaction characteristics of soils is no...Because of the various elements that come into play in natural soil formation, the impact of varied proportions of mineral composition and fines amount on Atterberg limits and compaction characteristics of soils is not well known. Three distinct soil samples were used in this investigation. The findings indicated the effect of varied mineral composition proportions and fines amount on the liquid limit, plastic limit, and plasticity index as assessed by the Casagrande test and hand-rolling method. The fluctuation of maximum dry density and optimal moisture content with these three soils has also been studied. Furthermore, correlations were established to indicate the compaction parameters and the amount of minerals and particles in the soil. The data show that the mineral content of the soil has a direct impact on the Atterberg limits and compaction characteristics. Soils containing larger percentages of expansive minerals, such as montmorillonite, have more flexibility and volume change capability. Mineral composition influences compaction parameters such as maximum dry density, ideal water content, axial strain, and axial stress. Soils with a larger proportion of fines, such as Soil 2 and Soil 3, have stronger flexibility and lower compaction qualities, with higher ideal water content and lower maximum dry density. Soil 1 has moderate flexibility and intermediate compaction qualities due to its low fines percentage. The effect of different mineral compositions and fines on the Atterberg limits and compaction characteristics of soils can be used to predict the behavior of compacted soils encountered in engineering practices, reducing the time and effort required to assess soil suitability for engineering use.展开更多
基金supported by National Key R&D Program of China(Grant No.2018YFB1501803,2019YFC1804805-4)China Geological Survey Project(Grant No.DD2019135)。
文摘Micro-seismic monitoring is one of the most critical technologies that guide hydraulic fracturing in hot dry rock resource development. Micro-seismic monitoring requires high precision detection of micro-seismic events with a low signal-to-noise ratio. Because of this requirement, we propose a recurrent neural network model named gated recurrent unit and support vector machine(GRU;VM). The proposed model ensures high accuracy while reducing the parameter number and hardware requirement in the training process. Since micro-seismic events in hot dry rock produce large wave amplitudes and strong vibrations, it is difficult to reverse the onset of each individual event. In this study, we utilize a support vector machine(SVM) as a classifier to improve the micro-seismic event detection accuracy. To validate the methodology, we compare the simulation results of the short-term-average to the long-term-average(STA/LTA) method with GRU;VM method by using hot dry rock micro-seismic event data in Qinghai Province, China. Our proposed method has an accuracy of about 95% for identifying micro-seismic events with low signal-to-noise ratios. By ignoring smaller micro-seismic events, the detection procedure can be processed more efficiently, which is able to provide a real-time observation on the types of hydraulic fracturing in the reservoirs.
文摘Because of the various elements that come into play in natural soil formation, the impact of varied proportions of mineral composition and fines amount on Atterberg limits and compaction characteristics of soils is not well known. Three distinct soil samples were used in this investigation. The findings indicated the effect of varied mineral composition proportions and fines amount on the liquid limit, plastic limit, and plasticity index as assessed by the Casagrande test and hand-rolling method. The fluctuation of maximum dry density and optimal moisture content with these three soils has also been studied. Furthermore, correlations were established to indicate the compaction parameters and the amount of minerals and particles in the soil. The data show that the mineral content of the soil has a direct impact on the Atterberg limits and compaction characteristics. Soils containing larger percentages of expansive minerals, such as montmorillonite, have more flexibility and volume change capability. Mineral composition influences compaction parameters such as maximum dry density, ideal water content, axial strain, and axial stress. Soils with a larger proportion of fines, such as Soil 2 and Soil 3, have stronger flexibility and lower compaction qualities, with higher ideal water content and lower maximum dry density. Soil 1 has moderate flexibility and intermediate compaction qualities due to its low fines percentage. The effect of different mineral compositions and fines on the Atterberg limits and compaction characteristics of soils can be used to predict the behavior of compacted soils encountered in engineering practices, reducing the time and effort required to assess soil suitability for engineering use.
