By substituting rock skeleton modulus expressions into Gassmann approximate fluid equation, we obtain a seismic porosity inversion equation. However, conventional rock skeleton models and their expressions are quite d...By substituting rock skeleton modulus expressions into Gassmann approximate fluid equation, we obtain a seismic porosity inversion equation. However, conventional rock skeleton models and their expressions are quite different from each other, resuling in different seismic porosity inversion equations, potentially leading to difficulties in correctly applying them and evaluating their results. In response to this, a uniform relation with two adjusting parameters suitable for all rock skeleton models is established from an analysis and comparison of various conventional rock skeleton models and their expressions including the Eshelby-Walsh, Pride, Geertsma, Nur, Keys-Xu, and Krief models. By giving the two adjusting parameters specific values, different rock skeleton models with specific physical characteristics can be generated. This allows us to select the most appropriate rock skeleton model based on geological and geophysical conditions, and to develop more wise seismic porosity inversion. As an example of using this method for hydrocarbon prediction and fluid identification, we apply this improved porosity inversion, associated with rock physical data and well log data, to the ZJ basin. Research shows that the existence of an abundant hydrocarbon reservoir is dependent on a moderate porosity range, which means we can use the results of seismic porosity inversion to identify oil reservoirs and dry or water-saturated reservoirs. The seismic inversion results are closely correspond to well log porosity curves in the ZJ area, indicating that the uniform relations and inversion methods proposed in this paper are reliable and effective.展开更多
Seismic events are very complex spatial-temporal phenomena. Seismic catalogues, reporting information about spatial-temporal distribution of the main shocks, are nowadays available for many seismic areas in the world,...Seismic events are very complex spatial-temporal phenomena. Seismic catalogues, reporting information about spatial-temporal distribution of the main shocks, are nowadays available for many seismic areas in the world, very often major events mark the beginning of a series of earthquakes （aflershocks） whose frequency and energy are meanly decreasing in time down to the background level of activity. Azerbaijan is one of the most active segments of the Alpine-Himalayan seismic belt and marks the junction between the African-Arabian and Indian plate to the south, and Eurasian plate to the north. The cluster of earthquakes that struck near Varzeghan-Ahar was centered near the Gosha-Dagh fault, but preliminary data suggested that the fault was not responsible for the temblor. On the late afternoon of Saturday, August 11, 2012, the northwest of Iran was shaken by two of the strong earthquakes in Iranian history. First was hit by Mw （moment magnitude scale） = 6.4 Richter at local time 16：54 （12：23 GMT （Greenwich Mean Time））, and about 11 min later, an Mw = 6.3 struck 10 km to the west. The spatial-temporal clustering of micro earthquakes （aftershocks） near Varzeghan, is parameterized by means of a generalized passion model. The region has known faults but numerous smaller or deeply buried faults remain undated, according to the Geological Survey of Iran.展开更多
Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions b...Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.展开更多
基金supported by the National Nature Science Foundation of China(Grant No.41174114)Important National Science and Technology Specific Projects(Grant No.2011ZX05025-005-010)
文摘By substituting rock skeleton modulus expressions into Gassmann approximate fluid equation, we obtain a seismic porosity inversion equation. However, conventional rock skeleton models and their expressions are quite different from each other, resuling in different seismic porosity inversion equations, potentially leading to difficulties in correctly applying them and evaluating their results. In response to this, a uniform relation with two adjusting parameters suitable for all rock skeleton models is established from an analysis and comparison of various conventional rock skeleton models and their expressions including the Eshelby-Walsh, Pride, Geertsma, Nur, Keys-Xu, and Krief models. By giving the two adjusting parameters specific values, different rock skeleton models with specific physical characteristics can be generated. This allows us to select the most appropriate rock skeleton model based on geological and geophysical conditions, and to develop more wise seismic porosity inversion. As an example of using this method for hydrocarbon prediction and fluid identification, we apply this improved porosity inversion, associated with rock physical data and well log data, to the ZJ basin. Research shows that the existence of an abundant hydrocarbon reservoir is dependent on a moderate porosity range, which means we can use the results of seismic porosity inversion to identify oil reservoirs and dry or water-saturated reservoirs. The seismic inversion results are closely correspond to well log porosity curves in the ZJ area, indicating that the uniform relations and inversion methods proposed in this paper are reliable and effective.
文摘Seismic events are very complex spatial-temporal phenomena. Seismic catalogues, reporting information about spatial-temporal distribution of the main shocks, are nowadays available for many seismic areas in the world, very often major events mark the beginning of a series of earthquakes （aflershocks） whose frequency and energy are meanly decreasing in time down to the background level of activity. Azerbaijan is one of the most active segments of the Alpine-Himalayan seismic belt and marks the junction between the African-Arabian and Indian plate to the south, and Eurasian plate to the north. The cluster of earthquakes that struck near Varzeghan-Ahar was centered near the Gosha-Dagh fault, but preliminary data suggested that the fault was not responsible for the temblor. On the late afternoon of Saturday, August 11, 2012, the northwest of Iran was shaken by two of the strong earthquakes in Iranian history. First was hit by Mw （moment magnitude scale） = 6.4 Richter at local time 16：54 （12：23 GMT （Greenwich Mean Time））, and about 11 min later, an Mw = 6.3 struck 10 km to the west. The spatial-temporal clustering of micro earthquakes （aftershocks） near Varzeghan, is parameterized by means of a generalized passion model. The region has known faults but numerous smaller or deeply buried faults remain undated, according to the Geological Survey of Iran.
基金supported by the Special Fund for Meteorological Scientific Research in the Public Interest (Grant No. GYHY201506002, CRA40: 40-year CMA global atmospheric reanalysis)the National Basic Research Program of China (Grant No. 2015CB953703)+1 种基金the Intergovernmental Key International S & T Innovation Cooperation Program (Grant No. 2016YFE0102400)the National Natural Science Foundation of China (Grant Nos. 41305052 & 41375139)
文摘Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.
