Gassmann's equations are commonly used for predicting seismic wave velocity in rock physics research.However the input matrix mineral bulk modulus parameters are not accurate,which greatly influences the prediction r...Gassmann's equations are commonly used for predicting seismic wave velocity in rock physics research.However the input matrix mineral bulk modulus parameters are not accurate,which greatly influences the prediction reliability.In this paper,combining the Russell fluid factor with the Gassman-Biot-Geertsma equation and introducing the dry-rock Poisson's ratio,we propose an effective matrix mineral bulk modulus extraction method.This method can adaptively invert the equivalent matrix mineral bulk modulus to apply the Gassmann equation to fluid substitution of complex carbonate reservoirs and increase the fluid prediction reliability.The verification of the actual material fluid substitution also shows that this method is reliable,efficient,and adaptable.展开更多
For the past 20 years, numerous studies have been carried out on the application of equilibrium partitioning approach (EqPA) for the derivation of sediment quality guidelines (SQGs). However, for metals, few Equil...For the past 20 years, numerous studies have been carried out on the application of equilibrium partitioning approach (EqPA) for the derivation of sediment quality guidelines (SQGs). However, for metals, few Equilibrium-partitioning- based numerical SQGs have been developed or are currently available because of the confounding factors mediating the bioavailability of metals. A study was conducted at Dianchi Lake, which is a heavily eutrophicated lake on the Yunnan- Guizhou Plateau, China with the focus on the measurement of partitioning coefficient (Kp) and SQGs derivation and normalization to acid volatile sulfide (AVS), fine material, and organic carbon. Using new normalization methods, SQGs were formulated for seven metals including copper, zinc, lead, cadmium, chromium, mercury, and arsenic in Dianchi Lake. In Dianchi Lake sediments, the fine material contributed 25.4%-36.0% to the SQG values, with the largest contribution to the SQG value of mercury; AVS contributed 2.9%-75.0% to the SQG values, with the largest contribution to the SQG value of cadmium. This indicated that the fine material and the AVS were the most important controlling factors to the bioavailability of mercury and caximium, respectively. The contribution of total organic carbon (TOC) to the SQG values of copper and leaxi was 3.8% and 7.1%, respectively, indicating that at relatively lower concentrations, the contribution of TOC was not significant. In addition to normalization methods, appropriate procedures for the application of EqPA including sample collection, storage, and analysis are also essential to improve the reliability of SQGs. The normalized Dianchi Lake SQGs were higher than most of the empirically based SQGs developed in North America, but lower than Hong Kong interim SQGs except for cadmium and arsenic. The differences could be attributed to the approaches used for derivation of SQGs and the water quality criteria adopted and the differences in the physical and chemical characteristics of the sediments.展开更多
基金sponsored by National Natural Science Foundation of China(Grant No.40904035)
文摘Gassmann's equations are commonly used for predicting seismic wave velocity in rock physics research.However the input matrix mineral bulk modulus parameters are not accurate,which greatly influences the prediction reliability.In this paper,combining the Russell fluid factor with the Gassman-Biot-Geertsma equation and introducing the dry-rock Poisson's ratio,we propose an effective matrix mineral bulk modulus extraction method.This method can adaptively invert the equivalent matrix mineral bulk modulus to apply the Gassmann equation to fluid substitution of complex carbonate reservoirs and increase the fluid prediction reliability.The verification of the actual material fluid substitution also shows that this method is reliable,efficient,and adaptable.
基金Project supported by the State Key Laboratory of Soil and Sustainable Agriculture, China (No. 5022505)the National Natural Science Foundation of China (No. 40771128)
文摘For the past 20 years, numerous studies have been carried out on the application of equilibrium partitioning approach (EqPA) for the derivation of sediment quality guidelines (SQGs). However, for metals, few Equilibrium-partitioning- based numerical SQGs have been developed or are currently available because of the confounding factors mediating the bioavailability of metals. A study was conducted at Dianchi Lake, which is a heavily eutrophicated lake on the Yunnan- Guizhou Plateau, China with the focus on the measurement of partitioning coefficient (Kp) and SQGs derivation and normalization to acid volatile sulfide (AVS), fine material, and organic carbon. Using new normalization methods, SQGs were formulated for seven metals including copper, zinc, lead, cadmium, chromium, mercury, and arsenic in Dianchi Lake. In Dianchi Lake sediments, the fine material contributed 25.4%-36.0% to the SQG values, with the largest contribution to the SQG value of mercury; AVS contributed 2.9%-75.0% to the SQG values, with the largest contribution to the SQG value of cadmium. This indicated that the fine material and the AVS were the most important controlling factors to the bioavailability of mercury and caximium, respectively. The contribution of total organic carbon (TOC) to the SQG values of copper and leaxi was 3.8% and 7.1%, respectively, indicating that at relatively lower concentrations, the contribution of TOC was not significant. In addition to normalization methods, appropriate procedures for the application of EqPA including sample collection, storage, and analysis are also essential to improve the reliability of SQGs. The normalized Dianchi Lake SQGs were higher than most of the empirically based SQGs developed in North America, but lower than Hong Kong interim SQGs except for cadmium and arsenic. The differences could be attributed to the approaches used for derivation of SQGs and the water quality criteria adopted and the differences in the physical and chemical characteristics of the sediments.