Characteristics of deuterium excess parameters for geothermal water in Beijing

This study investigates the characteristics of geothermal water in 10 geothermal fields in Beijing. The relationships between the deuterium excess parameter (d) and temperature, depth, age of geothermal groundwater, groundwater flow field, and Eh were investigated using geothermal groundwater samples. Results showed that (1) the average d value of geothermal water is 5.4, whereas that of the groundwater in normal temperature is 6.04. The differences are induced by the oxygen isotope exchange during the water–rock interaction, which may be more easily completed in geothermal water than in cold groundwater. (2) The d value increases remarkably with the age of the geothermal groundwater. The d value increases from 11.2 to 14.6 when the age of the geothermal water is 12,760 ± 130 a and 38,960 ± 630 a, respectively. Moreover, the isotope heat exchange for composition of the hydrogen and oxygen isotopes in the geothermal groundwater proceeds sufficiently with time. (3) The d value decreases from 5.72 to 3.03 when the depth increases from 125.13 to 3221 m. Generally, in the same area, the d value decreases with depth because the temperature is increasing. (4) The d value of the groundwater gradually reduces from the northern recharge area to the southern discharge area. The average d value is 7.31 in the northern recharge area and 5.68 in the middle Beijing Depression, whereas the d value in the southern area of Fengheying is ?9.20. The larger difference in d values between the recharge and discharge areas is due to the slower velocity of underwater flow, which induces longer time for oxygen exchange. (5) The relationship between the d and Eh is complex. When Eh is <200 mV, the d value of the geothermal water decreases with the decrease in Eh. When Eh is higher than 200 mV, the d value increases slightly with the decrease in Eh. The study of the characteristics of deuterium excess parameters for geothermal water could provide a scientific isotopic evidence for assessment and exploitation measures in geothermal groundwater systems.     

Application of the non-seismic geophysical method in the deep geological structure study of Benxi-Huanren area

Based upon 1:200,000 regional gravity and aeromagnetic data, gravity and aeromagnetic slice maps were obtained through fast Fourier transformation (FFT) upward continuation. A comparison between gravity and aeromagnetic slice maps at different depths combined with regional geological data and Magneto-Telluric sounding reveals the deep geological structure of Benxi-Huanren area and provides important information for study of the deep geological evolution process of Benxi-Huanren area. Yanshanian granitic pluton is widely distributed in this area and tends to be continuous toward depth. Significant metallogenic areas, such as Dataigou and Nanfen areas, lie above the buried granitic pluton. The Paleoproterozoic strata distribution area and the Archean strata distribution area have similar characteristics in terms of gravity anomaly. The iron-bearing formation in Anshan area is Archean supracrustal rock which was not engulfed by Archean granite. The thickness of Liaoji paleo-rift can be up to 10 km, whose lower part was intruded by Yanshanian granites. The basement of the Liaoji rift was remelted during granite intrusion in Yanshanian period.     

Geological characteristics and origin of the Hadamengou gold deposit in Inner Mongolia,China

The Hadamengou gold deposit is located in the western segment of the northern margin of the North China Craton (NCC). It is hosted by Archean metamorphic rocks of the Wulashan Group. The main ore types include gold-bearing quartz vein type, gold-bearing quartz-potassic feldspar vein type, and gold-bearing altered rock type. Gold mineralization is closely related to K-feldspathization. Hydrogen and oxygen isotope data indicate that ore-forming fluids were dominated by magmatic water mixed with minor meteoric water. Sulfur and lead isotope data indicate that metallogenic materials were mainly supplied by the magmatic and Archean Wulashan Group. The gold mineralization was mainly formed during the Early Indosinian tectonic movement, which drove ore-forming fluids to the favorable depositional environment. The northern margin of the NCC is a prospective area for gold exploration. Gold deposits hosted by or related to alkaline intrusions have become one of the most important mineral exploration targets in northern China.     

Intrinsic groundwater vulnerability determination at the aquifer scale: a methodology coupling travel time estimation and rating methods

Groundwater vulnerability has been subject of much research due to the valuable information it provides concerning groundwater protection and exploitation potential. Up to now, most groundwater vulnerability studies adopt subjective systems of rating the various factors and subsequently, their results are often ambiguous and contradicting. Within the present study a methodology for the estimation of intrinsic groundwater vulnerability at the aquifer scale is presented. The methodology is based on travel time estimation from specified sources of pollution to the aquifer. Besides the deterministic calculation of travel times, the methodology provides a rating system for each pollution source, based on its relative severity and the estimated threat that it poses to the aquifer. Therefore, it can be regarded as a hybrid method that couples the advantages provided by the physically based methods with those of the subjective rating systems. The methodology is applied to the Neon Sidirochorion aquifer, Northeastern Greece, an overexploited aquifer where river waters, sea waters and lake waters interact, causing groundwater quality deterioration to the aquifer. The results indicated that the proposed groundwater vulnerability assessment methodology is well capturing pollution related to saltwater intrusion and agricultural activities, while it is concluded that the conceptual model is significantly affecting the vulnerability assessment results and therefore has to be previously developed.     

Estimation of air-overpressure produced by blasting operation through a neuro-genetic technique

Blasting operations usually produce significant environmental problems which may cause severe damage to the nearby areas. Air-overpressure (AOp) is one of the most important environmental impacts of blasting operations which needs to be predicted and subsequently controlled to minimize the potential risk of damage. In order to solve AOp problem in Hulu Langat granite quarry site, Malaysia, three non-linear methods namely empirical, artificial neural network (ANN) and a hybrid model of genetic algorithm (GA)–ANN were developed in this study. To do this, 76 blasting operations were investigated and relevant blasting parameters were measured in the site. The most influential parameters on AOp namely maximum charge per delay and the distance from the blast-face were considered as model inputs or predictors. Using the five randomly selected datasets and considering the modeling procedure of each method, 15 models were constructed for all predictive techniques. Several performance indices including coefficient of determination (R ²), root mean square error and variance account for were utilized to check the performance capacity of the predictive methods. Considering these performance indices and using simple ranking method, the best models for AOp prediction were selected. It was found that the GA–ANN technique can provide higher performance capacity in predicting AOp compared to other predictive methods. This is due to the fact that the GA–ANN model can optimize the weights and biases of the network connection for training by ANN. In this study, GA–ANN is introduced as superior model for solving AOp problem in Hulu Langat site.     

Application and performances of unconstrained optimization methods in seafloor AVO inversion

Seafloor elastic parameters are important for seafloor engineering and geophysical detection beneath the seafloor. We have proposed to use AVO (amplitude variation with offset) theory to estimate seafloor elastic parameters. However, the previous inversion methods are time-consuming. To improve the computing efficiency, we try to solve the inverse problem as an unconstrained optimization problem in this paper. Three kinds of classical unconstrained optimization methods are applied to seafloor AVO inversion, including the steepest descent method, the Newton’s method, and the conjugate gradient method. Then, we design different initial models to test the convergence behaviors of the three methods. Numerical tests show that the perturbation level of the initial models and the noise level of the observed data have a significant effect on the convergence performances of the three methods. Even for the same perturbation and noise levels, the convergence performances differ with different combinations of the perturbed initial elastic parameters. All three methods have higher computing efficiency than the previous methods. This research also offers a strategy to choose a proper optimization method for a specific case in real seafloor AVO inversion.