Using constrained inversion of gravity and magnetic field to produce a 3D litho‐prediction model

Geologically constrained inversion of gravity and magnetic field data of the Victoria property (located in Sudbury, Canada) was undertaken in order to update the present three‐dimensional geological model. The initial and reference model was constructed based on geological information from over 950 drillholes to constrain the inversion. In addition, downhole density and magnetic susceptibility measured in six holes were statistically analysed to derive lower and upper bounds on the physical properties attributed to the lithological units in the reference model. Constrained inversion of the ground gravity and the airborne magnetic data collected at the Victoria property were performed using GRAV3D and MAG3D, respectively. A neural network was trained to predict lithological units from the physical properties measured in six holes. Then, the trained network was applied on the three‐dimensional distribution of physical properties derived from the inversion models to produce a three‐dimensional litho‐prediction model. Some of the features evident in the lithological model are remnants of the constraints, where the data did not demand a significant change in the model from the initial constraining model (e.g., the thin pair of diabase dykes). However, some important changes away from the initial model are evident; for example, a larger body was predicted for quartz diorite, which may be related to the prospective offset dykes; a new zone was predicted as sulfide, which may represent potential mineralisation; and a geophysical subcategory of metabasalt was identified with high magnetic susceptibility and high density. The litho‐prediction model agrees with the geological expectation for the three‐dimensional structure at Victoria and is consistent with the geophysical data, which results in a more holistic understanding of the subsurface lithology.     

Potential of legacy 2D seismic data for deep targeting and structural imaging at the Neves–Corvo massive sulphide-bearing deposit,Portugal

Seismic methods are becoming an established choice for deep mineral exploration after being extensively tested and employed for the past two decades. To investigate whether the early European mineral-exploration datasets had potential for seismic imaging that was overlooked, we recovered a low-fold legacy seismic dataset from the Neves–Corvo mine site in the Iberian Pyrite Belt in southern Portugal. This dataset comprises six 4–6 km long profiles acquired in 1996 for deep targeting. Using today's industry-scale processing algorithms, the world-class, ca. 150 Mt, Lombador massive sulphide and other smaller deposits were better imaged. Additionally, we also reveal a number of shallow but steeply dipping reflections that were absent in the original processing results. This study highlights that legacy seismic data are valuable and should be revisited regularly to take advantage of new processing algorithms and the experiences gained from processing such data in hard-rock environments elsewhere. Remembering that an initial processing job in hard rock should always aim to first obtain an overall image of the subsurface and make reflections visible, and then subsequent goals of the workflow could be set to, for example understanding relative amplitude ratios. The imaging of the known mineralization implies that this survey could likely have been among one of the pioneer studies in the world that demonstrated the capability of directly imaging massive sulphide deposits using the seismic method.     

Experimental and modeling study on Cr(VI) transfer from soil into surface runoff

With the development of modern agriculture, large amount of fertilizer and pesticide outflow from farming land causes great waste and serious pollution to surface water and groundwater, and threatens ecological environment and even human life. In this paper, laboratory experiments are conducted to simulate adsorbed Cr(VI) transfer from soil into runoff. A two-layer in-mixing analytical model is applied to analyze laboratory experimental results. A data assimilation (DA) method via the ensemble Kalman filter (EnKF) is used to update parameters and improve modeling results. In comparison with the experimental data, DA updated modeling results are much better than those without the updating. To make predictions better, the inflation method with a constant inflation factor via DA method was used to compensate the fast decrease of ensemble spread partially related to filter inbreeding. Based on the used rainfall and relevant physical principles, the updated value of the incomplete mixing coefficient γ is about 14.0 times of the value of the incomplete mixing coefficient α in experiment 1 and about 7.4 times in experiment 2, while the difference between the flow rate of runoff and infiltration is not so large even after reaching stable infiltration condition. The results indicate the loss of Cr(VI) in soil solute is mainly due to infiltration, rather than surface runoff. With the increase of mixing layer depth, soil adsorption capacity will increase and the loss of soil solute will decrease. The study results provide information for reducing and even preventing the agricultural nonpoint source pollution.     

Generation of zonal flow by resonant Rossby-Haurwitz wave interactions

Starting out with two interacting Rossby-Haurwitz waves, the generation of zonal flow is discussed. It is shown that zonal flow cannot be generated by first or second order interactions between two such waves, unless they are exchanging energy with a third wave within a resonant triad. The generation of zonal flow at second order through resonant triad interactions is subsequently established and studied.     

Simulating flow in karst aquifers at laboratory and sub-regional scales using MODFLOW-CFP

Groundwater flow in a well-developed karst aquifer dominantly occurs through bedding planes, fractures, conduits, and caves created by and/or enlarged by dissolution. Conventional groundwater modeling methods assume that groundwater flow is described by Darcian principles where primary porosity (i.e. matrix porosity) and laminar flow are dominant. However, in well-developed karst aquifers, the assumption of Darcian flow can be questionable. While Darcian flow generally occurs in the matrix portion of the karst aquifer, flow through conduits can be non-laminar where the relation between specific discharge and hydraulic gradient is non-linear. MODFLOW-CFP is a relatively new modeling program that accounts for non-laminar and laminar flow in pipes, like karst caves, within an aquifer. In this study, results from MODFLOW-CFP are compared to those from MODFLOW-2000/2005, a numerical code based on Darcy’s law, to evaluate the accuracy that CFP can achieve when modeling flows in karst aquifers at laboratory and sub-regional (Woodville Karst Plain, Florida, USA) scales. In comparison with laboratory experiments, simulation results by MODFLOW-CFP are more accurate than MODFLOW 2005. At the sub-regional scale, MODFLOW-CFP was more accurate than MODFLOW-2000 for simulating field measurements of peak flow at one spring and total discharges at two springs for an observed storm event.