3-D geochemical interpolation guided by geophysical inversion models

3-D geochemical subsurface models,as constructed by spatial interpolation of drill-core assays,are valuable assets across multiple stages of the mineral industry's workflow.However,the accuracy of such models is limited by the spatial sparsity of the underlying drill-core,which samples only a small fraction of the subsurface.This limitation can be alleviated by integrating collocated 3-D models into the interpolation process,such as the 3-D rock property models produced by modern geophysical inversion procedures,provided that they are sufficiently resolved and correlated with the interpolation target.While standard machine learning algorithms are capable of predicting the target property given these data,incorporating spatial autocorrelation and anisotropy in these models is often not possible.We propose a Gaussian process regression model for 3-D geochemical interpolation,where custom kernels are introduced to integrate collocated 3-D rock property models while addressing the trade-off between the spatial proximity of drill-cores and the similarities in their collocated rock properties,as well as the relative degree to which each supporting 3-D model contributes to interpolation.The proposed model was evaluated for 3-D modelling of Mg content in the Kevitsa Ni-Cu-PGE deposit based on drill-core analyses and four 3-D geophysical inversion models.Incorporating the inversion models improved the regression model's likelihood(relative to a purely spatial Gaussian process regression model)when evaluated at held-out test holes,but only for moderate spatial scales(100 m).

Swarm intelligence optimization and its application in geophysical data inversion

The inversions of complex geophysical data always solve multi-parameter, nonlinear, and multimodal optimization problems. Searching for the optimal inversion solutions is similar to the social behavior observed in swarms such as birds and ants when searching for food. In this article, first the particle swarm optimization algorithm was described in detail, and ant colony algorithm improved. Then the methods were applied to three different kinds of geophysical inversion problems： （1） a linear problem which is sensitive to noise, （2） a synchronous inversion of linear and nonlinear problems, and （3） a nonlinear problem. The results validate their feasibility and efficiency. Compared with the conventional genetic algorithm and simulated annealing, they have the advantages of higher convergence speed and accuracy. Compared with the quasi-Newton method and Levenberg-Marquardt method, they work better with the ability to overcome the locally optimal solutions.

Metallogenic model of the Shuangjianzishan Ag-Pb-Zn district,Northeast China:Revealed from integrated geophysical investigation

The Shuangjianzishan deposit in Inner Mongolia is a typical Ag-Pb-Zn deposit of the southern Great Xing’an Range.Proven reserves of Ag,Pb,and Zn in this deposit have reached the scale of super-large deposits,with favorable metallogenic conditions,strong prospecting signs,and high metallogenic potential.This paper reports a study involving integrated geophysical methods,including controlled-source audio-frequency magnetotelluric,gravity,magnetic,and shallow-seismic-reflection methods,to determine the spatial distribution of ore-controlling structures and subsurface intrusive rock for a depth range of<2000 m in the Shuangjianzishan ore district.The objective of this study is to construct a metallogenic model of the ore district and provide a scientific basis for the exploration of similar deposits in the deep and surrounding regions.We used three-dimensional inversion for controlled-source audio-frequency magnetotelluric data based on the limited memory quasi-Newton algorithm,and three-dimensional physical-property inversion for the gravity and magnetic data to obtain information about the subsurface distribution of ore-controlling structures and intrusive rocks.Under seismic reflection results,regional geology,petrophysical properties,and borehole information,the geophysical investigation shows that the Dashizhai group,which contains the main ore-bearing strata in the ore district,is distributed within a depth range of<1239 m,and is thick in the Xinglongshan ore block and the eastern part of the Shuangjianzishan ore block.The mineralization is spatially associated with a fault system characterized by NE-,NW-,and N-trending faults.The magnetic and electrical models identify large,deep bodies of intrusive rock that are inferred to have been involved in mineralization,with local shallow emplacement of some intrusions.Combining the subsurface spatial distributions of ore-bearing strata,ore-controlling faults,and intrusive rock,we propose two different metallogenic models for the Shuangjianzishan ore district,which provide a scientific basis for further prospecting in the deep regions of the ore district and surrounding areas.

Improvements on particle swarm optimization algorithm for velocity calibration in microseismic monitoring

In this paper, we apply particle swarm opti- mization （PSO）, an artificial intelligence technique, to velocity calibration in microseismic monitoring. We ran simulations with four 1-D layered velocity models and three different initial model ranges. The results using the basic PSO algorithm were reliable and accurate for simple models, but unsuccessful for complex models. We propose the staged shrinkage strategy （SSS） for the PSO algorithm. The SSS-PSO algorithm produced robust inversion results and had a fast convergence rate. We investigated the effects of PSO＇s velocity clamping factor in terms of the algorithm reliability and computational efficiency. The velocity clamping factor had little impact on the reliability and efficiency of basic PSO, whereas it had a large effect on the efficiency of SSS-PSO. Reassuringly, SSS-PSO exhibits marginal reliability fluctuations, which suggests that it can be confidently implemented.

Deep Structure and Dynamics of Passive Continental Margin from Shelf to Ocean of the Northern South China Sea

To study the deep dynamic mechanism leading to the difference in rifting pattern and basin structure from shelf to oceanic basin in passive continental margin, we constructed long geological sections across the shelf, slope and oceanic basin using new seismic data. Integrated gravity-magnetic inversion and interpretation of these sections were made with the advanced dissection method. Results show that the basement composition changes from intermediate-acid intrusive rocks in the shelf to intermediate-basic rocks in the slope. The Moho surface shoals gradually from 31 km in the shelf to 22.5 km in the uplift and then 19 km in the slope and finally to 13 km in the oceanic basin. The crust thickness also decreases gradually from 30 km in the northern fault belt to 9 km in the oceanic basin. The crustal stretching factor increases from the shelf toward the oceanic basin, with the strongest extension under the sags and the oceanic basin. The intensity of mantle upwelling controlled the style of basin structures from shelf to oceanic basin. In the Zhu 1 depression on the shelf, the crust is nearly normal, the brittle and cold upper crust mainly controlled the fault development; so the combinative grabens with single symmetric graben are characteristic. In the slope, the crust thinned with a large stretching factor, affected by the mantle upwelling. The ductile deformation controlled the faults, so there developed an asymmetric complex graben in the Baiyun （白云） sag.

Heterogeneity Spectrum of Earth’s Upper Mantle Obtained from the Coherence of Teleseismic P Waves

Fluctuations in log-amplitude and travel time of teleseismic P waves recorded by the EarthScope USArray are used to invert for the heterogeneity spectrum of P-wave velocity in a 1000 km thick region of the upper mantle beneath the array.These fluctuations are used to form coherence functions.Best fits to joint transverse coherence functions require a depth dependent heterogeneity spectrum,with peaks in narrow depth ranges.These peaks agree well with peaks predicted for the temperature derivative of seismic velocity from models of the chemistry and phase of silicate mineral assemblages appropriate for the upper mantle,correlating with the depths of phase changes.The results show that chemistry and phase act in concert with lateral and depth variations in temperature to produce the observed heterogeneity in seismic velocities in the upper mantle at spatial scales from 50 to 300 km.