Exploring the spatial relationships between various geological features and mineralization is not only conducive to understanding the genesis of ore deposits but can also help to guide mineral exploration by providing predictive mineral maps. However, most current methods assume spatially constant determinants of mineralization and therefore have limited applicability to detecting possible spatially non-stationary relationships between the geological features and the mineralization. In this paper, the spatial variation between the distribution of mineralization and its determining factors is described for a case study in the Dingjiashan Pb–Zn deposit, China. A local regression modeling technique, geological weighted regression (GWR), was leveraged to study the spatial non-stationarity in the 3D geological space. First, ordinary least-squares (OLS) regression was applied, the redundancy and significance of the controlling factors were tested, and the spatial dependency in Zn and Pb ore grade measurements was confirmed. Second, GWR models with different kernel functions in 3D space were applied, and their results were compared to the OLS model. The results show a superior performance of GWR compared with OLS and a significant spatial non-stationarity in the determinants of ore grade. Third, a non-stationarity test was performed. The stationarity index and the Monte Carlo stationarity test demonstrate the non-stationarity of all the variables throughout the area. Finally, the influences of the degree of non-stationary of all controlling factors on mineralization are discussed. The existence of significant non-stationarity of mineral ore determinants in 3D space opens up an exciting avenue for research into the prediction of underground ore bodies.
Deepwater sediments are prone to loss circulation in drilling due to a low overburden gradient. How to predict the magnitude of leak-off pressure more accurately is an important issue in the protection of drilling safety and the reduction of drilling cost in deep water. Starting from the mechanical properties of a shallow formation and based on the basic theory of rock-soil mechanics, the stress distribution around a borehole was analyzed. It was found that the rock or soil on a borehole is in the plastic yield state before the effective tensile stress is generated, and the effective tangential and vertical stresses increase as the drilling fluid density increases; thus, tensile failure will not occur on the borehole wall. Based on the results of stress calculation, two mechanisms and leak-off pressure prediction models for shallow sediments in deepwater drilling were put forward, and the calculated values of these models were compared with the measured value of shallow leak-off pressure in actual drilling. The results show that the MHPS (minimum horizontal principle stress) model and the FIF (fracturing in formation) model can predict the lower and upper limits of leak-off pressure. The PLC (permeable lost circulation) model can comprehensively analyze the factors influencing permeable leakage and provide a theoretical basis for leak-off prevention and plugging in deepwater drilling. 相似文献
