地震剖面线条化的一种简单算法

地震剖面线条化是应用模式识别方法自动追踪剖面中的同相轴, 并自动绘制线条图.首先探测地震道中的周波, 并描述周波属性, 然后根据相邻三道周波相关的目标函数最小原则追踪同相轴, 描述同相轴属性, 并记录同相轴属性表.根据同相轴属性表, 可对地震剖面进行基于同相轴属性的统计分析和滤波以及定量解释.本文对现有的地震剖面线条化方法进行了改进简化, 实现地震剖面同相轴快速自动追踪和自动绘制线条图.合成数据和实际数据试验表明该方法计算简单、快速、有效.      

A New Algorithm for Borehole Electromagnetic Measurements Employing Lambert W Function

The Lambert W function is defined to be the multivalued inverse of the function w we ^w . It has been widely used in many fields. In this paper, we developed an accurate algorithm for calculating apparent formation conductivity and dielectric constant from electromagnetic logs by making use of Lambert W function. Transforming the complicated nonlinear system into a linear system of much simpler format, this new algorithm can achieve a much higher accuracy of data processing and provide physically meaningful results over the full frequency band of electromagnetic logs. In the frequency band of induction logs (<20 MHz) this algorithm eliminates the complicated procedure for correcting for the skin effects. It also removes the conventional limitation of for induction logs, and therefore, makes accuracy of induction log measurements no longer dependent on the true formation conductivity. In the frequency band of 20–100 MHz, this method can obtain accurate formation conductivities and dielectric constant simultaneously. Theoretical analysis, numerical modeling, and field data processing cases of Oklahoma formation demonstrate the advantages of this new method over traditional methods. The algorithm for this method is easy to implement and it can be used with electronic hardware to produce accurate formation conductivity and dielectric logs directly.     

A spatial analysis method for geochemical anomaly separation

One purpose of using statistical methods in exploration geochemistry is to assist exploration geologists in separating anomalies from background. This always involves two types of negatively associated errors of misclassification: type I errors occur when samples with background levels are rejected as background; and type II errors occur when samples with anomalous values are accepted as background. A new spatial statistical approach is proposed to minimize errors of total misclassification using a moving average technique with variable window radius. This method has been applied for geochemical anomaly enhancement and recognition as demonstrated by a case study of Au and Au-associated data for 698 stream sediment samples in the Iskut River area, northwestern British Columbia. Similar results were obtained using the fractal concentration-area method on the same data. By employing spatial information in the analysis, the process of selecting anomalies becomes less subjective than in more traditional approaches.     

Exploratory Data Analysis Applied in Mapping Multi-element Soil Geochemical Anomalies for Drill Target Definition: A Case Study from the Unpha Layered Non-magmatic Hydrothermal Pb-Zn Deposit,DPR Korea

A factor analysis was applied to soil geochemical data to define anomalies related to buried Pb-Zn mineralization. A favorable main factor with a strong association of the elements Zn, Cu and Pb, related to mineralization, was selected for interpretation. The median + 2MAD (median absolute deviation) method of exploratory data analysis (EDA) and C-A (concentration-area) fractal modeling were then applied to the Mahalanobis distance, as defined by Zn, Cu and Pb from the factor analysis to set the thresholds for defining multi-element anomalies. As a result, the median + 2MAD method more successfully identified the Pb-Zn mineralization than the C-A fractal model. The soil anomaly identified by the median + 2MAD method on the Mahalanobis distances defined by three principal elements (Zn, Cu and Pb) rather than thirteen elements (Co, Zn, Cu, V, Mo, Ni, Cr, Mn, Pb, Ba, Sr, Zr and Ti) was the more favorable reflection of the ore body. The identified soil geochemical anomalies were compared with the in situ economic Pb-Zn ore bodies for validation. The results showed that the median + 2MAD approach is capable of mapping both strong and weak geochemical anomalies related to buried Pb-Zn mineralization, which is therefore useful at the reconnaissance drilling stage.     

An Assessment of Performance in the Routine Analysis of Silicate Rocks Based on an Analysis of Data Submitted to the GeoPT Proficiency Testing Programme for Geochemical Laboratories (2001–2011)

Data reported by laboratories contributing to the GeoPT proficiency testing programme for geochemical laboratories over the period from 2001 to 2011 have been assessed to identify the elements and concentration ranges over which analytical performance can be considered satisfactory. Criteria developed in the paper indicated that performance in the content determination of the elements/constituents SiO₂, Al₂O₃, MnO, Cs, Dy, Er, Eu, Ga, Hf, Ho, Lu, Nd, Pr, Sm, Sr, Tb, Tl, Tm, U, Y, Yb and Zn was satisfactory over the full concentration range assessed. The elements/constituents TiO₂, Fe₂O₃(T), MgO, CaO, Na₂O, K₂O, P₂O₅, Ba, Be, Cd, Ce, Co, Gd, La, Li, Nb, Rb, Sb, Sc, Sn, Ta, Th, V and Zr showed some degradation in performance at lower concentration levels (approaching the detection limit of some techniques). Performance in determining LOI, As, Bi, Cr, Cu, Ge, Mo, Ni, Pb and W was in general unsatisfactory over the full concentration range assessed. Other elements (especially Fe(II)O, H₂O⁺, CO₂, Ag, Au, B, Br, Cl, F, Hg, I, In, Ir, N, Os, Pd, Pt, Re, Rh, S, Se, Te) could not be evaluated as they were not routinely reported by laboratories participating in the GeoPT programme, often because they are present in silicate rocks at sufficiently low concentrations to require a pre‐concentration stage. Some suggestions are made for the causes of unsatisfactory performance, but further progress will require a detailed assessment of the methods used by participating laboratories, which will form the subject of a further paper.