The Experts below are selected from a list of 4068 Experts worldwide ranked by ideXlab platform
Campbell T Mccuaig - One of the best experts on this subject based on the ideXlab platform.
-
exploratory data analysis and c a fractal model applied in mapping multi element soil anomalies for drilling a case study from the sari gunay epithermal gold deposit nw iran
Journal of Geochemical Exploration, 2014Co-Authors: Hooshang H Asadi, Sadegh Kianpouryan, Campbell T MccuaigAbstract:Abstract This contribution investigates potential best practice in statistical treatment of Exploration Geochemistry data for drill target definition, using data from the Sari Gunay epithermal gold deposit, northwest Iran. Primarily, a robust factor analysis was applied to the soil geochemical data to identify anomalies related to outcropping and weak surface expression of hidden gold mineralizations. Investigation of outcropping mineralization indicates that the invisible gold mostly occurs in arsenian pyrite, accompanied by antimony and mercury sulfides. Therefore, a favorable principal factor with strong association of Au, As, Sb, Hg, Tl and S elements, related to epithermal mineralization, was selected for analysis. Then, the boxplot and median + 2MAD (median absolute deviation) techniques of the exploratory data analysis (EDA) and also concentration–area (C–A) fractal model were applied to the favorable factor loading to set the threshold values for defining multi-element soil geochemical anomalies for drilling. The median + 2MAD and C–A fractal models successfully identified the known outcropping gold mineralization at the Sari Gunay and Agh Dagh hills. In contrast, the boxplot method only identified the strong outcropping gold mineralization at the Sari Gunay hill, but failed to map the weaker mineralization at the Agh Dagh hill due to the usage of higher threshold values. In addition, the C–A fractal analysis identified a few second-class, weaker multi-element soil anomalies, mostly related to subsurface gold mineralization. The identified soil geochemical anomalies were compared with the in situ economic gold concentration in channel rock samples, mostly below the soil cover, and the outcropping host lithologies for validation. The results indicated the EDA approaches failed to map weak surface expression of gold mineralization and only mapped strong geochemical anomalies, useful only for reconnaissance drilling stages. The C–A fractal analysis is capable of mapping multi-class geochemical anomalies, some of which were associated with the weak surface expression of hidden gold mineralization, and is therefore useful in defining targets at both the reconnaissance and systematic drilling stages. The identified geochemical anomalies by C–A fractal analysis were also useful to characterize the favorable lithologies (e.g. quartz–tourmaline breccias, intrusive fragmental rocks including diatreme and dacite/trachyte porphyry) and hydrothermal alterations (e.g. quartz-sericite, K-feldspar and silicification) hosting gold mineralization at Sari Gunay.
-
Exploration targeting for orogenic gold deposits in the granites tanami orogen mineral system analysis targeting model and prospectivity analysis
Ore Geology Reviews, 2012Co-Authors: Aurore Joly, Alok Porwal, Campbell T MccuaigAbstract:Abstract A major challenge for mineral Exploration geologists is the development of a transparent and reproducible approach to targeting Exploration efforts, particularly at the regional to camp scales, in terranes under difficult cover where Exploration and opportunity costs are high. In this study, a three-pronged approach is used for identifying the most prospective ground for orogenic gold deposits in the Paleoproterozoic Granite-Tanami Orogen (GTO) in Western Australia. A key input to the analyses is the recent development of a 4D model of the GTO architectural evolution that provides new insights on the spatio-temporal controls over orogenic gold occurrences in the area; in particular, on the role of pre-mineralization (pre-1795 Ma) D GTOE –D GTO1 –D GTO2 architecture in localization of gold deposits and the spatial distribution of rock types in 3D. This information is used to build up a model of orogenic gold minerals system in the area, which is then integrated into the three mutually independent but complementary mineral prospectivity maps namely, a concept-driven “manual” and “fuzzy” analysis; and a data-driven “automated” analysis. The manual analysis involved: (1) generation of a process-based gold mineral systems template to aid target selection; (2) manual delineation of targets; (3) manual estimation of the probability of occurrence of each critical mineralization process based on the available information; and (4) combining the above probabilities to derive the relative probability of occurrence of orogenic gold deposits in each of the targets. The knowledge-based Geological Information System (GIS) analysis attempts to replicate the expert knowledge used in the manual approach, but queried in a more systematic format to eliminate human heuristic bias. This involves representing the critical mineralization processes in the form of spatial predictor maps and systematically querying them through the use of a fuzzy logic model to integrate the predictor maps and to derive the western GTO orogenic gold prospectivity map. The data-driven ‘empirical’ GIS analysis uses no expert knowledge. Instead it employs statistical measures to evaluate the spatial associations between known deposits and predictor maps to establish weights for each predictor layer then combines these layers into a predictive map using a Weights of Evidence (WofE) approach. Application of a mineral systems approach in the manual analysis and the fuzzy analysis is critical: potential high value targets identified by these approaches in the western GTO lie largely under cover, whereas traditional manual targeting is biased to areas of outcrop or sub-crop amenable to direct detection technology such as Exploration Geochemistry, and therefore towards areas that are data rich. The results show the power of combining the three approaches to prioritize areas for Exploration. While the manual analysis identifies and employs human intuition and can see through incomplete datasets, it is difficult to filter out human bias and to systematically apply to a large region. The fuzzy method is more systematic, and highlights areas that the manual analysis has undervalued, but lacks the intuitive power of the human mind that refines the target by seeing through incomplete datasets. The empirical WoE method highlights correlations with favorable host stratigraphy and highlights the control of an early set of structures potentially undervalued in the knowledge driven approaches, yet is biased due to the incomplete nature of Exploration datasets and lack of abundant gold deposits due to the extensive cover. The results indicate that the most prospective areas for orogenic gold in western GTO are located in the central part of the study area, largely in areas blind to previous Exploration efforts. According to our study, the procedure to follow should be to undertake the analyses in the following order: manual prospectivity analysis, followed by the conceptual fuzzy approach, followed by the empirical GIS-based method. Undertaking the manual analysis first is important to prevent Explorationists from being biased by the automated GIS-based outputs. It is however emphasized that all of the prospectivity outputs from these three methods are possible, and they should not be treated as ‘treasure maps’, but instead, as decision-support aids. Therefore, a final manual prospectivity analysis redefined by the mutual consideration of output from all of the methods is required. The strategy employed in this study constitutes a new template for best-practice in terrane- to camp-scale Exploration targeting that can be applied to different terranes and deposit types, particularly in terranes under cover, and provides a step forward in managing uncertainty in the Exploration targeting process.
C R M Butt - One of the best experts on this subject based on the ideXlab platform.
-
the development of regolith Exploration Geochemistry in the tropics and sub tropics
Ore Geology Reviews, 2016Co-Authors: C R M ButtAbstract:Abstract This essay traces the development of geochemical Exploration from its early beginnings in the modern era during the 1930s, concentrating especially in its application to deeply weathered terrain in the tropics and sub-tropics. Following promising results obtained in temperate regions in North America and Europe, test orientation surveys were conducted to see whether similar procedures were applicable in the tropics, where conventional geological prospecting was largely precluded due to the extensive cover of a deep lateritic regolith and consequent lack of outcrop. After initial work in Sierra Leone and Nigeria, the emphasis transferred to East Africa in the 1950s and 1960s, aimed principally at Cu Exploration. Many of the basic principles for Exploration in dominantly residual, free-draining terrain were quickly established in this period. Exploration in terrains with more complex weathering histories, however, raised a number of difficulties due to leaching and secondary concentrations of elements, problems in selecting and identifying appropriate sample media, and extensive transported overburden. These were encountered especially in more arid regions in Australia and Africa during Exploration for Ni and Au during the 1970s and 1980s. This led to a change in approach, placing weathering and geochemical dispersion in the context of regolith and landscape evolution –a return to the early concept of landscape Geochemistry. The 3D expression of mineralization in the landscape is depicted as empirical conceptual models, that account for both relict features and active processes, and portray element associations, dispersion mechanisms and host materials. They also indicate suitable sample media, sampling intervals and procedures for analysis and interpretation.
-
regolith Exploration Geochemistry in tropical and subtropical terrains
1992Co-Authors: C R M Butt, H ZeegersAbstract:Preface. List of Contributors. Introduction. I: Characteristics of Tropically Weathered Terrains. Climate, Geomorphological Environment and Geochemical Dispersion Models (C.R.M. Butt and H. Zeegers). Chemical Weathering (J.-J. Trescases). The Ferruginous Laterites (D. Nahon and Y. Tardy). Soil Formation in Tropicallly Weathered Terrains (Y. Lucas and M. Chauvel). The Chemical Mobility and Transport of Elements in the Weathering Environment (M.R. Thornber). Physical Weathering and Dispersion (C.R.M. Butt). II: Gossan Formation and Gossan Surveys. The Mechanisms of Sulphide Oxidation and Gossan Formation (M.R. Thornber and G.F. Taylor). Gossan and Ironstone Surveys (G.F. Taylor and M.R. Thornber). III: Exploration in Areas of Low to Moderate Relief. Seasonally Humid Tropical Terrains ( Savannas ) (H. Zeegers and P. Lecomte). Humid Tropical Terrains ( Rainforests ) (P. Lecomte and H. Zeegers). Semi-Arid and Arid Terrains (C.R.M. Butt). IV: Exploration in Areas of Moderate to High Relief. Dissected Terrains and Tropical Mountains (C.R.M. Butt and H. Zeegers). V: Specific Commodities and Techniques. Diamond Exploration in Tropical Terrains (G.P. Gregory and A.J.A. Janse). Uranium Exploration in Tropical Terrains (F. Bianconi and K. Kogler). The Geochemistry of Gold in Lateritic Terrains (D.J. Gray, C.R.M. Butt and L.M. Lawrance). Heavy Mineral Surveys in Exploration of Lateritic Terrain (G. Friedrich, A. Marker and M. Kanig). VI: Synthesis and Conclusions. Summary and Procedural Recommendations. (H. Zeegers and C.R.M. Butt). Appendix 1: Sample Media used in Geochemical Exploration in Tropically Weathered Environments: Definitions and Use. Appendix 2: Sample Preparation and Analysis. Appendix 3: Profile Nomenclature and Glossary. Author Index. Place Index. Subject Index.
Alastair J Sinclair - One of the best experts on this subject based on the ideXlab platform.
-
a fundamental approach to threshold estimation in Exploration Geochemistry probability plots revisited
Journal of Geochemical Exploration, 1991Co-Authors: Alastair J SinclairAbstract:Abstract Several threshold estimation (and thus anomaly recognition) procedures are in use of Exploration Geochemistry. Experiential methods rely on absolute values in graphs or tables and are highly subjective in being dependent of the variable experience of Explorationists. Model-based subjective techniques of threshold determination, including the mean plus two standard deviations, are arbitrary and inefficient: thus, they are not suitalbe despite the widespread use they have found in the past. Model-based objective methods include the gap statistic and the probability graph approaches, the latter finding much greater acceptance with the greatly increased ease of a recently available microcomputer software package that can treat many variables easily and rapidly. Many critical decisions in Exploration Geochemistry require a comprehensive interpretation of available data, including clear insight into the recognition of anomalous and background samples. Several decisions cannot be made in a vigorous and confident manner unless based on a fundamental approach to threshold selection. Examples include: (1) element zoning in Geochemistry: (2) absolute estimation of geochemical contrast: (3) the recognition of the isotropic or anisotropic nature of anomalies: and (4) an estimation of areal extent of anomalies of various elements. Methods of threshold estimation which incorporate the philosophy that anomalous and background data are each characterized by their own probability density functions will be most successful in deriving a fundamental approach to threshold estimation. In the simplest general case, there are two overlapping populations, the overlapping character leading naturally to the extension of the single threshold concept to the definition of two thresholds that delimit the range of overlap. Such a concept, easily conceived and applied to individual variables, can be extended to the n-dimensional case. Univariate approaches will continue to dominate practical applications in the foreseeable future except in special circumstances.
Qiuming Cheng - One of the best experts on this subject based on the ideXlab platform.
-
application of singularity mapping technique to identify local anomalies using stream sediment geochemical data a case study from gangdese tibet western china
Journal of Geochemical Exploration, 2009Co-Authors: Renguang Zuo, Qiuming Cheng, F P Agterberg, Qinglin XiaAbstract:Abstract Identifying geochemical anomalies from background is a fundamental task in Exploration Geochemistry. The Gangdese mineral district in western China has complex geochemical surface expression due to complex geological background and was chosen as a study area for recognition of the spatial distribution of geochemical elements and separating anomalies from background using stream sediment geochemical data. The results illustrate that weak anomalies are hidden within the strong variance of background and are not well identified by means of inverse distance weighted; neither are they clearly identified by the C–A method if this method is applied to the whole study area. On the other hand, singularity values provide new information that complements use of original concentration values and can quantify the properties of enrichment and depletion caused by mineralization. In general, producing maps of singularities can help to identify relatively weak metal concentration anomalies in complex geological regions. Application of singularity mapping technique in Gangdese district shows local anomalies of Cu are not only directly associated with known deposits in the central part of the study area, but also with E–W and N–E oriented faults in the north of the study area. Both types of anomalies should be further investigated for undiscovered Cu mineral deposits.
-
a spatial analysis method for geochemical anomaly separation
Journal of Geochemical Exploration, 1996Co-Authors: Qiuming Cheng, F P Agterberg, Graeme F BonhamcarterAbstract:Abstract 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.
Alok Porwal - One of the best experts on this subject based on the ideXlab platform.
-
Exploration targeting for orogenic gold deposits in the granites tanami orogen mineral system analysis targeting model and prospectivity analysis
Ore Geology Reviews, 2012Co-Authors: Aurore Joly, Alok Porwal, Campbell T MccuaigAbstract:Abstract A major challenge for mineral Exploration geologists is the development of a transparent and reproducible approach to targeting Exploration efforts, particularly at the regional to camp scales, in terranes under difficult cover where Exploration and opportunity costs are high. In this study, a three-pronged approach is used for identifying the most prospective ground for orogenic gold deposits in the Paleoproterozoic Granite-Tanami Orogen (GTO) in Western Australia. A key input to the analyses is the recent development of a 4D model of the GTO architectural evolution that provides new insights on the spatio-temporal controls over orogenic gold occurrences in the area; in particular, on the role of pre-mineralization (pre-1795 Ma) D GTOE –D GTO1 –D GTO2 architecture in localization of gold deposits and the spatial distribution of rock types in 3D. This information is used to build up a model of orogenic gold minerals system in the area, which is then integrated into the three mutually independent but complementary mineral prospectivity maps namely, a concept-driven “manual” and “fuzzy” analysis; and a data-driven “automated” analysis. The manual analysis involved: (1) generation of a process-based gold mineral systems template to aid target selection; (2) manual delineation of targets; (3) manual estimation of the probability of occurrence of each critical mineralization process based on the available information; and (4) combining the above probabilities to derive the relative probability of occurrence of orogenic gold deposits in each of the targets. The knowledge-based Geological Information System (GIS) analysis attempts to replicate the expert knowledge used in the manual approach, but queried in a more systematic format to eliminate human heuristic bias. This involves representing the critical mineralization processes in the form of spatial predictor maps and systematically querying them through the use of a fuzzy logic model to integrate the predictor maps and to derive the western GTO orogenic gold prospectivity map. The data-driven ‘empirical’ GIS analysis uses no expert knowledge. Instead it employs statistical measures to evaluate the spatial associations between known deposits and predictor maps to establish weights for each predictor layer then combines these layers into a predictive map using a Weights of Evidence (WofE) approach. Application of a mineral systems approach in the manual analysis and the fuzzy analysis is critical: potential high value targets identified by these approaches in the western GTO lie largely under cover, whereas traditional manual targeting is biased to areas of outcrop or sub-crop amenable to direct detection technology such as Exploration Geochemistry, and therefore towards areas that are data rich. The results show the power of combining the three approaches to prioritize areas for Exploration. While the manual analysis identifies and employs human intuition and can see through incomplete datasets, it is difficult to filter out human bias and to systematically apply to a large region. The fuzzy method is more systematic, and highlights areas that the manual analysis has undervalued, but lacks the intuitive power of the human mind that refines the target by seeing through incomplete datasets. The empirical WoE method highlights correlations with favorable host stratigraphy and highlights the control of an early set of structures potentially undervalued in the knowledge driven approaches, yet is biased due to the incomplete nature of Exploration datasets and lack of abundant gold deposits due to the extensive cover. The results indicate that the most prospective areas for orogenic gold in western GTO are located in the central part of the study area, largely in areas blind to previous Exploration efforts. According to our study, the procedure to follow should be to undertake the analyses in the following order: manual prospectivity analysis, followed by the conceptual fuzzy approach, followed by the empirical GIS-based method. Undertaking the manual analysis first is important to prevent Explorationists from being biased by the automated GIS-based outputs. It is however emphasized that all of the prospectivity outputs from these three methods are possible, and they should not be treated as ‘treasure maps’, but instead, as decision-support aids. Therefore, a final manual prospectivity analysis redefined by the mutual consideration of output from all of the methods is required. The strategy employed in this study constitutes a new template for best-practice in terrane- to camp-scale Exploration targeting that can be applied to different terranes and deposit types, particularly in terranes under cover, and provides a step forward in managing uncertainty in the Exploration targeting process.
