F. O. Ogunsanwo, V. C. Ozebo, O. T. Olurin, J. D. Ayanda, J. M. Olumoyegun, A. D. Adelaja, K. A. Egunjobi, S. A. Ganiyu, O. A. Oyebanjo, J. A. Olowofela
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The objectives of this work are to (i) fit the aeromagnetic data into the variogram model to estimate the magnetic spatial structural dependency on the geological composition (ii) delineate the spatial magnetic anomaly associated with the lithological units using kriging interpolation techniques (iii) deduce the zone associated with strong and weak gold mineralization (iv) evaluate the kriging techniques for cross validation. The major tool used in this work is the geological map of Ilesha which was partitioned into nine (9) lithological H-units in conjunction with an aeromagnetic sheet obtained from the Nigeria Geophysical Survey Agency, Abuja. In this study, three variogram models, the spherical (S), exponential (E) and Gaussian (G) models, were used. Three kriging interpolation techniques, ordinary kriging (OK), co-kriging (CK) and radial basis function (RBF) were employed. Nugget Sill Ratio (NSR) was deduced to estimate the autocorrelation level of the variogram models while cross validation was carried out on the kriging techniques using mean square error (MSE) and root mean square error (RMSE) for predictive performance evaluation. The result obtained accounted for the variogram model in the order of S < E < G for six (6) lithological H-units. Two units (H3 and H4) were found in the order of E < S < G while one unit, H5 is in the order of S < G < E. The NSR result revealed two distinct levels, namely; a strong and moderate level. Six H- units fall under the strong autocorrelation dependency in the range of 6.78–20.79%, while three H-units have moderate autocorrelation dependency within the range of 26.07–58.91%. The kriging results accounted for three distinct magnetic anomalies; low, moderate, and intense, across the nine lithological H- units. The gold strong mineralization zone are attributed to hydrothermal alteration in the region with low to moderate magnetic field intensity in the range < − 100 nT to 50 nT. The interpolation performance evaluation revealed CK to have the lowest MSE and RMSE value when compared to OK and RBF. The three kriging techniques adopted are good linear predictive estimator but CK gives a better predictive accuracy and have less perturbation. In this study, the application of the geostatistical methods (variogram and kriging) to the analysis of Ilesha aeromagnetic data has led to the conclusion that these techniques are effective mathematical tools for delineating the structural and spatial dependency of magnetic anomalies which have a great attribute in mineral exploration.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"83 23","pages":""},"PeriodicalIF":2.8000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Geostatistical analysis and interpretation of Ilesha aeromagnetic data south–western, Nigeria\",\"authors\":\"F. O. Ogunsanwo, V. C. Ozebo, O. T. Olurin, J. D. Ayanda, J. M. Olumoyegun, A. D. Adelaja, K. A. Egunjobi, S. A. Ganiyu, O. A. Oyebanjo, J. A. 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The objectives of this work are to (i) fit the aeromagnetic data into the variogram model to estimate the magnetic spatial structural dependency on the geological composition (ii) delineate the spatial magnetic anomaly associated with the lithological units using kriging interpolation techniques (iii) deduce the zone associated with strong and weak gold mineralization (iv) evaluate the kriging techniques for cross validation. The major tool used in this work is the geological map of Ilesha which was partitioned into nine (9) lithological H-units in conjunction with an aeromagnetic sheet obtained from the Nigeria Geophysical Survey Agency, Abuja. In this study, three variogram models, the spherical (S), exponential (E) and Gaussian (G) models, were used. Three kriging interpolation techniques, ordinary kriging (OK), co-kriging (CK) and radial basis function (RBF) were employed. Nugget Sill Ratio (NSR) was deduced to estimate the autocorrelation level of the variogram models while cross validation was carried out on the kriging techniques using mean square error (MSE) and root mean square error (RMSE) for predictive performance evaluation. The result obtained accounted for the variogram model in the order of S < E < G for six (6) lithological H-units. Two units (H3 and H4) were found in the order of E < S < G while one unit, H5 is in the order of S < G < E. The NSR result revealed two distinct levels, namely; a strong and moderate level. Six H- units fall under the strong autocorrelation dependency in the range of 6.78–20.79%, while three H-units have moderate autocorrelation dependency within the range of 26.07–58.91%. The kriging results accounted for three distinct magnetic anomalies; low, moderate, and intense, across the nine lithological H- units. 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引用次数: 0
摘要
变分法和克里金法作为地质统计分析的一种工具,最近在各种科学领域,特别是在矿产勘探方面的应用日益突出。研究区域伊莱沙已被确定为尼日利亚黄金矿藏丰富的地区之一。过去曾使用过不同的方法来分析和解释该金矿地区的航磁数据,但较少关注地质统计方法。这项工作的目标是:(i) 将航磁数据拟合到变异图模型中,以估算磁性空间结构与地质组成的关系;(ii) 利用克里金插值技术划定与岩性单元相关的空间磁异常;(iii) 推断与强弱金矿化相关的区域;(iv) 评估克里金技术的交叉验证。这项工作中使用的主要工具是伊莱沙地质图,该地质图被划分为九(9)个岩性 H 单元,同时还使用了从阿布贾尼日利亚地球物理勘测局获得的航磁图。本研究使用了三种变异图模型,即球形模型(S)、指数模型(E)和高斯模型(G)。采用了三种克里金插值技术,即普通克里金(OK)、协同克里金(CK)和径向基函数(RBF)。推导出了 Nugget Sill Ratio (NSR),以估计变异图模型的自相关水平,同时使用均方误差 (MSE) 和均方根误差 (RMSE) 对克里金技术进行了交叉验证,以评估预测性能。结果表明,六(6)个岩性 H 单位的变异图模型顺序为 S < E < G。两个单元(H3 和 H4)的顺序为 E < S < G,而一个单元 H5 的顺序为 S < G < E。NSR 结果显示了两个不同的水平,即强水平和中等水平。六个 H 单位属于强自相关依赖,范围在 6.78-20.79% 之间,而三个 H 单位属于中度自相关依赖,范围在 26.07-58.91% 之间。克里格法结果表明,在九个岩性 H- 单元中存在三种不同的磁异常:低度、中度和高度。金的强矿化带归因于该区域的热液蚀变,磁场强度在 < - 100 nT 到 50 nT 之间。插值性能评估显示,与 OK 和 RBF 相比,CK 的 MSE 和 RMSE 值最低。所采用的三种克里金技术都是良好的线性预测估算器,但 CK 的预测精度更高,扰动更小。在这项研究中,应用地质统计方法(变异图和克里金法)分析伊勒沙航空磁数据得出的结论是,这些技术是划分磁异常的结构和空间依赖性的有效数学工具,在矿产勘探中具有重要作用。
Geostatistical analysis and interpretation of Ilesha aeromagnetic data south–western, Nigeria
The uses of variogam and kriging as a tool in geostatistical analysis have gained greater prominence recently in the diverse scientific field, especially for mineral exploration purpose. Ilesha, the study area, has been identified as the one the region with abundance gold deposits in Nigeria. Different methods have been used in the past for the analysis and interpretation of aeromagnetic data in the gold deposit area with less attention to the geostatistical approach. The objectives of this work are to (i) fit the aeromagnetic data into the variogram model to estimate the magnetic spatial structural dependency on the geological composition (ii) delineate the spatial magnetic anomaly associated with the lithological units using kriging interpolation techniques (iii) deduce the zone associated with strong and weak gold mineralization (iv) evaluate the kriging techniques for cross validation. The major tool used in this work is the geological map of Ilesha which was partitioned into nine (9) lithological H-units in conjunction with an aeromagnetic sheet obtained from the Nigeria Geophysical Survey Agency, Abuja. In this study, three variogram models, the spherical (S), exponential (E) and Gaussian (G) models, were used. Three kriging interpolation techniques, ordinary kriging (OK), co-kriging (CK) and radial basis function (RBF) were employed. Nugget Sill Ratio (NSR) was deduced to estimate the autocorrelation level of the variogram models while cross validation was carried out on the kriging techniques using mean square error (MSE) and root mean square error (RMSE) for predictive performance evaluation. The result obtained accounted for the variogram model in the order of S < E < G for six (6) lithological H-units. Two units (H3 and H4) were found in the order of E < S < G while one unit, H5 is in the order of S < G < E. The NSR result revealed two distinct levels, namely; a strong and moderate level. Six H- units fall under the strong autocorrelation dependency in the range of 6.78–20.79%, while three H-units have moderate autocorrelation dependency within the range of 26.07–58.91%. The kriging results accounted for three distinct magnetic anomalies; low, moderate, and intense, across the nine lithological H- units. The gold strong mineralization zone are attributed to hydrothermal alteration in the region with low to moderate magnetic field intensity in the range < − 100 nT to 50 nT. The interpolation performance evaluation revealed CK to have the lowest MSE and RMSE value when compared to OK and RBF. The three kriging techniques adopted are good linear predictive estimator but CK gives a better predictive accuracy and have less perturbation. In this study, the application of the geostatistical methods (variogram and kriging) to the analysis of Ilesha aeromagnetic data has led to the conclusion that these techniques are effective mathematical tools for delineating the structural and spatial dependency of magnetic anomalies which have a great attribute in mineral exploration.
期刊介绍:
Environmental Earth Sciences is an international multidisciplinary journal concerned with all aspects of interaction between humans, natural resources, ecosystems, special climates or unique geographic zones, and the earth:
Water and soil contamination caused by waste management and disposal practices
Environmental problems associated with transportation by land, air, or water
Geological processes that may impact biosystems or humans
Man-made or naturally occurring geological or hydrological hazards
Environmental problems associated with the recovery of materials from the earth
Environmental problems caused by extraction of minerals, coal, and ores, as well as oil and gas, water and alternative energy sources
Environmental impacts of exploration and recultivation – Environmental impacts of hazardous materials
Management of environmental data and information in data banks and information systems
Dissemination of knowledge on techniques, methods, approaches and experiences to improve and remediate the environment
In pursuit of these topics, the geoscientific disciplines are invited to contribute their knowledge and experience. Major disciplines include: hydrogeology, hydrochemistry, geochemistry, geophysics, engineering geology, remediation science, natural resources management, environmental climatology and biota, environmental geography, soil science and geomicrobiology.