Potential-field geophysical data inversion for 3D modelling and reserve estimation (Example of the Hajjar mine, Guemassa massif, Morocco): magnetic and gravity data case

IF 2 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY Comptes Rendus Geoscience Pub Date : 2020-11-04 DOI:10.5802/crgeos.10
Saâd Soulaimani, S. Chakiri, A. Manar, Ayoub Soulaimani, A. Miftah, M. Bouiflane
{"title":"Potential-field geophysical data inversion for 3D modelling and reserve estimation (Example of the Hajjar mine, Guemassa massif, Morocco): magnetic and gravity data case","authors":"Saâd Soulaimani, S. Chakiri, A. Manar, Ayoub Soulaimani, A. Miftah, M. Bouiflane","doi":"10.5802/crgeos.10","DOIUrl":null,"url":null,"abstract":"Geophysical data inversion is a tool, which can be used to recover the subsurface distribution of physical properties from field data. Each type of geophysical data can be inverted using one or more inversion algorithms. In this paper, a set of geophysical magnetic and gravity data of the Hajjar area in Morocco, covering an extent of 3.2× 1.6 km2, were used to make a 3D model of an orebody and to estimate the mineral reserve by potential-field geophysical data inversion and excess mass estimation. We thus promote the development and application of potential-field geophysical data inversion using the softwares Geosoft Oasis Montaj and Voxi Earth ModellingTM and the evaluation of its power compared to the excess mass estimation method. The process of inversion begins with data processing, then moves to analysis and interpretation, and ends with unconstrained Cartesian cut cell inversion. The results show a variation of −0.22 mGal to 1.59 mGal for the gravity residual anomaly map, leading to have density variations from 2.45 g/cm3 to 4.22 g/cm3, and a variation of −232 nT to 1018 nT for the reduced magnetic anomaly map. Moreover, data inversion allowed us to create a 3D model of the orebody and of the adjacent geological formation, and to estimate the different parameters that characterize the orebody derived from the inversion results, which have been confirmed from survey data: (depth ≈ 160 m; maximum ∗Corresponding author. ISSN (electronic) : 1778-7025 https://comptes-rendus.academie-sciences.fr/geoscience/ 140 Saâd Soulaimani et al. density ≈ 4.22 g/cm3; minimum density ≈ 3 g/cm3; mean density ≈ 3.61 g/cm3; thickness of the overburden ≈120 m; dip ≈ 45◦; morphology ≈ lens; volume ≈ 4.8×106 m3). It was therefore possible to evaluate the reserve, and to validate the reliability of the inversion by having a root mean square error between the exploited reserve and the calculated reserve of 13.5%, i.e. an insignificant difference between the real and calculated magnetic and gravity orebody responses, which support the validity of the results.","PeriodicalId":50651,"journal":{"name":"Comptes Rendus Geoscience","volume":"352 1","pages":"139-155"},"PeriodicalIF":2.0000,"publicationDate":"2020-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comptes Rendus Geoscience","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5802/crgeos.10","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 3

Abstract

Geophysical data inversion is a tool, which can be used to recover the subsurface distribution of physical properties from field data. Each type of geophysical data can be inverted using one or more inversion algorithms. In this paper, a set of geophysical magnetic and gravity data of the Hajjar area in Morocco, covering an extent of 3.2× 1.6 km2, were used to make a 3D model of an orebody and to estimate the mineral reserve by potential-field geophysical data inversion and excess mass estimation. We thus promote the development and application of potential-field geophysical data inversion using the softwares Geosoft Oasis Montaj and Voxi Earth ModellingTM and the evaluation of its power compared to the excess mass estimation method. The process of inversion begins with data processing, then moves to analysis and interpretation, and ends with unconstrained Cartesian cut cell inversion. The results show a variation of −0.22 mGal to 1.59 mGal for the gravity residual anomaly map, leading to have density variations from 2.45 g/cm3 to 4.22 g/cm3, and a variation of −232 nT to 1018 nT for the reduced magnetic anomaly map. Moreover, data inversion allowed us to create a 3D model of the orebody and of the adjacent geological formation, and to estimate the different parameters that characterize the orebody derived from the inversion results, which have been confirmed from survey data: (depth ≈ 160 m; maximum ∗Corresponding author. ISSN (electronic) : 1778-7025 https://comptes-rendus.academie-sciences.fr/geoscience/ 140 Saâd Soulaimani et al. density ≈ 4.22 g/cm3; minimum density ≈ 3 g/cm3; mean density ≈ 3.61 g/cm3; thickness of the overburden ≈120 m; dip ≈ 45◦; morphology ≈ lens; volume ≈ 4.8×106 m3). It was therefore possible to evaluate the reserve, and to validate the reliability of the inversion by having a root mean square error between the exploited reserve and the calculated reserve of 13.5%, i.e. an insignificant difference between the real and calculated magnetic and gravity orebody responses, which support the validity of the results.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
三维建模和储量估算的位场地球物理数据反演(以摩洛哥Guemassa地块Hajjar矿为例):磁重数据案例
地球物理数据反演是一种从野外数据中恢复地表物理性质分布的工具。每种类型的地球物理数据都可以使用一种或多种反演算法进行反演。本文利用摩洛哥哈贾尔地区一组3.2×1.6km2的地球物理磁、重数据,建立了矿体的三维模型,并通过势场地球物理数据反演和过剩质量估计来估计矿产储量。因此,我们推动了利用Geosoft Oasis Montaj和Voxi Earth ModellingTM软件进行势场地球物理数据反演的开发和应用,并与超质量估计方法进行了功率评估。反演过程从数据处理开始,然后进入分析和解释,最后以无约束笛卡尔剪切单元反演结束。结果显示,重力残余异常图的变化范围为-0.22 mGal至1.59 mGal,导致密度变化范围为2.45 g/cm3至4.22 g/cm3,而还原磁异常图的密度变化范围则为-232 nT至1018 nT。此外,数据反演使我们能够创建矿体和相邻地质构造的3D模型,并根据反演结果估计矿体的不同参数,这些参数已从调查数据中得到证实:(深度≈160 m;最大值*通讯作者。ISSN(电子版):1778-7025https://comptes-rendus.academie-sciences.fr/geoscience/140 Saâd Soulaimani等人,密度≈4.22 g/cm3;最小密度≈3 g/cm3;平均密度≈3.61g/cm3;覆盖层厚度≈120m;倾角≈45◦; 形态学≈晶状体;体积≈4.8×106 m3)。因此,可以评估储量,并通过开采储量和计算储量之间的均方根误差为13.5%来验证反演的可靠性,即实际和计算的磁性和重力矿体响应之间的微小差异,这支持了结果的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Comptes Rendus Geoscience
Comptes Rendus Geoscience 地学-地球科学综合
CiteScore
2.80
自引率
14.30%
发文量
68
审稿时长
5.9 weeks
期刊介绍: Created in 1835 by physicist François Arago, then Permanent Secretary, the journal Comptes Rendus de l''Académie des sciences allows researchers to quickly make their work known to the international scientific community. It is divided into seven titles covering the range of scientific research fields: Mathematics, Mechanics, Chemistry, Biology, Geoscience, Physics and Palevol. Each series is led by an editor-in-chief assisted by an editorial committee. Submitted articles are reviewed by two scientists with recognized competence in the field concerned. They can be notes, announcing significant new results, as well as review articles, allowing for a fine-tuning, or even proceedings of symposia and other thematic issues, under the direction of invited editors, French or foreign.
期刊最新文献
Lingual Actinomycosis Clinically Simulating Nodular Median Rhomboid Glossitis: Literature Review and Report of Additional Case. Pesticide upsurge, cross-contamination and biodiversity: case studies from the Caribbean Coast Human-Environment Observatory The rôle of Nuclear energy for fighting climate change: assets and weaknesses in a global perspective Climate change, an opportunity for humanity? Cities and climate change: buildings and urban land use
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1