Magnetic and Gravity Surface Geometry Inverse Modeling of the TAG Active Mound

Galley, Christopher; Lelièvre, Peter G.; Haroon, Amir; Graber, S. David; Jamieson, John; Szitkar, Florent; Yeo, Isobel; Farquharson, Colin G.; Petersen, Sven; Evans, Robert

doi:10.1029/2021jb022228

Cited by 18 publications

(17 citation statements)

References 55 publications

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“…(c) Extrapolated CSEM conductance derived from random forest regression and the corresponding prediction variability assuming 5% Gaussian error. The black markers denote the actual profiles of the CSEM conductance data distributed geophysical, geochemical, geomorphological, oceanographic or geological data; (b) update first-order predictions of available strategic metals on the seafloor through guided geophysical interpretations (Galley et al 2021).…”

Section: Using Machine Learning For Automated Site Detection Of Massi...mentioning

confidence: 99%

The Digital Earth Smart Monitoring Concept and Tools

Ködel

Dietrich

Fischer

et al. 2022

Integrating Data Science and Earth Science

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Reliable data are the base of all scientific analyses, interpretations and conclusions. Evaluating data in a smart way speeds up the process of interpretation and conclusion and highlights where, when and how additionally acquired data in the field will support knowledge gain. An extended SMART monitoring concept is introduced which includes SMART sensors, DataFlows, MetaData and Sampling approaches and tools. In the course of the Digital Earth project, the meaning of SMART monitoring has significantly evolved. It stands for a combination of hard- and software tools enhancing the traditional monitoring approach where a SMART monitoring DataFlow is processed and analyzed sequentially on the way from the sensor to a repository into an integrated analysis approach. The measured values itself, its metadata, and the status of the sensor, and additional auxiliary data can be made available in real time and analyzed to enhance the sensor output concerning accuracy and precision. Although several parts of the four tools are known, technically feasible and sometimes applied in Earth science studies, there is a large discrepancy between knowledge and our derived ambitions and what is feasible and commonly done in the reality and in the field.

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Section: Using Machine Learning For Automated Site Detection Of Massi...mentioning

confidence: 99%

The Digital Earth Smart Monitoring Concept and Tools

Ködel

Dietrich

Fischer

et al. 2022

Integrating Data Science and Earth Science

View full text Add to dashboard Cite

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“…(2020) and Galley et al. (2021). The black dashed rectangle represents the TAG active hydrothermal mound.…”

Section: Introductionmentioning

confidence: 97%

“…In the last decades, galvanometric and electromagnetic methods have been used for the exploration and assessment of SMS resources. These methods include the controlled source electromagnetic (CSEM) method, the direct current (DC) resistivity imaging method, the transient electromagnetic (TEM) method, and the passive self‐potential (SP) method (see case studies in Cairns et al., 1996; Constable et al., 2018; Galley et al., 2021; Gehrmann et al., 2019; Haroon et al., 2018; Ishizu et al., 2019; Kawada & Kasaya, 2018; Müller et al., 2018; Su, Tao, Shen et al., 2022; Szitkar et al., 2021; Zhu et al., 2020). However, ore bodies and metallic deposits are not always characterized by conductivity contrasts (Mao & Revil, 2016; Mao et al., 2016).…”

Section: Introductionmentioning

confidence: 99%

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Joint Interpretation of Marine Self‐Potential and Transient Electromagnetic Survey for Seafloor Massive Sulfide (SMS) Deposits: Application at TAG Hydrothermal Mound, Mid‐Atlantic Ridge

Tao

Zhu

et al. 2022

JGR Solid Earth

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The self-potential (SP) method is expected to play an important role in the exploration of seafloor massive sulfide (SMS) resources. Since the redox potential changes with depth below the seafloor, SMS deposits are the source of an electrical (source) current density, generating in turn a recordable electrical field. This electrical field can be remotely measured at and above the seafloor. By integrating this electrical field, we obtained a so-called SP profile or map. The electrical conductivity distribution of SMS deposits is an important ingredient in the inversion of these SP data in order to distinguish between causative primary sources (i.e., associated with the SMS deposits themselves) and secondary current sources associated with conductivity contrasts below the seafloor. Such ingredient is therefore necessary to properly localize SMS deposits and eliminating ghosts associated with high conductivity contrasts. The conductivity structure of the seafloor is however unknown in most SP surveys. This study presents the first joint interpretation of transient electromagnetic and SP surveys. The field data were acquired at the Trans-Atlantic Geotraverse (TAG) hydrothermal mound. The conductivity structure of TAG mound was obtained by inverting transient electromagnetic data. This electrical conductivity distribution is then used to invert the SP data. The obtained (primary) source current distribution delineates the geometry of the SMS deposits. The deposits are located in the center of the mound as well as at its edges, in a way that is consistent with water column data. Combining the two geophysical methods improves our ability to better decipher the fine geometry of SMS deposits below the seafloor.Plain Language Summary Seafloor massive sulfide (SMS) deposits contain abundant amounts of Cu, Zn, Au, and Ag, which are of growing economic interest for our civilization. In recent years, the exploration of SMS deposits has entered into a new era with the goal of better assess and characterize these resources. In this perspective, geophysical methods are in high demand to localize SMS deposits and obtain their three-dimensional geometry. The self-potential (SP) method provides an efficient non-intrusive and cost-effective approach to image SMS deposits. Previous surveys have documented the existence of recordable negative SP anomalies above the seafloor in association with SMS deposits. SP tomography can be used to assess the 3D geometry of SMS deposits. That said, the conductivity pattern below the seafloor is unknown in previous SP surveys while it is an important ingredient in the inversion of the SP data. Active source measurements like the transient electromagnetic (TEM) method can be used to obtain the electrical conductivity distribution below the seafloor. So, we propose to combine SP and TEM data to improve our ability to image SMS deposits. We apply the new methodology to a famous submarine hydrothermal field located in the Atlantic mid-oceanic ridge Trans-Atlantic Geotraverse and investigated in the past...

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“…However, detailed magnetomineralogy and magnetic property variations among different hydrothermal products in TAG were not established by Zhao et al (1998). Consequently, although the low concentration of magnetic minerals within the stockwork explains the reduced crustal magnetization in the TAG active mound (e.g., Gehrmann et al, 2019;Tivey et al, 1993), utilizing magnetic surveying data for sophisticated subsurface stockwork geometry inversion and tonnage estimation of SMS deposits remain challenging (e.g., Galley et al, 2021;Szitkar et al, 2021).…”

mentioning

confidence: 99%

Rock Magnetic Signatures of Hydrothermal Mineralization in the Trans‐Atlantic Geotraverse (TAG) Hydrothermal Field

Wang

Chang

2022

Geochem Geophys Geosyst

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The Ocean Drilling Program Leg 158 drill holes from the Trans‐Atlantic Geotraverse hydrothermal field are investigated to understand the rock magnetic signatures of hydrothermal mineralization. A composite columnar section has been constructed through hole correlation to understand the stratigraphic variation of magnetomineralogy within the stockwork. Isothermal remanent magnetization components unmixing, first‐order reversal curve diagrams, low‐temperature magnetic signatures, and electron microscopic analyses disclose magnetic minerals of disparate occurrences related to predominating hydrothermal mineralization reactions in three broad zones: For basaltic basements, serpentinization of olivine phenocrysts during preliminary hydrothermal alteration produces magnetite, in addition to primary titanomagnetite; Chloritized and silicified zone samples contain relict titanomagnetite and exsolved magnetite that survived hydrothermal dissolution; Anhydrite and sulfide zone samples are dominated by magnetite and hematite, likely from oxidation of polymetallic sulfides due to exposure in oxidative seafloor environments during drilling. Our findings suggest that seafloor oxidation potentially modifies the magnetic properties of polymetallic sulfides in hydrothermal deposits, which applies to magnetic tomography of sophisticated subseafloor vent structures and prospecting seafloor massive sulfides (SMS) deposits therein. Meanwhile, we alert future deep‐sea mining that drilling may promote physicochemical alteration of SMS deposits, causing environmental risks. The established magnetic signatures ultimately contribute to understanding the in situ geological preservation of SMS deposits and optimizing exploitation procedures in the future.

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Magnetic and Gravity Surface Geometry Inverse Modeling of the TAG Active Mound

Cited by 18 publications

References 55 publications

The Digital Earth Smart Monitoring Concept and Tools

The Digital Earth Smart Monitoring Concept and Tools

Joint Interpretation of Marine Self‐Potential and Transient Electromagnetic Survey for Seafloor Massive Sulfide (SMS) Deposits: Application at TAG Hydrothermal Mound, Mid‐Atlantic Ridge

Rock Magnetic Signatures of Hydrothermal Mineralization in the Trans‐Atlantic Geotraverse (TAG) Hydrothermal Field

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