Bayesian inversion of magnetic data: A case study of Australia 

2021 ◽  
Author(s):  
Yixiati Dilixiati ◽  
Wolfgang Szwillus ◽  
Jörg Ebbing
Keyword(s):  
Heat Flow ◽  
Magnetic Layer ◽  
Rock Properties ◽  
Magnetic Data ◽  
Dipole Source ◽  
Bayesian Inversion ◽  
Crustal Rock ◽  
Geothermal Heat ◽  
Magnetic Model ◽  
Set Up

<p>We apply a Bayesian inversion based on the Monte Carlo Markov chain sampling scheme to magnetic anomaly data of Australia. In our inversion, we simultaneously solve for the susceptibility distribution and the thickness of the magnetic layer. Due to the excellent data coverage, we test our method for Australia. As data source, we use aeromagnetic data of Australia, which are conformed to the recent satellite magnetic model, LCS-1, by an equivalent dipole source approach combined with a spherical harmonic representation. The data are presented in different heights in order to minimize local scale features and to maximize sensitivity to the thickness of the magnetic layer. As constraint, we use estimates of the magnetic layer based on measurements of geothermal heat flow and crustal rock properties. Hereby, we assume that the Curie isotherm does coincide with the deepest magnetic layer. We systematically explore, the effect of increasing model resolution and of the geothermal heat flow values considering their accuracy and quality. The set-up will in the next step be applied to other continental areas of the Earth.</p>

Implications for the lithospheric structure of Greenland by applying different heat flow models

2021 ◽  
Author(s):  
Agnes Wansing ◽  
Jörg Ebbing ◽  
Mareen Lösing ◽  
Sergei Lebedev ◽  
Nicolas Celli ◽  
...  
Keyword(s):  
Heat Flow ◽  
Heat Dissipation ◽  
Ice Sheet ◽  
Magnetic Data ◽  
Similarity Function ◽  
Lithospheric Structure ◽  
Temperature Structure ◽  
Geothermal Heat ◽  
Flow Models ◽  
Ice Sheet Dynamics

<p>The lithospheric structure of Greenland is still poorly known due to its thick ice sheet, the sparseness of seismological stations, and the limitation of geological outcrops near coastal areas. As only a few geothermal measurements are available for Greenland, one must rely on geophysical models. Such models of Moho and LAB depths and sub-ice geothermal heat-flow vary largely.</p><p>Our approach is to model the lithospheric architecture by geophysical-petrological modelling with LitMod3D. The model is built to reproduce gravity observations, the observed elevation with isostasy assumptions and the velocities from a tomography model. Furthermore, we adjust the thermal parameters and the temperature structure of the model to agree with different geothermal heat flow models. We use three different heat flow models, one from machine learning, one from a spectral analysis of magnetic data and another one which is compiled from a similarity study with tomography data.</p><p>For the latter, a new shear wave tomography model of Greenland is used. Vs-depth profiles from Greenland are compared with velocity profiles from the US Array, where a statistical link between Vs profiles and surface heat flow has been established. A similarity function determines the most similar areas in the U.S. and assigns the mean heat-flow from these areas to the corresponding area in Greenland.</p><p>The geothermal heat flow models will be further used to discuss the influence on ice sheet dynamics by comparison to friction heat and viscous heat dissipation from surface meltwater.</p>

Towards a global lithospheric thermal model

2020 ◽  
Author(s):  
Sheona Masterton ◽  
Samuel Cheyney ◽  
Chris Green ◽  
Peter Webb
Keyword(s):  
Heat Flow ◽  
Curie Temperature ◽  
Thermal Structure ◽  
Magnetic Layer ◽  
Surface Heat ◽  
Local Context ◽  
Magnetic Data ◽  
Flow Data ◽  
Surface Heat Flow ◽  
Temperature Depth

<p>Temperature and heat flow are key parameters for understanding the potential for source rock maturation in sedimentary basins. Knowledge of the thermal structure of the lithosphere in both a regional and local context can provide important constraints for modelling basin evolution through time.</p><p>In recent years, global coverage of heat flow data constraints have enhanced scientific understanding of the thermal state of the lithosphere. However, sample bias and variability in sampling methods continues to be a major obstacle to heat flow-derived isotherm prediction, particularly in frontier areas where data are often sparse or poorly constrained. Consideration and integration of alternative approaches to predict temperature at depth may allow interpolation of surface heat flow in such data poor areas.   </p><p>We have attempted to integrate three independent approaches to modelling temperature with depth. The first approach is based on heat flow observations, in which a 1D steady-state model of the lithosphere is constructed from quality-assessed surface heat flow data, crustal thickness estimates and associated lithospheric thermal properties. The second approach is based on terrestrial (airborne, ground and shipborne) magnetic data, in which the maximum depth of magnetisation within the lithosphere is estimated using a de-fractal method and used as a proxy for Curie temperature depth. The third approach is based on satellite magnetic data and estimates the thickness of the magnetic layer within the lithosphere based on the varying amplitudes of satellite magnetic data, accounting for global variations in crustal magnetisation. Curie temperature depth results from each of these approaches have been integrated into a single global grid, then used to calculate temperature-depth variations through the crust.</p><p>We have evaluated our isotherm predictions by comparing them with temperature-depth control points and undertook qualitative and quantitative analyses of discrepancies that exist between different modelling approaches; this has provided insights into the origin of such discrepancies that can be integrated into our models to generate a better controlled global temperature-depth result.  </p><p>We present details of our methodology and the results of our integrated studies. We demonstrate areas where the independent results are in good agreement, providing vital information for high-level basin screening. We also highlight areas of disagreement and suggest possible causes for these discrepancies and potential resolutions.</p>

Gravity, magnetics and geothermal heat flow of the Antarctic lithospheric crust and mantle

2021 ◽  
pp. M56-2020-5
Author(s):  
Folker Pappa ◽  
Jörg Ebbing
Keyword(s):  
Heat Flow ◽  
Gravity Data ◽  
Magnetic Data ◽  
Geothermal Heat ◽  
Satellite Gravity ◽  
Gravity And Magnetic ◽  
Magnetic Analysis ◽  
Gravity And Magnetic Data ◽  
The Antarctic ◽  
Broad Scale

AbstractThis chapter describes the application and coverage of gravity and magnetic data for Antarctica with emphasis on airborne and satellite models. Low resolution satellite data help to fill gaps between high-resolution airborne data. Satellite gravity data are best used to study broad-scale lithospheric architecture while airborne data, especially magnetic data, provide finer detail. We review examples of gravity and magnetic analysis and describe the possibilities and pitfalls for estimating the properties of the lithosphere as it relates to the mantle. This is followed by a discussion on geothermal heat flow and possible ways to combine different geophysical and petrological models for a better understanding of the Antarctic mantle.

scholarly journals Model-Based Probabilistic Inversion Using Magnetic Data: A Case Study on the Kevitsa Deposit

Geosciences ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 150
Author(s):  
Nilgün Güdük ◽  
Miguel de la Varga ◽  
Janne Kaukolinna ◽  
Florian Wellmann
Keyword(s):  
Structural Parameters ◽  
Rock Properties ◽  
Magnetic Data ◽  
Geological Model ◽  
Borehole Data ◽  
Likelihood Functions ◽  
Different Types ◽  
Geophysical Information ◽  
Different Sources

Structural geological models are widely used to represent relevant geological interfaces and property distributions in the subsurface. Considering the inherent uncertainty of these models, the non-uniqueness of geophysical inverse problems, and the growing availability of data, there is a need for methods that integrate different types of data consistently and consider the uncertainties quantitatively. Probabilistic inference provides a suitable tool for this purpose. Using a Bayesian framework, geological modeling can be considered as an integral part of the inversion and thereby naturally constrain geophysical inversion procedures. This integration prevents geologically unrealistic results and provides the opportunity to include geological and geophysical information in the inversion. This information can be from different sources and is added to the framework through likelihood functions. We applied this methodology to the structurally complex Kevitsa deposit in Finland. We started with an interpretation-based 3D geological model and defined the uncertainties in our geological model through probability density functions. Airborne magnetic data and geological interpretations of borehole data were used to define geophysical and geological likelihoods, respectively. The geophysical data were linked to the uncertain structural parameters through the rock properties. The result of the inverse problem was an ensemble of realized models. These structural models and their uncertainties are visualized using information entropy, which allows for quantitative analysis. Our results show that with our methodology, we can use well-defined likelihood functions to add meaningful information to our initial model without requiring a computationally-heavy full grid inversion, discrepancies between model and data are spotted more easily, and the complementary strength of different types of data can be integrated into one framework.

scholarly journals Critical Tectonic Limits for Geothermal Aquifer Use: Case Study from the East Slovakian Basin Rim

Resources ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 31
Author(s):  
Stanislav Jacko ◽  
Roman Farkašovský ◽  
Igor Ďuriška ◽  
Barbora Ščerbáková ◽  
Kristína Bátorová
Keyword(s):  
Heat Flow ◽  
Pannonian Basin ◽  
Open Fractures ◽  
Water Type ◽  
Geothermal Heat ◽  
The North ◽  
Heat System ◽  
Volcanic Chain ◽  
Saline Solutions

The Pannonian basin is a major geothermal heat system in Central Europe. Its peripheral basin, the East Slovakian basin, is an example of a geothermal structure with a linear, directed heat flow ranging from 90 to 100 mW/m2 from west to east. However, the use of the geothermal source is limited by several critical tectono-geologic factors: (a) Tectonics, and the associated disintegration of the aquifer block by multiple deformations during the pre-Paleogene, mainly Miocene, period. The main discontinuities of NW-SE and N-S direction negatively affect the permeability of the aquifer environment. For utilization, minor NE-SW dilatation open fractures are important, which have been developed by sinistral transtension on N–S faults and accelerated normal movements to the southeast. (b) Hydrogeologically, the geothermal structure is accommodated by three water types, namely, Na-HCO3 with 10.9 g·L−1 mineralization (in the north), the Ca-Mg-HCO3 with 0.5–4.5 g·L−1 mineralization (in the west), and Na-Cl water type containing 26.8–33.4 g·L−1 mineralization (in the southwest). The chemical composition of the water is influenced by the Middle Triassic dolomite aquifer, as well as by infiltration of saline solutions and meteoric waters along with open fractures/faults. (c) Geothermally anomalous heat flow of 123–129 °C with 170 L/s total flow near the Slanské vchy volcanic chain seems to be the perspective for heat production.

Euler’s differential equation and the identification of the magnetic point‐pole and point‐dipole sources

Geophysics ◽  
1984 ◽  
Vol 49 (9) ◽  
pp. 1549-1553 ◽  
Author(s):  
J. O. Barongo
Keyword(s):  
Magnetic Field ◽  
Differential Equation ◽  
Magnetic Anomalies ◽  
Field Vector ◽  
Magnetic Data ◽  
Dipole Source ◽  
Point Dipole ◽  
Main Subject ◽  
Depth Extent ◽  
Dipole Sources

The concept of point‐pole and point‐dipole in interpretation of magnetic data is often employed in the analysis of magnetic anomalies (or their derivatives) caused by geologic bodies whose geometric shapes approach those of (1) narrow prisms of infinite depth extent aligned, more or less, in the direction of the inducing earth’s magnetic field, and (2) spheres, respectively. The two geologic bodies are assumed to be magnetically polarized in the direction of the Earth’s total magnetic field vector (Figure 1). One problem that perhaps is not realized when interpretations are carried out on such anomalies, especially in regions of high magnetic latitudes (45–90 degrees), is that of being unable to differentiate an anomaly due to a point‐pole from that due to a point‐dipole source. The two anomalies look more or less alike at those latitudes (Figure 2). Hood (1971) presented a graphical procedure of determining depth to the top/center of the point pole/dipole in which he assumed prior knowledge of the anomaly type. While it is essential and mandatory to make an assumption such as this, it is very important to go a step further and carry out a test on the anomaly to check whether the assumption made is correct. The procedure to do this is the main subject of this note. I start off by first using some method that does not involve Euler’s differential equation to determine depth to the top/center of the suspected causative body. Then I employ the determined depth to identify the causative body from the graphical diagram of Hood (1971, Figure 26).

ADDITIONAL HEAT FLOW DETERMINATIONS IN THE AREA OF MOULD BAY, ARCTIC CANADA

1966 ◽  
Vol 3 (2) ◽  
pp. 237-246 ◽  
Author(s):  
W. S. B. Paterson ◽  
L. K. Law
Keyword(s):  
Heat Flow ◽  
Canadian Arctic ◽  
The Arctic ◽  
Canadian Arctic Archipelago ◽  
General Area ◽  
Geothermal Heat ◽  
Field Methods ◽  
The Mean ◽  
Water Depths ◽  
Made In

Seven determinations of geothermal heat flow were made in the general area of southern Prince Patrick Island in the Canadian Arctic Archipelago. Measurements were made from sea ice in water depths of between 200 and 600 m. The mean heat flow for the two stations on the continental shelf in the Arctic Ocean was 0.46 ± 0.08 μcal cm−2 s−1. The mean heat flow for the five stations in the channels to the east of Mould Bay was 1.46 ± 0.16 μcal cm−2 s−1. The instrument and field methods are described. Errors due to the instrument and to the environment are discussed.

Joint Inversion for Surface Accumulation and Geothermal Heat Flow from Ice-Penetrating Radar Observations at Dome A, East Antarctica. 

2021 ◽  
Author(s):  
Michael Wolovick ◽  
John Moore ◽  
Liyun Zhao
Keyword(s):  
Heat Flow ◽  
Accumulation Rate ◽  
Joint Inversion ◽  
Observational Constraints ◽  
Dome A ◽  
Glacial Cycles ◽  
Geothermal Heat ◽  
Hydrological System ◽  
And Storage ◽  
Best Fit

<p>Dome A is the summit of the East Antarctic Ice Sheet (EAIS), underlain by the rugged Gamburtsev Subglacial Mountains (GSM).  The rugged basal topography produces a complex hydrological system featuring basal melt, water transport and storage, and freeze-on.  Here, we present the results of an inverse model used to infer the spatial distributions of geothermal heat flow (GHF) and accumulation rate that best fit a variety of observational constraints.  Our model agrees well with the observed water bodies and freeze-on structures, while also predicting a significant amount of unobserved water and suggesting a change in stratigraphic interpretation that reduces the volume of the freeze-on units.  Our model stratigraphy agrees well with observations, and we predict that there will be two distinct patches of ice up to 1.5 Ma suitable for ice coring underneath the divide.  Past divide migration could have interrupted stratigraphic continuity at the old ice patches, but various indirect lines of evidence suggest that the divide has been stable for about the last one and a half glacial cycles, which is a hopeful but by no means definitive sign for stability in the longer term.  Finally, our GHF estimate is higher than previous estimates for this region, but consistent with possible heterogeneity in crustal heat production.     </p>

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