Advances in 3D Potential Field Modeling

Alvers, Michael R.; Götze, H.-J.; Lahmeyer, B.; Plonka, Christian; Schmidt, Sabine

doi:10.3997/2214-4609.20130125

Cited by 6 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, our inverse problem formulation is based on a mixed scheme that combines a stochastic optimization technique known as Covariance Matrix Adaptation Evolution Strategy (CMAES) (Hansen & Ostermeier, 2001), with McMC methods (e.g., Mosegaard & Tarantola, 1995). Although the use of CMAES in geophysics is not common, it has been implemented in recent studies as a global minimization method (Alvers et al, 2013;Diouane, 2014;Fonseca et al, 2014;Grayver et al, , 2017Shen et al, 2015) outperforming other techniques such as genetic algorithms and particle Although the use of CMAES in geophysics is not common, it has been implemented in recent studies as a global minimization method (Alvers et al, 2013;Diouane, 2014;Fonseca et al, 2014;Grayver et al, , 2017Shen et al, 2015) outperforming other techniques such as genetic algorithms and particle…”

Section: Stochastic Inversionmentioning

confidence: 99%

“…CMAES explores the model space globally and exhibits a remarkable robustness on ill-conditioned problems (Hansen et al, 2011). Although the use of CMAES in geophysics is not common, it has been implemented in recent studies as a global minimization method (Alvers et al, 2013;Diouane, 2014;Fonseca et al, 2014;Grayver et al, , 2017Shen et al, 2015) outperforming other techniques such as genetic algorithms and particle Journal of Geophysical Research: Solid Earth 10.1002/2017JB014691 Swarm optimization (Arsenault et al, 2013;Auger et al, 2009;Elshall et al, 2015). Additionally, showed that the use of CMAES for finding regions of low misfit can improve performance of conventional McMC methods.…”

Section: Stochastic Inversionmentioning

confidence: 99%

See 1 more Smart Citation

Stochastic Inversion of Geomagnetic Observatory Data Including Rigorous Treatment of the Ocean Induction Effect With Implications for Transition Zone Water Content and Thermal Structure

et al. 2018

View full text Add to dashboard Cite

In this paper we estimate and invert local electromagnetic (EM) sounding data for 1‐D conductivity profiles in the presence of nonuniform oceans and continents to most rigorously account for the ocean induction effect that is known to strongly influence coastal observatories. We consider a new set of high‐quality time series of geomagnetic observatory data, including hitherto unused data from island observatories installed over the last decade. The EM sounding data are inverted in the period range 3–85 days using stochastic optimization and model exploration techniques to provide estimates of model range and uncertainty. The inverted conductivity profiles are best constrained in the depth range 400–1,400 km and reveal significant lateral variations between 400 km and 1,000 km depth. To interpret the inverted conductivity anomalies in terms of water content and temperature, we combine laboratory‐measured electrical conductivity of mantle minerals with phase equilibrium computations. Based on this procedure, relatively low temperatures (1200–1350°C) are observed in the transition zone (TZ) underneath stations located in Southern Australia, Southern Europe, Northern Africa, and North America. In contrast, higher temperatures (1400–1500°C) are inferred beneath observatories on islands, Northeast Asia, and central Australia. TZ water content beneath European and African stations is ∼0.05–0.1 wt %, whereas higher water contents (∼0.5–1 wt %) are inferred underneath North America, Asia, and Southern Australia. Comparison of the inverted water contents with laboratory‐constrained water storage capacities suggests the presence of melt in or around the TZ underneath four geomagnetic observatories in North America and Northeast Asia.

show abstract

Section: Stochastic Inversionmentioning

confidence: 99%

Section: Stochastic Inversionmentioning

confidence: 99%

Stochastic Inversion of Geomagnetic Observatory Data Including Rigorous Treatment of the Ocean Induction Effect With Implications for Transition Zone Water Content and Thermal Structure

et al. 2018

View full text Add to dashboard Cite

show abstract

“…This technique aims to explore the model space globally showing remarkable robustness on ill‐conditioned problems (Hansen et al, ). The use of CMAES in geophysics is not common, but has recently been implemented as a global minimization method (Alvers et al, ; Diouane, ; Grayver et al, ; Munch et al, ; Shen et al, ) outperforming other optimization techniques such as Genetic Algorithms and Particle Swarm Optimization (Arsenault et al, ; Auger et al, ; Elshall et al, ).…”

Section: Inverse Problemmentioning

confidence: 99%

Stochastic Inversion of P‐to‐S Converted Waves for Mantle Composition and Thermal Structure: Methodology and Application

et al. 2018

View full text Add to dashboard Cite

We present a new methodology for inverting P‐to‐S receiver function (RF) waveforms directly for mantle temperature and composition. This is achieved by interfacing the geophysical inversion with self‐consistent mineral phase equilibria calculations from which rock mineralogy and its elastic properties are predicted as a function of pressure, temperature, and bulk composition. This approach anchors temperatures, composition, seismic properties, and discontinuities that are in mineral physics data, while permitting the simultaneous use of geophysical inverse methods to optimize models of seismic properties to match RF waveforms. Resultant estimates of transition zone (TZ) topography and volumetric seismic velocities are independent of tomographic models usually required for correcting for upper mantle structure. We considered two end‐member compositional models: the equilibrated equilibrium assemblage (EA) and the disequilibrated mechanical mixture (MM) models. Thermal variations were found to influence arrival times of computed RF waveforms, whereas compositional variations affected amplitudes of waves converted at the TZ discontinuities. The robustness of the inversion strategy was tested by performing a set of synthetic inversions in which crustal structure was assumed both fixed and variable. These tests indicate that unaccounted‐for crustal structure strongly affects the retrieval of mantle properties, calling for a two‐step strategy presented herein to simultaneously recover both crustal and mantle parameters. As a proof of concept, the methodology is applied to data from two stations located in the Siberian and East European continental platforms.

show abstract

Potential Methods and Geoinformation Systems

Götze

2013

Handbook of Geomathematics

View full text Add to dashboard Cite

Advances in 3D Potential Field Modeling

Cited by 6 publications

References 0 publications

Stochastic Inversion of Geomagnetic Observatory Data Including Rigorous Treatment of the Ocean Induction Effect With Implications for Transition Zone Water Content and Thermal Structure

Stochastic Inversion of Geomagnetic Observatory Data Including Rigorous Treatment of the Ocean Induction Effect With Implications for Transition Zone Water Content and Thermal Structure

Stochastic Inversion of P‐to‐S Converted Waves for Mantle Composition and Thermal Structure: Methodology and Application

Potential Methods and Geoinformation Systems

Contact Info

Product

Resources

About