3D joint inversion of gravity-gradient and borehole gravity data

2017 ◽  
Vol 48 (2) ◽  
pp. 151-165 ◽  
Author(s):  
Meixia Geng ◽  
Qingjie Yang ◽  
Danian Huang
Keyword(s):  
Joint Inversion ◽  
Gravity Data ◽  
Gravity Gradient

Joint inversion of the lithospheric density struture in the North China Craton based on GOCE satellite gravity gradient data and surface gravity data

2020 ◽  
Author(s):  
Yu Tian ◽  
Yong Wang
Keyword(s):  
North China ◽  
Joint Inversion ◽  
Gravity Data ◽  
Initial Density ◽  
Gravity Gradient ◽  
Density Structure ◽  
Satellite Gravity ◽  
Density Data ◽  
The North ◽  
Goce Satellite

<p>The North China Craton (NCC) is one of the oldest cratons in the world. Currently, the destruction mechanism and geodynamics of the NCC still remain controversial. All of the proposed views regarding the issues involve studying the internal density structure of the NCC lithosphere. Gravity field data are one of the most important data in regard to investigating the lithospheric density structure, the gravity gradient data and the gravity data possess their own advantages. Given the inconsistency of the on orbit GOCE satellite gravity gradient and surface gravity observation plane height, also effects of the initial density model upon of the inversion results, the joint inversion of gravity gradient and gravity are divided into two integrated processes. By using the preconditioned conjugate gradient (PCG) inversion algorithm, the density data are calculated using the preprocessed remaining gravity anomaly data. The newly obtained high resolution density data are then used as the initial density model, which can be served as the constraints for the subsequent gravity gradient inversion. Downward continuation, terrain correction, interface undulation correction and long wavelength correction are performed for the four gravity gradient tensor data(<strong>T</strong><sub>xx</sub>，<strong>T</strong><sub>xz</sub>，<strong>T</strong><sub>yy</sub>，<strong>T</strong><sub>zz</sub>)of the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite,  after which the remaining gravity gradient anomaly data(<strong>T</strong>'<sub>xx</sub>，<strong>T</strong>'<sub>xz</sub>，<strong>T</strong>'<sub>yy</sub>，<strong>T</strong>'<sub>zz</sub>) are used as the new observation quantity. Finally, the ultimate lithospheric density distribution within the depth range of 0–180 km in the NCC is obtained using the same PCG algorithm.</p>

scholarly journals Joint inversion of the lithospheric density struture in the North China Craton based on GOCE satellite gravity gradient data and surface gravity data

2020 ◽  
Author(s):  
Yu Tian ◽  
Yong Wang
Keyword(s):  
North China ◽  
Joint Inversion ◽  
Gravity Data ◽  
Initial Density ◽  
Gravity Gradient ◽  
Density Structure ◽  
Satellite Gravity ◽  
Density Data ◽  
The North ◽  
Goce Satellite

Abstract. The North China Craton (NCC) is one of the oldest cratons in the world. Currently, the destruction mechanism and geodynamics of the NCC still remain controversial. All of the proposed views regarding the issues involve studying the internal density structure of the NCC lithosphere. Gravity field data are one of the most important data in regard to investigating the lithospheric density structure, the gravity gradient data and the gravity data possess their own advantages. Given the inconsistency of the on orbit GOCE satellite gravity gradient and surface gravity observation plane height, also effects of the initial density model upon of the inversion results, the joint inversion of gravity gradient and gravity are divided into two integrated processes. By using the preconditioned conjugate gradient (PCG) inversion algorithm, the density data are calculated using the preprocessed remaining gravity anomaly data. The newly obtained high resolution density data are then used as the initial density model, which can be served as the constraints for the subsequent gravity gradient inversion. Several essential corrections are performed for the four gravity gradient tensor (Txx，Txz，Tyy，Tzz) of the GOCE satellite, after which the remaining gravity gradient anomaly (T'xx，

Delineating Geothermal Structure from 3D Joint Inversion of MT and Gravity Data

2020 ◽  
Author(s):  
W. Soyer ◽  
R. Mackie ◽  
S. Hallinan ◽  
F. Miorelli ◽  
A. Pavesi
Keyword(s):  
Joint Inversion ◽  
Gravity Data

Joint receiver function and gravity inversion for new constraints on the Ivrea body structure: a 2D high-resolution view along the Val Sesia profile (N. Italy).

2021 ◽  
Author(s):  
Matteo Scarponi ◽  
György Hetényi ◽  
Jaroslava Plomerová ◽  
Stefano Solarino
Keyword(s):  
High Resolution ◽  
Velocity Structure ◽  
Receiver Function ◽  
Joint Inversion ◽  
Gravity Data ◽  
Rock Physics ◽  
Receiver Functions ◽  
Gravity Inversion ◽  
European Alps ◽  
Horizontal Distance

<p>We present results from a joint inversion study of new seismic and gravity data to constrain a 2D high-resolution image of one of the most prominent geophysical anomalies of the European Alps: the Ivrea geophysical body (IGB). Our work exploits both new data and multidisciplinary a priori constraints, to better resolve the shallow crustal structure in the Ivrea-Verbano zone (IVZ), where the IGB is known to reach anomalously shallow depths and partially outcrop at the surface.</p><p>A variety of previous studies, ranging from gravity surveys to vintage refraction seismics and recent local earthquake tomographies (Solarino et al. 2018, Diehl et al. 2009), provide comprehensive but spatially sparse information on the IGB structure, which we aim at investigating at higher resolution, along a linear profile crossing the IVZ. To this purpose, we deployed 10 broadband seismic stations (MOBNET pool, IG CAS Prague), 5 km spaced along a linear West-East profile, along Val Sesia and crossing Lago Maggiore. This network operated for 27 months and allowed us to produce a new database of ca. 1000 seismic high-quality receiver functions (RFs). In addition, we collected new gravity data in the IVZ, with a data coverage of 1 gravity point every 1-2 km along the seismic profile. The newly collected data was used to set up an inversion scheme, in which RFs and gravity anomalies are jointly used to constrain the shape and the physical property contrasts across the IGB interface.</p><p>We model the IGB as a single interface between far-field constraints, whose geometry is defined by the coordinates of four nodes which may vary in space, and  density and V<sub>S</sub> shear-wave velocity contrasts associated with the interface itself, varying independently. A Markov chain Monte Carlo (MCMC) sampling method with Metropolis-Hastings selection rule was implemented to efficiently explore the model space, directing the search towards better fitting areas.</p><p>For each model, we perform ray-tracing and RFs migration using the actual velocity structure both for migration and computation of synthetic RFs, to be compared with the observations via cross-correlation of the migration images. Similarly, forward gravity modelling for a 2D density distribution is implemented and the synthetic gravity anomaly is compared with the observations along the profile. The joint inversion performance is the product of these two misfits.</p><p>The inversion results show that the IGB reaches the shallowest depths in the western part of the profile, preferentially locating the IGB interface between 3 and 7 km depth over a horizontal distance of ca. 20 km (between Boccioleto and Civiasco, longitudes 8.1 and 8.3). Within this segment, the shallowest point reaches up to 1 km below sea level. The found density and velocity contrasts are in agreement with rock physics properties of various units observed in the field and characterized in earlier studies.</p>

Joint inversion of potential-fields data over the DO-27 kimberlite pipe using a Gaussian mixture model prior

2020 ◽  
Vol 8 (4) ◽  
pp. SS47-SS62
Author(s):  
Thibaut Astic ◽  
Dominique Fournier ◽  
Douglas W. Oldenburg
Keyword(s):  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Joint Inversion ◽  
Gravity Data ◽  
Physical Property ◽  
Gaussian Mixture ◽  
Kimberlite Pipe ◽  
Magnetic Data ◽  
High Porosity ◽  
Rock Types

We have carried out petrophysically and geologically guided inversions (PGIs) to jointly invert airborne and ground-based gravity data and airborne magnetic data to recover a quasi-geology model of the DO-27 kimberlite pipe in the Tli Kwi Cho (also referred to as TKC) cluster. DO-27 is composed of three main kimberlite rock types in contact with each other and embedded in a granitic host rock covered by a thin layer of glacial till. The pyroclastic kimberlite (PK), which is diamondiferous, and the volcanoclastic kimberlite (VK) have anomalously low density, due to their high porosity, and weak magnetic susceptibility. They are indistinguishable from each other based upon their potential-field responses. The hypabyssal kimberlite (HK), which is not diamondiferous, has been identified as highly magnetic and remanent. Quantitative petrophysical signatures for each rock unit are obtained from sample measurements, such as the increasing density of the PK/VK unit with depth and the remanent magnetization of the HK unit, and are represented as a Gaussian mixture model (GMM). This GMM guides the PGI toward generating a 3D quasi-geology model with physical properties that satisfies the geophysical data sets and the petrophysical signatures. Density and magnetization models recovered individually yield volumes that have physical property combinations that do not conform to any known petrophysical characteristics of the rocks in the area. A multiphysics PGI addresses this problem by using the GMM as a coupling term, but it puts a volume of the PK/VK unit at a location that is incompatible with geologic information from drillholes. To conform to that geologic knowledge, a fourth unit is introduced, PK-minor, which is petrophysically and geographically distinct from the main PK/VK unit. This inversion produces a quasi-geology model that presents good structural locations of the diamondiferous PK unit and can be used to provide a resource estimate or decide the locations of future drillholes.

3D joint inversion of seismic traveltime and gravity data: A case study

2015 ◽  
Author(s):  
Dengguo Zhou ◽  
Weizhong Wang ◽  
Jie Zhang ◽  
Daniel R.H. O'Connell
Keyword(s):  
Joint Inversion ◽  
Gravity Data
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