Joint inversion of seismic traveltimes and gravity data on unstructured grids with application to mineral exploration

2010 ◽  
Author(s):  
Peter G. Lelièvre ◽  
Colin G. Farquharson ◽  
Charles A. Hurich
Keyword(s):  
Unstructured Grids ◽  
Joint Inversion ◽  
Mineral Exploration ◽  
Gravity Data

Joint inversion of seismic traveltimes and gravity data on unstructured grids with application to mineral exploration

Geophysics ◽  
2012 ◽  
Vol 77 (1) ◽  
pp. K1-K15 ◽  
Author(s):  
Peter G. Lelièvre ◽  
Colin G. Farquharson ◽  
Charles A. Hurich
Keyword(s):  
Seismic Data ◽  
Unstructured Grids ◽  
Joint Inversion ◽  
Mineral Exploration ◽  
Gravity Data ◽  
Physical Property ◽  
Sulfide Deposit ◽  
Earth Model ◽  
Data Set ◽  
First Arrival

Seismic methods continue to receive interest for use in mineral exploration due to the much higher resolution potential of seismic data compared to the techniques traditionally used, namely, gravity, magnetics, resistivity, and electromagnetics. However, the complicated geology often encountered in hard-rock exploration can make data processing and interpretation difficult. Inverting seismic data jointly with a complementary data set can help overcome these difficulties and facilitate the construction of a common earth model. We considered the joint inversion of seismic first-arrival traveltimes and gravity data to recover causative slowness and density distributions. Our joint inversion algorithm differs from previous work by (1) incorporating a large suite of measures for coupling the two physical property models, (2) slowly increasing the effect of the coupling to help avoid potential convergence issues, and (3) automatically adjusting two Tikhonov tradeoff parameters to achieve a desired fit to both data sets. The coupling measures used are both compositional and structural in nature and allow the inclusion of explicitly known or implicitly assumed empirical relationships, physical property distribution information, and cross-gradient structural coupling. For any particular exploration scenario, the combination of coupling measures used should be guided by the geologic knowledge available. We performed our inversions on unstructured grids comprised of triangular cells in 2D, or tetrahedral cells in 3D, but the joint inversion methods are equally applicable to rectilinear grids. We tested our joint inversion methodology on scenarios based on the Voisey’s Bay massive sulfide deposit in Labrador, Canada. These scenarios present a challenge to the inversion of first-arrival traveltimes and we show how joint inversion with gravity data can improve recovery of the subsurface features.

scholarly journals Joint Inversion of 2D Gravity Gradiometry and Magnetotelluric Data in Mineral Exploration

Minerals ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 541 ◽  
Author(s):  
Rongzhe Zhang ◽  
Tonglin Li
Keyword(s):  
2D Gravity ◽  
Joint Inversion ◽  
Mineral Exploration ◽  
Gravity Data ◽  
Computation Time ◽  
Iteration Algorithm ◽  
Imaging Method ◽  
Gravity Gradiometry ◽  
Magnetotelluric Data ◽  
Data Space

We have developed a mineral exploration method for the joint inversion of 2D gravity gradiometry and magnetotelluric (MT) data based on data-space and normalized cross-gradient constraints. To accurately explore the underground structure of complex mineral deposits and solve the problems such as the non-uniqueness and inconsistency of the single parameter inversion model, it is now common practice to perform collocated MT and gravity surveys that complement each other in the search. Although conventional joint inversion of MT and gravity using model-space can be diagnostic, we posit that better results can be derived from the joint inversion of the MT and gravity gradiometry data using data-space. Gravity gradiometry data contains more abundant component information than traditional gravity data and can be used to classify the spatial structure and location of underground structures and field sources more accurately and finely, and the data-space method consumes less memory and has a shorter computation time for our particular inversion iteration algorithm. We verify our proposed method with synthetic models. The experimental results prove that our proposed method leads to models with remarkable structural resemblance and improved estimates of electrical resistivity and density and requires shorter computation time and less memory. We also apply the method to field data to test its potential use for subsurface lithofacies discrimination or structural classification. Our results suggest that the imaging method leads to improved characterization of geological targets, which is more conducive to geological interpretation and the exploration of mineral resources.

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.

scholarly journals Three-Dimensional Regularized Focusing Migration: A Case Study from the Yucheng Mining Area, Shandong, China

Minerals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 471
Author(s):  
Yidan Ding ◽  
Guoqing Ma ◽  
Shengqing Xiong ◽  
Haoran Wang
Keyword(s):  
Large Scale ◽  
Mineral Exploration ◽  
Gravity Data ◽  
Three Dimensional ◽  
Mining Area ◽  
Model Parameters ◽  
Step Size ◽  
Migration Direction ◽  
Migration Imaging ◽  
Imaging Results

Gravity migration is a fast imaging technique based on the migration concept to obtain subsurface density distribution. For higher resolution of migration imaging results, we propose a 3D regularized focusing migration method that implements migration imaging of an entire gravity survey with a focusing stabilizer based on regularization theory. When determining the model parameters, the iterative direction is chosen as the conjugate migration direction, and the step size is selected on the basis of the Wolfe–Powell conditions. The model tests demonstrate that the proposed method can improve the resolution and precision of imaging results, especially for blocky structures. At the same time, the method has high computational efficiency, which allows rapid imaging for large-scale gravity data. It also has high stability in noisy conditions. The developed novel method is applied to interpret gravity data collected from the skarn-type iron deposits in Yucheng, Shandong province. Migration results show that the depth of the buried iron ore in this area is 750–1500 m, which is consistent with the drilling data. We also provide recommendations for further mineral exploration in the survey area. This method can be used to complete rapid global imaging of large mining areas and it provides important technical support for exploration of deep, concealed deposits.

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