Airborne Gravity 2010 - Geoscience Australia

Airborne Gravity 2010
3D imaging of subsurface structures using
migration and regularized focusing inversion of
gravity and gravity gradiometry data
Introduction
Michael S. Zhdanov 1 , Glenn A. Wilson 2 , and Xiaojun Liu 3
1 University of Utah & TechnoImaging (mzhdanov@technoimaging.com)
2 TechnoImaging (glenn@technoimaging.com)
3 University of Utah (xiaojun.liu@utah.edu)
Since gravity and gravity gradiometry can provide an independent measure of the subsurface density
distribution, they have come to be routinely integrated into exploration workflows. The advantage of
gravity gradiometry over other gravity methods is that the data are extremely sensitive to localized
density contrasts within regional geological settings. Moreover, high quality data can now be acquired
from either air- or ship-borne platforms over very large areas at relatively low cost.
Here, we present the results from two different methods of interpretation for gravity and gravity
gradiometry data. We introduce potential field migration that is a direct integral transformation of the
observed gravity fields and/or their gradients into 3D images of density distribution. Unlike ill-posed
and unstable transforms such as downward analytic continuation or higher order differentiation,
migration is a well-posed and stable transformation. Migration does not assume nor require any a
priori information about the type of the source of the fields. When implemented, potential field
migration is fast and robust, and can be used for real-time imaging as well as for producing a priori
models for a subsequent inversion.
We then introduce 3D regularized focusing inversion, whereby the use of focusing stabilizers allows
the recovery of subsurface models with sharper density contrasts than can be obtained using
traditional smooth stabilizers. Our inversion is based on the re-weighted regularized conjugate
gradient method. Compression and FFT matrix multiplications further reduce memory requirements
and runtimes, so as to make it practical to invert entire airborne or marine datasets to models with
millions of cells.
The combination of migration and inversion makes it is feasible to run multiple interpretation scenarios
based on different data combinations and various regularization parameters so as to build confidence
in the robustness of features in the recovered models. It also allows us to discriminate any artifacts
that may arise from any single interpretation. Here, we demonstrate these methods using a case study
for the inversion of marine gravity gradiometry data for salt mapping in the Norwegian Barents Sea.
Potential Field Migration
A variety of fast imaging techniques related to Euler decomposition have been developed. Most of
these are based on the superposition of analytical responses from specific sources. These imaging
methods estimate the positions and some parameters of the sources based on field attenuation
characteristics. We developed a different approach to imaging, one which we base on the idea of
potential field migration as originally introduced by Zhdanov (2002) and first applied to gravity
gradiometry data by Zhdanov et al. (2010). The concept of the migration was developed for seismic
wave fields (e.g., Schneider, 1978; Berkhout, 1980; Claerbout, 1985). Since, it has been demonstrated
that the same concept can also be extended to electromagnetic and potential fields (Zhdanov, 1988,
2002, 2009a). Potential field migration is based on a special form of downward continuation of the
potential field or one of its gradients. This downward continuation is obtained as the solution of the
boundary value problem to Laplace’s equation in the lower half-space where the boundary values of
the migration field on the Earth’s surface are determined from the observed data. It is important to
stress that potential field migration is not the same as analytic continuation. It transforms the observed
field into a migration field, and does not attempt to reconstruct the true potential field. However, the
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