Airborne Gravity Gradient Data Research Articles

Application of curvatures to airborne gravity gradient data in oil exploration

We apply equipotential surface curvatures to airborne gravity gradient data. The mean and differential curvature of the equipotential surface, the curvature of the gravity field line, the zero contour of the Gaussian curvature, and the shape index improve the understanding and geologic interpretation of gravity gradient data. Their use is illustrated in model data and applied to FALCON airborne gravity gradiometer data from the Canning Basin, Australia.

Expression of terrain and surface geology in high-resolution helicopter-borne gravity gradient (AGG) data: Examples from Great Sand Dunes National Park, Rio Grande Rift, Colorado

Airborne gravity gradient (AGG) data are rapidly becoming standard components of geophysical mapping programs because of their advantages in cost, access, and resolution over measurements of the gravity field on the ground. Unlike conventional techniques that measure the gravity field, AGG methods measure derivatives of the gravity field. This means that effects of terrain and near-surface geology are amplified in AGG data, and that proper terrain corrections are critically important for AGG data processing. However, terrain corrections require reasonable estimates of density for the rocks and sediments that make up the terrain. A recommended philosophical approach is to use the terrain and surface geology, with their strong expression in AGG data, to the interpreter's advantage. An example of such an approach is presented here for an area with difficult ground access and little ground gravity data. Nettleton-style profiling is used with AGG data to estimate the densities of the sand dunefield and adjacent Precambrian rocks from the area of Great Sand Dunes National Park in southern Colorado. Processing of the AGG data using the density estimate for the dunefield allows buried structures, including a hypothesized buried basement bench, to be mapped beneath the sand dunes.

Consequences of flight height and line spacing on airborne (helicopter) gravity gradient resolution in the Great Sand Dunes National Park and Preserve, Colorado

Line spacing and flight height are critical parameters in airborne gravity gradient surveys; the optimal trade-off between survey costs and desired resolution, however, is different for every situation. This article investigates the additional benefit of reducing the flight height and line spacing though a study of a survey conducted over the Great Sand Dunes National Park and Preserve, which is the highest-resolution public-domain airborne gravity gradient data set available, with overlapping high- and lower-resolution surveys. By using Fourier analysis and matched filtering, it is shown that while the lower-resolution survey delineates the target body, reducing the flight height from 80 m to 40 m and the line spacing from 100 m to 50 m improves the recoverable resolution even at basement depths.

Structurally constrained lithology characterization using magnetic and gravity gradient data over an iron ore formation

SUMMARY It is often desirable to extract meaningful lithologic information directly from geophysical data. Here, we describe a multi-faceted approach that combines the known geologic sections of a site from borehole data with recovered density and magnetic susceptibility distributions from 3D inversion of airborne gravity gradient and magnetic data. The technique can produce end-member solutions based on average property values extracted from literature and well records; or, it can be implemented using the geologic sections to extract an appropriate range of property values to address the model smoothing common to modern 3D generalized inversions. To demonstrate our approach, we present results utilizing magnetic and gravity gradient data over part of the Gandarela Syncline iron formation in the Quadrilatero Ferrifero, Brazil.

Application of curvatures to airborne gravity gradients

The application of equipotential surface curvatures to airborne gravity gradient data is presented. The differential curvature, as measured by the FALCON? airborne gravity gradiometer system, the mean curvature, and the direction of maximum curvature of the equipotential surface should improve the understanding and geological interpretation of gravity gradient data. It has been shown that the horizontal gradients of the vertical component of the gravity vector form the curvature of the gravity field line. As this line is orthogonal to the equipotential surface, its curvature is related to how successive equipotential surfaces change and it may not be needed to interpret. The theoretical basis for the method is discussed. Practical applications of utilising the curvature method are presented on a synthetic model and FALCON? airborne gravity gradiometer data from the western zone of the Halls Creek Orogen, Western Australia.

Imaging geologic surfaces by inverting gravity gradient data with depth horizons

The nonuniqueness problem that occurs when inverting potential field data is well known. It can, however, be surmounted by jointly inverting these data with independent data sets, incorporating depth information and regularizing the solution. The goal is to produce a geologic model that is compatible with all measured quantities, does not exceed any prescribed limits, and is geologically plausible. To achieve this, we have developed a spatially based surface inversion algorithm that solves for the geometric interface between geologic bodies. The bodies are constructed from grids of rectangular prisms that have their bottom depths adjusted by the algorithm to form the inverted surface. To solve large-scale inversions, approximations are used in the potential field calculations that allow internal matrices to be stored in sparse format with minimal loss of accuracy. The impetus for the work came from the need to combine airborne gravity gradient data with depth horizons estimated from interpreted 2D seismic profiles to form a high-resolution 3D inversion for imaging salt bodies. By treating the depth information as measurements rather than constraints, we accommodate uncertainties in these estimates. Total variation regularization is incorporated to support the sharp edges of the salt structures and to stabilize the solution. Inversions for near-surface structures also incorporate a high-pass filter to suppress the interference in the gravity gradient signal from deeper geology. The resulting optimization finds a surface that fits (in a least-squares sense) the depth information and the high-frequency content of the gravity gradient data.

Processing gravity gradient data

As the demand for high-resolution gravity gradient data increases and surveys are undertaken over larger areas, new challenges for data processing have emerged. In the case of full-tensor gradiometry, the processor is faced with multiple derivative measurements of the gravity field with useful signal content down to a few hundred meters’ wavelength. Ideally, all measurement data should be processed together in a joint scheme to exploit the fact that all components derive from a common source. We have investigated two methods used in commercial practice to process airborne full-tensor gravity gradient data; the methods result in enhanced, noise-reduced estimates of the tensor. The first is based around Fourier operators that perform integration and differentiation in the spatial frequency domain. By transforming the tensor measurements to a common component, the data can be combined in a way that reduces noise. The second method is based on the equivalent-source technique, where all measurements are inverted into a single density distribution. This technique incorporates a model that accommodates low-order drift in the measurements, thereby making the inversion less susceptible to correlated time-domain noise. A leveling stage is therefore not required in processing. In our work, using data generated from a geologic model along with noise and survey patterns taken from a real survey, we have analyzed the difference between the processed data and the known signal to show that, when considering the Gzz component, the modified equivalent-source processing method can reduce the noise level by a factor of 2.4. The technique has proven useful for processing data from airborne gradiometer surveys over mountainous terrain where the flight lines tend to be flown at vastly differing heights.

Inversion of airborne gravity gradient data, southwestern Oklahoma

The diagonal elements of the gravity gradient tensor, as recorded by the Bell airborne Gravity Gradient Survey System (GGSS), are used to determine the basement topography in southwestern Oklahoma. This determination is accomplished through a nonlinear inverse procedure based on the conjugate gradient algorithm. The resulting model contains a ridge of shallow basement material (⩽3.0 km deep) trending east‐southeast. This ridge is bounded on the north and the south by basement troughs; the northern trough extends as deep as 10.0 km. The gradient field which results from this model fits most of the GGSS observations within their estimated errors of 12.0 E [Formula: see text]. The model is in general agreement with a set of available oil well depths to the basement and with inferred faults in these igneous rocks. To assess the derived solution, the problem was linearized about the final model and the linear parameter resolution and parameter covariances were computed. Generally, the basement depths are well resolved and the resolution matrix is diagonally dominant. Furthermore, the parameter standard errors are small: 72 parameters out of 98 have errors less than 1.0 km.