Two-step Gravity Inversion Reveals Variable Architecture of African Cratons

The lithospheric build-up of the African continent is still to a large extent unexplored. In this contribution, we present a new Moho depth model to discuss the architecture of the three main African cratonic units, which are: West African Craton, Congo Craton, and Kalahari Craton. Our model is based on a two-step gravity inversion approach that allows variable density contrasts across the Moho depth. In the first step, the density contrasts are varied for all non-cratonic units, in the second step for the three cratons individually. The lateral extension of the tectonic units is defined by a regionalization map, which is calculated from a recent continental seismic tomography model. Our Moho depth is independently constrained by pointwise active seismics and receiver functions. Treating the constraints separately reveals a variable range of density contrasts and different trends in the estimated Moho depth for the three cratons. Some of the estimated density contrasts vary substantially, caused by sparse data coverage of the seismic constraints. With a density contrast of Δ ρ = 200 kg/m3 the Congo Craton features a cool and undisturbed lithosphere with smooth density contrasts across the Moho. The estimated Moho depth shows a bimodal pattern with average Moho depth of 39–40 km for the Kalahari and Congo Cratons and 33–34 km for the West African Craton. We link our estimated Moho depth with the cratonic extensions, imaged by seismic tomography, and with topographic patterns. The results indicate that cratonic lithosphere is not necessarily accompanied by thick crust. For the West African Craton, the estimated thin crust, i.e. shallow Moho, contrasts to thick lithosphere. This discrepancy remains enigmatic and requires further studies.

Uncertainty quantification of geological model parameters in 3D gravity inversion by Hessian informed Markov chain Monte Carlo

Geological modeling has been widely adopted to investigate underground geometries. However, modeling processes inevitably have uncertainties due to scarcity of data, measurement errors, and simplification of modeling methods. Recent developments in geomodeling methods have introduced a Bayesian framework to constrain the model uncertainties by considering additional geophysical data into the modeling procedure. Markov chain Monte Carlo (MCMC) methods are normally used as tools to solve the Bayesian inference problem. To achieve a more efficient posterior exploration, advances inMCMC methods utilize derivative information. Hence, we introduce an approach to efficiently evaluate second-order derivatives in geological modeling and introduce a Hessian-informed MCMC method, the generalized preconditioned Crank-Nicolson (gpCN), as a tool to solve the 3D model-based gravity Bayesian inversion problem. The result is compared with two other widely applied MCMC methods, random walk Metropolis-Hasting and Hamiltonian Monte Carlo, on a synthetic three-layer geological model. Our experiment demonstrates that superior performance is achieved by the gpCN, which has the potential to be generalized to more complex models.

Joint inversion of gravity and gravity gradient data: A systematic evaluation

Gravity and gravity gradiometry measurements are commonly used to map density variations in the subsurface. Gravity measurements can characterize gravitational anomalies at both long and short wavelengths effectively, but the cost of collecting a sufficiently spatially dense survey to characterize the short wavelengths can be prohibitive. Gravity gradient data can be quickly collected with short wavelength information at a low noise level, but have decreasing sensitivity to longer wavelengths. We describe a method to jointly invert gravity and gravity gradient data that takes advantage of the differing frequency contents and noise levels of the two methods to create an improved image of the subsurface. Previous work simply treated the inversion as a multiple component gravity inversion, however this can cause unintended errors in the recovered models because each data set is not guaranteed to be fit within its noise level. Our joint inversion methodology ensures that both the gravity and gravity gradient data sets are fit to within their individual noise levels by incorporating a relative weighting parameter, and we describe how to find that parameter. This method can also be used to create an improved broadband gravity anomaly map that has a reduced noise level at long wavelengths using a joint equivalent source reconstruction. We first build a synthetic model using a Minecraft world editor, that has different wavelength anomalies, and show the improvement with joint inversion. These results are also confirmed using a real world example at the R. J. Smith test range in Kauring, Australia.

Moho Geometry of the Okinawa Trough Based on Gravity Inversion and Its Implications on the Crustal Nature and Tectonic Evolution

The Okinawa Trough (OT) is an incipient back-arc basin, but its crustal nature is still controversial. Gravity inversion along with sediment and lithospheric mantle density modeling are used to map the regional Moho depth and crustal thickness variations of the OT and its adjacent areas. The gravity inversion result shows that the crustal thicknesses are 17–22 km at the northern OT, 11–19 km at the central OT, and 7–19 km at the southern OT. Because of the crust with a thickness larger than 17 km, the slow southward arc movement, and scarce contemporaneous volcanisms, the northern OT should be in the stage of early back-arc extension. All of the moderate crustal thickness, high heat flow, and intense volcanism at the central OT indicate that this region is probably in the transitional stage from the back-arc rifting to the oceanic spreading. A crust that is only 7 km thick, lithosphere strength as low as the mid-ocean ridge, and MORB-similar basalts at the southern OT demonstrate that the southern OT is at the early stage of seafloor spreading.

Analysis on the Characteristics of Crustal Structure and Seismotectonic Environment in Zigui Basin, Three Gorges

The Zigui Basin in the Three Gorges area is a syncline running in the north-south axial direction; the sediments in the basin are mainly late Triassic-late Jurassic sandy and argillaceous rocks. Since the Three Gorges Project began undergoing impoundment in May 2003, nearly 20,000 mini-earthquakes have occurred in the Zigui–Badong region, including five earthquakes with magnitudes greater than Ms 5.0. Herein, a 3D gravity inversion method was introduced to investigate the density structure of the Zigui Basin and its adjacent areas. A comprehensive analysis of the geological structure of the area was carried out, based on focal mechanism solutions of six moderate–strong earthquakes in the area. The Zigui Basin is a low–density area from the periphery, and the sediment in the east is thicker but less dense than in the west. The shallow part of the Zigui Basin is a weak bottom layer prone to slippage, and the deep part (5–10 km) could comprise lithological strata such as limestone, sandstone, and shale, which easily undergo dissolution by leaking reservoir water. Under the action of external forces such as long-term infiltration and unloading of reservoir water, fissures will expand and squeeze then earthquakes are likely induced in the deep strata. Furthermore, new buried faults in the western and southeastern edges of the core area of the Zigui Basin could also trigger an earthquake under long–term pressurization and reservoir water penetration.

Seismic Constrained Gravity Inversion: A Reliable Tool to Improve Geophysical Models Away from Seismic Information

The exploitation of gravity fields in order to retrieve information about subsurface geological structures is sometimes considered a second rank method, in favour of other geophysical methods, such as seismic, able to provide a high resolution detailed picture of the main geological horizons. Within the current work we prove, through a realistic synthetic case study, that the gravity field, thanks to the availability of freely of charge high resolution global models and to the improvements in the gravity inversion methods, can represent a valid and cheap tool to complete and enhance geophysical modelling of the Earth’s crust. Three tests were carried out: In the first one a simple two-layer problem was considered, while in tests two and three we considered two more realistic scenarios in which the availability on the study area of constraints derived from 3D or 2D seismic surveys were simulated. In all the considered test cases, in which we try to simulate real-life scenarios, the gravity field, inverted by means of an advanced Bayesian technique, was able to obtain a final solution closer to the (simulated) real model than the assumed a priori information, typically halving the uncertainties in the geometries of the main geological horizons with respect to the initial model.

Constraining 3D geometric gravity inversion with a 2D reflection seismic profile using a generalized level set approach: application to the eastern Yilgarn Craton

One of the main tasks in 3D geological modeling is the boundary parametrization of the subsurface from geological observations and geophysical inversions. Several approaches have been developed for geometric inversion and joint inversion of geophysical datasets. However, the robust, quantitative integration of models and datasets with different spatial coverage, resolution, and levels of sparsity remains challenging. One promising approach for recovering the boundary of the geological units is the utilization of a level set inversion method with potential field data. We focus on constraining 3D geometric gravity inversion with sparse lower-uncertainty information from a 2D seismic section. We use a level set approach to recover the geometry of geological bodies using two synthetic examples and data from the geologically complex Yamarna Terrane (Yilgarn Craton, Western Australia). In this study, a 2D seismic section has been used for constraining the location of rock unit boundaries being solved during the 3D gravity geometric inversion. The proposed work is the first we know of that automates the process of adding spatially distributed constraints to the 3D level set inversion. In many hard-rock geoscientific investigations, seismic data are sparse, and our results indicate that unit boundaries from gravity inversion can be much better constrained with seismic information even though they are sparsely distributed within the model. Thus, we conclude that it has the potential to bring the state of the art a step further towards building a 3D geological model incorporating several sources of information in similar regions of investigation.

Structure-guided gravity inversion for layered density modeling with an application in the Chezhen Depression, Bohai Bay Basin

Gravity inversion, as a static potential field inversion, has inherent ambiguity with low vertical resolution. In order to reduce the nonuniqueness of inversion, it is necessary to impose the apriori constraints derived by other geophysical inversion, drilling or geological modeling. Based on the a priori normalized gradients derived from seismic imaging or reference models, a structure-guided gravity inversion method with a few known point constraints is developed for mapping density with multiple layers. The cubic B-spline interpolation is used to parameterize the forward modeling calculation of the gravity response to smooth density fields. A recently proposed summative gradient is used to maximize the structural similarity between the a priori and inverted models. We first demonstrate the methodology, followed by a synthetic fault model example to confirm its validity. Monte Carlo tests and uncertainty tests further illustrate the stability and practicality of the method. This method is easy to implement, and consequently produces an interpretable density model with geological consistency. Finally, we apply this method to the density modeling of the Chezhen Depression in the Bohai Bay Basin. Our work determines the distribution of deep Lower Paleozoic carbonate rocks and Archean buried hills with high-density characteristics. Our results are consistent with the existing formation mechanism of the “upper source-lower reservoir” type oil-gas targets.