Gravity Gradiometry Data Research Articles

Modeling Gravity Gradients from Surface Gravity Anomaly Data

Gravity gradients are useful to characterize near mass anomalies since they are much more sensitive to short wavelength anomalies than gravitational accelerations. Estimating gravity gradients from surface gravity data is based on numerical implementations of solutions to geodetic boundary value problem for determination of disturbing potential. One of methods to solve this problem is least-squares collocation which is basically based on data and a defined covariance function. This study deals with estimating gravity gradient tensor components from along track surface gravity anomaly data. The Least-Squares Collocation solution is based on a stationary local covariance function defined for the disturbing potential which allows upward continuation of the observations to a desired altitude. The modeling method is evaluated in using Earth Gravitational Model 2008(EGM2008) and real airborne gravity gradiometry data collected over Southern Texas, Oklahoma region. The results show that modeled gravity gradients estimated in both on the ground and at a certain altitude have basically good agreement with EGM08 gradients. Modeled gradients including horizontal components in the east-west direction exhibit some discrepancies in comparison to the airborne gradiometry data, which may be attributed to some measurement errors in the gradient data.

Joint inversion of full-tensor gravity gradiometry data based on source growing

Joint inversion of full-tensor gravity gradiometry data based on source growing

Joint Gramian inversion of gravity, magnetic and gravity gradient tensor data for the modelling of Mesoproterozoic iron oxide deposits, southeast Missouri, USA

SUMMARY Within the iron metallogenic province of southeast Missouri, USA, there are several mines that contain not only economic iron resources, magnetite and/or hematite, but also contain rare earth elements, copper and gold. An area including three major deposits, Pea Ridge, Bourbon and Kratz Spring, was selected for detailed modelling for the upper crustal magnetic susceptibility and density structures. For the study area, ground gravity and high-resolution airborne magnetic and gravity gradiometry data sets are available. An efficient and novel joint inversion algorithm for the simultaneous inversion of these multiple data sets is presented. The Gramian coupling constraint is used to correlate the reconstructed density and magnetic susceptibility models. The implementation relies on the structures of the sensitivity matrices and an efficient minimization algorithm to achieve significant reductions in the memory requirements and computational costs. Consequently, it is feasible to use a laptop computer for the inversion of multiple data sets, each containing thousands of data points, for the recovery of models on the study area, each including approximately one million model parameters. This is the first time that these multiple data sets have been simultaneously inverted for this area. The L1-norm stabilizer is used to provide compact and focused images of the ore deposits. For contrast, independent inversions of each data set are also discussed. In general, our results provide new insights about the concealed ore deposits in the Mesoproterozoic basement rocks of southeast Missouri. Both short- and long-wavelength anomalies exist in the recovered models; these provide a high-resolution image of the subsurface. The geometry and physical properties of the known deposits are determined very well. Additionally, some unknown concealed deposits are revealed; these could be economically valuable and should be considered in future geophysical and geological investigations.

2D seismic design on frontier basins using potential field data, a case study in the south of the eastern arm of the East African Rift System

AbstractThe 2D seismic design for a frontier basin was conducted from potential field data and available geological information using a case of a Block within the East African Rift System. The Block forms part of a southern extension of the eastern branch of the East African Rift System. The most significant structural features of the Block within this part of the rift were mapped using Airborne Gravity Gradiometry data along A, B and C sub‐basin boundaries. The Block covers a total area of more than 10,107 km2 in the central north of Tanzania. The 2D seismic lines were planned to intersect the major structures within the Block, in which a total of 1074 line kilometres from 18 seismic lines were proposed. The spatial sampling interval of 12.5 m with a minimum of two samples per wavelength was deemed adequate for a frontier basin, as would record dips well above 15° limit from the minimum target of 2000 m. The relevant source spacing may be suitable if tested, and the required energy has been recorded. These parameters, though may need refining depending on the field, are proposed for a good resolution imaging and wide bandwidth recording of complex geology for a frontier basin. The seismic design provided the basis for the economic evaluation of the possible survey to be undertaken for a frontier basin. The suggested parameters allow for the flexibility of inclusion or improvement in any subsequent study related to the seismic acquisition in a Block with similar characteristics.

Inversion of the Gravity Gradiometry Data by ResUnet Network: An Application in Nordkapp Basin, Barents Sea

The study and assessment of the subsurface density distribution are vital for mining and oil & gas exploration. This can be achieved by the three-dimensional (3D) inversion of the observed gravity and gravity gradiometry (GG) data. Due to the ill-posedness of the geophysical inverse problem, the nonuniqueness and instability of solutions represent the main difficulties in inversion. In recent years, convolutional neural networks, especially U-net technology, have found wide applications in image processing, recognition, and reconstruction. This paper proposes using this method for fast reconstruction of the subsurface density models based on the ResUnet technology. The developed new method was examined on two 3D synthetic gravity and gravity gradiometry datasets inversion. The results show that the ResUnet network can reconstruct the density anomaly with sharp boundaries and is robust to the noise, making the solution stable.

Joint focusing inversion of marine controlled-source electromagnetic and full tensor gravity gradiometry data

We have developed an approach for integrating the interdependent information of different geophysical methods to obtain a self-consistent geophysical model in offshore exploration. Electromagnetic (EM) and gravity data complement seismic data by providing information about the physical properties of prospective reservoir rocks. We have combined marine EM and gravity gradiometry geophysical data in joint inversion using a joint focusing stabilizer. The method enforces coupling between different physical models and simultaneously promotes focused images of the targets. We also consider the importance of using robust norms to analyze data collected by marine controlled-source EM surveys. The practical effectiveness of the developed method is illustrated by a case study of integrating and imaging marine multiphysics data collected in the Nordkapp Basin, Barents Sea, Norway.

Combined Compact and Smooth Inversion for Gravity and Gravity Gradiometry Data

3-D inversion for gravity data is of great significance in geophysical quantitative interpretation. However, due to the complexity of the density distribution on the subsurface and nonuniqueness of inverse problems, the classical inversion still has many shortages. The smooth constrained inversion results in redundant structures, whereas the results of the compact inversion are too focused, and excessively rely on the choice of target density parameters. In view of the above issues, we develop a 3-D combined compact and smooth inversion for gravity and gravity gradient data. The objective function is built by the combination of the minimization of field source volume and the misfit between observed and predicted data. The prior information is treated as the “target density” in the inversion process. Furthermore, in order to solve the problem of overreliance on “target density,” we improve a 3-D gravity inversion algorithm where the model constraints include the combination of compact and smooth factors. Model tests show the method can better recover the source distribution when the parameter of target density is not given. Also, we make a comparative analysis of the inversion results of different gradient components and conclude that the inversion results of the gradient data <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$g_{xy}$ </tex-math></inline-formula> are better than those of other gradient components. Finally, we apply the method to the real gravity data. The inferred results of the anomalous rock mass are consistent with the previous geologic knowledge.

Joint Nonlinear Inversion of Full Tensor Gravity Gradiometry Data and Its Parallel Algorithm

Geophysical joint inversion is more frequently applied to deep crust probes. For the potential field data, it requires the introduction of large-scale observed data and sensitivity matrices. Massive matrix-vector multiplications occur during iterations, and the obtained data cannot be effectively interpreted by merely using desktop computers. To improve the resolution and the computing ability of inversion, we here propose the parallel joint nonlinear inversion of full tensor gravity gradiometry data. As the inversion is affected by linear searches, it is associated with certain classical computing performance issues. Hence, we addressed the memory and efficiency limitations, which are caused by very large calculation volumes. Also, we performed a quantitative and comprehensive feasibility analysis of parallel computing. Then, we identified the main factor influencing the inversion performance and clarified the correspondence between the cell number and the memory. A parallel inversion solution was proposed via graphics processing unit (GPU) based on the sensitivity matrix compression. The data tests demonstrated that inversion has antinoise property and that it can obtain accurate underground density distributions. Also, the parallel solution was found to be suitable for inverting cells at the million cell scale and greater because of its ability of acceleration and matrix compression. A design pattern was applied for gravity or magnetic anomaly inversion of 100 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times 100\times20$ </tex-math></inline-formula> cells, and the run time was less than 1 min. Overall, we believe that the proposed solution can help implement massive potential field data inversions and promote the application of the parallel technique in other inversion research.

The Advantage Analysis of 3-D Inversion of Airborne Gravity Gradiometry Data With Larger Sampling Interval

Airborne gravity gradiometry is an effective tool for its high efficiency and sensitivity to the interesting buried targets, which has been increasingly introduced in mineral and petroleum exploration. When compared to gravimetry, full tensor gradient (FTG) measurements provide higher resolution and signal-to-noise ratio. In this article, we build and test models with different sampling intervals and compare the performances of individual components or their combinations in minimum structure inversion to evaluate the benefits of FTG combinations. As part of a theoretical study, the singular value spectrum (SVS) and depth-resolution plot (DRP) are examined to determine how much information and resolution different datasets provide in the underdetermined inverse problem. The synthetic examples show that integrating more components in inversion improves the resolution of the recovered model, and the inversion result of gravity or individual component cannot accurately restore the distribution of anomalous bodies. With the increasing sampling interval, joint inversion of FTG data still provides enough information corresponding to the source density distribution, and the limit survey interval is tested through models. In addition, we use a real survey over the Vinton dome as a case study and discover that <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {zz}}$ </tex-math></inline-formula> component fails to reconstruct the caprock model at coarse line spacing, whereas FTG combinations recover the acceptable geometry flawlessly. It also reflects the benefit of FTG combinations for inversion processing, which reduces the interference of measured noise on inversion results and allows for longer sampling intervals during the survey, effectively lowering the cost of an airborne survey and improving exploration efficiency

High-Resolution Cooperate Density-Integrated Inversion Method of Airborne Gravity and Its Gradient Data

Airborne (or satellite) gravity measurement is a commonly used remote sensing method to obtain the underground density distribution. Airborne gravity gradiometry data have a higher horizontal resolution to shallower causative sources than airborne gravity anomaly, so joint exploration of airborne gravity and its gradient data can simultaneously obtain the anomaly feature of sources with different depths. The most commonly used joint inversion method of gravity and its gradient data is the data combined method, which is to combine all the components into a data matrix as mutual constraints to reduce ambiguity and non-uniqueness. In order to obtain higher resolution results, we proposed a cooperate density-integrated inversion method of airborne gravity and its gradient data, which firstly carried out the joint inversion using cross-gradient constraints to obtain two density structures, and then fused two recovered models into a result through Fourier transform; finally, data combined joint inversion of airborne gravity, and gradient data were reperformed to achieve high-resolution density result using fused density results as a reference model. Compared to the data combined joint inversion method, the proposed cooperate density-integrated inversion method can obtain higher resolution and more accurate density distribution of shallow and deep bodies meanwhile. We also applied it to real data in the mining area of western Liaoning Province, China. The results showed that the depth of the skarn-type iron mine in the region is about 900–1300 m and gives a more specific distribution compared to the geological results, which provided reliable data for the next exploration plan.

Understanding the information content in gravity gradiometry data through constrained inversions for salt bodies

Gravity gradiometry inversion can provide important knowledge about a salt body and can assist in subsalt imaging. However, such inversions are faced with difficulties associated with the lack of response from the nil zone in which the salt density is nearly identical to that of the background sediments and weak signals from the deeper portion of the salt. It is well understood that such difficulties could be alleviated by incorporating prior information, such as the top of salt from seismic imaging and petrophysical data, into the inversions. How to effectively incorporate such prior information is still a challenge, and what level of increased knowledge such constrained inversions can provide remains to be understood. We have investigated and compared the additional knowledge provided by incorporating different forms of prior information, such as a top-of-salt surface and an expected density contrast model. These different types of information are incorporated through different strategies of constrained inversion, including an inversion with bound constraints on the density contrast, inversion after a reduction-to-binary process, and discrete-valued inversion. We apply these strategies first to synthetic gravity gradiometry data calculated from the SEG/EAGE salt body and evaluate the improvements to the recovered salt provided from successive imposition of increased prior information. We further apply the strategies to a set of marine gravity gradiometry data collected in the Gulf of Mexico and examine the additional knowledge gained from the imaging of the salt in the region. We find that much more valuable knowledge about the salt can be obtained with the right prior information imposed through an effective strategy, and we determine that such gravity gradiometry data contain information about the salt body at depths much greater than previously recognized.

Moho Depth Estimation Beneath Tibet From Satellite Gravity Data Based on a Condensation Approach

AbstractWe develop an algorithm for a Moho depth recovery from gravity and gravity gradiometry data and apply this method to estimate the Moho depth beneath the Tibetan Plateau. The basic idea of this algorithm is to describe mathematically the Moho depth undulations in terms of a condensation layer with respect to a mean Moho depth, instead of applying more commonly used isostatic compensation schemes. Expressions that functionally relate gravity field quantities with a (Moho) condensation layer are derived in spectral and spatial domains. The main advantage of this algorithm is that a functional relation between gravity field quantities and surface density anomalies, and consequently Moho depth undulations, has a linear form. The proposed algorithm is tested using satellite gravity and gravity gradiometry data. The Moho depth (taken with respect to the geoid surface) estimates obtained based on applying this algorithm are validated against global and regional seismic Moho results at the study area of Tibet. We also compare the result with the corresponding Moho depth estimates obtained by applying the Parker–Oldenburg and Vening Meinesz–Moritz (VMM) methods. The validation shows that results from all three gravimetric methods are similar, and they also closely agree with a regional seismic Moho model. Nevertheless, the VMM method and our algorithm in this comparison overperform the Parker–Oldenburg's method. The analysis of results also reveals that the newly developed algorithm provides better result (in terms of the RMS fit with a regional seismic Moho model) when applied for a Moho determination from gravity gradiometry instead of gravity data.

A new software for gravity gradiometry data forwarding and inversion

A new software has been developed specially for gravity gradiometry data forwarding and joint inversion. It is developed with hybrid programming technique and some powerful function libraries, including language of Python and C, Matplotlib, PyQt and so on. The software could help the users with graphical user interface, implement the data import/export and some management, the simple visualization in 2/3 dimension, modeling for gravity exploration data, and 3D density inversion. One of the advantages of this software is combining the popular development techniques to make the research of the forwarding and inversion easily, another one is simple secondary development, which allows the users to add their algorithms to the platform. The software is mainly used for the teaching and scientific research purposes, suitable for the geophysical scientists, engineers and graduate student.

Shallow velocity modelling – the application of high-resolution Full Tensor Gravity Gradiometry data and seismic tomography: a Permian Basin case study

Subsurface imaging from surface seismic reflection data is often complex as a result of issues related to the surface and the near surface including noise (ambient or otherwise), differing coupling of the geophones/geophone arrays and different coupling between the sources and mixed sources and the ground. With the diversity in land seismic exploration and increasingly complex near-surface conditions advanced modelling capabilities are being used for velocity model generation in processing. In this article the use of a multi-physics approach that does not suffer from velocity-depth ambiguity and provides a robust shallow velocity model is presented. This case study is taken from a project in the Permian Basin, USA. It presents the integration of Airborne Full Tensor Gravity Gradiometry (FTG) with tomography and the unique approach applied by the authors for modelling the near surface velocity structure integrated with surface seismic data.

Structural interpretation of the Beetaloo Sub-basin, NT from nonseismic geophysical data

The Beetaloo Sub-basin is known for its vast unconventional hydrocarbon resources even though it is relatively underexplored. There is reasonably good coverage of 2D seismic within the sub-basin which is used as the basis for most structural interpretations. However, seismic quality varies, and it is occasionally deteriorated by the presence of basalts from the Kalkarindji suite and the karstic nature of the Gum Ridge formation. Aeromagnetic data, constrained by petrophysical logs are used, to map faults in the basalts of the Kalkarindji suite and their lateral extent to the South and the East of the sub-basin. The same structural elements are identified in the full tensor gravity gradiometry data. The top of this unit is observed in the electrical conductivity profiles, derived from Tempest data, in the NW part of the eastern sub-basin.

Maintaining line of sight in oil and gas exploration: A case study from Mahakam Delta, Indonesia

In all exploration processes, the evaluation of basins, permits, and individual prospects changes over time with incremental availability and quality of data, technical effort expended, and knowledge gained. The NU prospect, located in the Mahakam Hilir PSC (East Kalimantan), is an example in which geologic chance of success (GCOS) predictions can change over time with increasing acquisition and availability of geophysical and geologic data and the studies done on them. We show how studies done on any one prospect or group of prospects can progressively increase/decrease the chance of at least one success in an exploration campaign of several wells. After a series of four wells was drilled in the PSC, which did not deliver commercial success, a change in approach was required to continue exploration. This included the acquisition of airborne gravity gradiometry data, initial trial prestack depth migration (PSDM) reprocessing of two key 1989 vintage 2D lines, acquisition of vintage well data from four Sambutan Field wells, acquisition of nine vintage 2D seismic lines over the field, and PSDM reprocessing of the nine 2D seismic lines. All data were then integrated to build a new geologic model. As a result, the NU prospect GCOS progressively moved from less than 10% to nearly 40%.

Posterror Compensation of Moving-Base Rotating Accelerometer Gravity Gradiometer

Mounting requirements of a rotating accelerometer gravity gradiometer (RAGG) beyond the art of manufacture, the RAGG is susceptible to the motion of itself. Motion error is a main source of error in airborne gravity gradiometry data. This study presented a posterror compensation method, which consists of postmotion error compensation and post-self-gradient compensation. The motion error and self-gradients are compensated before that the combined output of the four accelerometers is quadrature amplitude demodulated. The motion error compensation is based on the RAGG analytical model; motion response of the RAGG (namely, motion error) is related well to the motion of the RAGG, independent of the gravitational gradient response; recording the motion status of the RAGG, with least squares regression method and the RAGG analytical model, the motion response of the RAGG are separated and removed. RAGG numerical simulation experiment results show that the postmotion error compensation method is feasible, and its limit accuracy could reach 0.5 E/√Hz.

Focusing iterative migration of gravity gradiometry data acquired in the Nordkapp Basin, Barents Sea

ABSTRACTGeological interpretation based on gravity gradiometry data constitutes a very challenging problem. Rigorous 3D inversion is the main technique used in quantitative interpretation of the gravity gradiometry data. An alternative approach to the quantitative analysis of the gravity gradiometry data is based on 3D smooth potential field migration. This rapid imaging approach, however, has the shortcomings of providing smooth images since it is based on direct integral transformation of the observed gravity tensor data. Another limitation of migration transformation is related to the fact that, in a general case, the gravity data generated by the migration image do not fit the observed data well. In this paper, we describe a new approach to rapid imaging that allows us to produce the density distribution which adequately describes the observed data and, at the same time, images the structures with anomalous densities having sharp boundaries. This approach is based on the basic theory of potential field migration with a focusing stabilizer in the framework of regularized scheme, which iteratively transfers the observed gravity tensor field into an image of the density distribution in the subsurface formations. The results of gravity migration can also be considered as an a priori model for conventional inversion subsequently. We demonstrate the practical application of migration imaging using both synthetic and real gravity gradiometry data sets acquired for the Nordkapp Basin in the Barents Sea.

3-D joint inversion of seismic waveform and airborne gravity gradiometry data

SUMMARYSeismic full waveform inversion (FWI) is a robust velocity model building technique for hydrocarbon exploration. However, the density reconstruction within the framework of multiparameter FWI leads to more degrees of freedom in the parametrization, and the sensitivity of the inversion change significantly from velocity to density, thereby increasing the ill-posedness of the inverse problem. Gravity gradiometry data inversion is an effective method for resolving density distribution. Combining gravity gradiometry data in FWI could alleviate the non-linearity of the inversion by contributing additional density information for the velocity model building. I develop a 3-D joint seismic waveform and gravity gradiometry inversion method for estimating the velocity and density distribution in the subsurface. The method alternatingly minimizes the waveform and gravity gradiometry misfit. The cross-gradient constraint is applied to enhance the structural similarity between the density and velocity models. The effectiveness of the joint inversion algorithm is demonstrated by a 3-D checkerboard model and 3-D SEAM model. Synthetic examples demonstrate that the joint inversion can improve the image quality in geologically complex areas. A case study from the South China Sea shows that the joint inversion improves the velocity and density solutions compared to a standalone seismic FWI. The joint inversion results are consistent with the pre-stack depth migration section and the shape of the salt body is well resolved.

Targeting Geothermal Exploration Using Airborne Multi-geophysics, Kutcharo Caldera, Teshikaga Area

Multiple geophysical techniques have been applied to geothermal exploration within the Teshikaga area. The three-dimensional inversion of HeliFalcon® airborne gravity gradiometry (AGG) data has enabled a detailed interpretation of subsurface features. The vertically elongated high-density anomalies beneath lava domes located near Wakoto Peninsula and Mt. Atosanupuri are interpreted as subsurface intrusive bodies, while low-density anomalous feature to the depth represents the Kutcharo caldera structure, which was filled with large scale of low-density pyroclastic materials. Helitem® electromagnetic data acquired in combination with the AGG data revealed a widespread conductive anomaly west of Mt. Atosanupuri, which may represent the cap rocks to a geothermal reservoir. The distribution of a low magnetic intensity zone matches that of a low-resistivity zone, suggesting that magnetite degradation and demagnetization possibly occur, most likely caused by hydrothermal activities. Integrated interpretation of airborne gravity gradiometer, electromagnetic and magnetic data helps with identification of prospective areas and planning of a drilling program for the development of geothermal energy with greater precision.