Gravity Gradiometry Data Research Articles

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

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.

3D inversion of airborne gravity gradiometry data for the Budgell Harbour Stock, Newfoundland: A case history using a probabilistic approach

We have studied the Mesozoic Budgell Harbour Stock, a gabbroic intrusion in north-central Newfoundland, Canada, using 3D inversion of airborne gravity gradiometry data based on a probabilistic inversion method. Significantly, differences were observed between the results when inverting the single [Formula: see text] component and when inverting the 5C combination. We also found that the [Formula: see text] model failed to reproduce the long-wavelength signals from other components, whereas the model recovered from five components accommodated all of the signals from all of the components. To estimate the influence of long-wavelength signals from targets other than the intrusion, such as deeper bodies or large-scale terrain variations, inversion tests are performed on a synthetic model. The inversion results for the synthetic example indicate that the joint inversion of five components is more sensitive to long-wavelength signals, which can generate spurious structures to fit all of the signals from the five components. In contrast, the [Formula: see text] model is less affected by the long-wavelength signals and thus tends to produce a stable solution, despite failing to incorporate all of the long-wavelength signals from the tensor data. We found that gravity gradiometry data could be used to delineate the intrusion within this study area, which is also consistent with the susceptibility model recovered from inversion of aeromagnetic data and with results from a previous geophysical study. Moreover, the differences between the [Formula: see text] model and the 5C model may reflect the long-wavelength signals in the gravity gradiometry data.

3D density inversion of gravity gradiometry data with a multilevel hybrid parallel algorithm

The density inversion of gravity gradiometry data has attracted considerable attention; however, in large datasets, the multiplicity and low depth resolution as well as efficiency are constrained by time and computer memory requirements. To solve these problems, we improve the reweighting focusing inversion and probability tomography inversion with joint multiple tensors and prior information constraints, and assess the inversion results, computing efficiency, and dataset size. A Message Passing Interface (MPI)-Open Multi-Processing (OpenMP)-Computed Unified Device Architecture (CUDA) multilevel hybrid parallel inversion, named Hybrinv for short, is proposed. Using model and real data from the Vinton Dome, we confirm that Hybrinv can be used to compute the density distribution. For data size of 100×100×20, the hybrid parallel algorithm is fast and based on the run time and scalability we infer that it can be used to process the large-scale data.

Joint inversion of gravity gradiometry and magnetic data using Gramian structural constraints: A case study from the McFaulds Lake survey, Ontario

Abstract Potential field data form an important frontline exploration tool thanks to the modern-day airborne platforms capable of collecting large amounts of data over large areas. Interpretation of these data using a 3D inversion is still a challenging problem due to the large amount of data and the need to discretize the inversion volume into a huge number of elements.

Applying laterally varying density corrections to ground gravity and airborne gravity gradiometry data: a case study from the Bathurst Mining Camp

The influence of topography on gravity and gravity gradiometry measurements is profound and should be minimized prior to geological interpretation. The standard way of minimizing these effects is through the computation of a terrain correction. Terrain corrections require two inputs: topography and density. Often, geology and topography are inextricably intertwined: topography is caused by a change in geology. In geologic environments where there is a structural and (or) stratigraphic control on the near-surface mass distribution, using a single density value in the corrections leads to removal of the topographic effect of rocks having the chosen density. Any remaining gravity signal that correlates with topography is providing geological information. If the objective is to produce a gravity map with minimal topographic signal, then a regionally variable density correction is a means of compensating for this effect. In this paper, we demonstrate how to apply a spatially variable density correction using ground gravity and airborne gravity gradiometry data for the geologically complex Bathurst Mining Camp, northern New Brunswick, Canada. Ground gravity and airborne full tensor gravity gradiometry measurements are subdivided into a series of domains on the basis of the underlying tectonostratigraphic group. Terrain and Bouguer corrections are calculated for each domain using representative density values obtained from drill core and surface sampling throughout the Bathurst Mining Camp. The output from the spatially variable density correction is then compared with previous maps. Overall, the differences are subtle, but the spatially variably density allows for isolated anomalies to be better resolved.

Regional gravity field recovery of the void areas using SGG-derived surface residual gravity disturbances based on least-squares collocation: a case study in Iran

Objective of this paper is regional gravity field modelling of the Earth combining surface gravity disturbances and satellite gravity gradiometry (SGG) data based on the least-squares collocation (LSC) over the void areas in Iran, where the existing gravity data are not intensified or available. The gravity disturbances are obtained at minimum geocentric sphere, which is inside the topographic masses by joint inversion of the four high-accuracy components (Vxx, Vyy, Vzz, Vxz) of the GOCE SGG data using second derivatives of the Hotine integral. The GOCE-only global geopotential model (GGM) GO_CONS_GCF_2_TIM_R5 up to degree and order 60 is applied to reduce the effect of the omitted distant-zone, which is restored after calculation. The residual terrain model (RTM) is removed to estimate the effect of omission error of the GGM and provide mass-free space outside the boundary surface. The GOCE-based gravity disturbances at minimum geocentric sphere are continued upward on the Earth's surface based on planar approximation of the Poisson integral and subtracted from terrestrial gravity measurements to compute the residual gravity disturbances. The surface residual gravity disturbances are gridded in different cell-sizes according to the distribution of input gravity data and the locations of the empty cells that represent the void areas are determined. The height-uncorrelated residual values are applied to predict the residual gravity disturbance for every empty cell based on the LSC method using analytical local covariance function. The calculated results yielded an improvement of about 18.1% to 24.6% in gravity field recovery compared to the only RTM-corrected GGM-based solutions for two selected test areas in Iran.

Improved Imaging of the Subsurface Geology in the Mowla Terrace, Canning Basin using Gravity Gradiometry Data

A study was undertaken to test whether it is possible to map basement configuration and sedimentary horizons from the gravity gradiometry (AGG) data. This was within the EP431 Buru Energy permit on the Mowla Terrace in the onshore Canning Basin.By applying the Horizon Mapping method, using Energy Spectral Analysis Multi-Window-Test as described in the Methodology section (ESA-MWT), to AGG data, we conducted a test study on a narrow 8km long swath along 2D seismic traverse HCG-300, and at three wells: Pictor -1, Pictor-2 and Pictor East-1, with three additional wells located nearby.ESA-MWT was applied to gridded Bouguer and tensor gravity data. The ESA-MWT procedure was conducted at stations 1km apart. At each station, multiple spectra were computed over incrementally increasing windows. For each spectrum, the depth was interpreted and plotted versus window size, and from these graphs, multiple Depth-Plateaus were detected at each station. These Depth-Plateaus correspond to density contrasts within the sediments and the underlying basement. These were then laterally merged with those from adjacent stations to form density interfaces. The results were validated with seismic and the litho-stratigraphy from well data which showed a good correlation with the tops of several sedimentary formations and intra-formational lithological boundaries. Ten density interfaces were mapped: Top Precambrian Basement, Top Nambeet Formation, Intra-Willara Interface, Top Acacia Sandstone, Top Willara Formation, Intra-Goldwyer Interface, Top Goldwyer Formation, Top Nita Formation, Intra-Tandalgoo Group Interface and Intra-Tandalgoo Group Interface.The geological model built along the Test Profile from interpretation of the AGG data shows good correlation with the wells and seismic data.

Inversion of airborne geophysics over the DO-27/DO-18 kimberlites — Part 1: Potential fields

The Tli Kwi Cho (TKC) kimberlite complex contains two pipes, called DO-27 and DO-18, which were discovered during the Canadian diamond exploration rush in the 1990s. The complex has been used as a testbed for ground and airborne geophysics, and an abundance of data currently exist over the area. We have evaluated the historical and geologic background of the complex, the physical properties of interest for kimberlite exploration, and the geophysical surveys. We have carried out 3D inversion and joint interpretation of the potential field data. The magnetic data indicate high susceptibility at DO-18, and the magnetic inversion maps the horizontal extent of the pipe. DO-27 is more complicated. The northern part is highly magnetic and is contaminated with remanent magnetization; other parts of DO-27 have a low susceptibility. Low densities, obtained from the gravity and gravity gradiometry data, map the horizontal extents of DO-27 and DO-18. We combine the 3D density contrast and susceptibility models into a single geologic model that identifies three distinct kimberlite rock units that agree with drilling data. In further research, our density and magnetic susceptibility models are combined with information from electromagnetic data to provide a multigeophysical interpretation of the TKC kimberlite complex.

Adaptive multinary inversion of gravity and gravity gradiometry data

We have developed a novel approach for inversion of gravity and gravity gradiometry data based on multinary transformation of the model parameters. This concept is a generalization of binary density inversion to the models described by any number of discrete model parameters. The multinary inversion makes it possible to explicitly exploit the sharp contrasts of the density between the host media and anomalous targets in the inversion of gravity and gravity gradiometry data. In the framework of the multinary inversion method, we use the given values of density and error functions to transform the density distribution into the desired step-function distribution. To accommodate a possible deviation of the densities from the fixed discrete values, we develop an adaptive technique for selecting the corresponding standard deviations, guided by the inversion process. The novel adaptive multinary inversion algorithm is demonstrated to be effective in determining the shape, location, and densities of the anomalous targets. We find that this method can be effectively applied for the inversion of the full tensor gravity gradiometry (FTG) data computer simulated for the SEG salt density model and for the field FTG data collected in the Nordkapp Basin, Barents Sea.

Comparison of methods for a 3-D density inversion from airborne gravity gradiometry

In this study, we apply Tikhonov’s regularization algorithm for a 3-D density inversion from the gravity-gradiometry data. To reduce the non-uniqueness of the inverse solution (carried out without additional information from geological evidence), we implement the depth-weighting empirical function. However, the application of an empirical function in the inversion equation brings the bias problem of the regularization factor when a traditional Tikhonov’s algorithm is applied. To solve the bias problem of regularization factor selection, we present a standardized solution that comprises two parts for solving a 3-D constrained inversion equation, specifically the linear matrix transformation and Tikhonov’s regularization algorithm. Since traditional regularization techniques become numerically inefficient when dealing with large number of data, we further apply methods which include the Simultaneous Iterative Reconstruction Technique (SIRT) and the wavelet compression combined with Least Squares QR-decomposition (LSQR). In our simulation study, we demonstrate that SIRT as well as the wavelet compression plus LSQR algorithm improve the computation efficiency, while provide results which closely agree with that obtained from applying Tikhonov’s regularization. In particular, the algorithm of wavelet compression plus LSQR shows the best computing efficiency, because it combines the advantages of coefficients compression of big matrix and fast solution of sparse matrix. Similar findings are confirmed from the vertical gravity gradient data inversion for detecting potential deposits at the Kauring (near Perth, Western Australia) testing site.

Multi-GPU parallel algorithm design and analysis for improved inversion of probability tomography with gravity gradiometry data

In this paper, we make a study on the inversion of probability tomography (IPT) with gravity gradiometry data at first. The space resolution of the results is improved by multi-tensor joint inversion, depth weighting matrix and the other methods. Aiming at solving the problems brought by the big data in the exploration, we present the parallel algorithm and the performance analysis combining Compute Unified Device Architecture (CUDA) with Open Multi-Processing (OpenMP) based on Graphics Processing Unit (GPU) accelerating. In the test of the synthetic model and real data from Vinton Dome, we get the improved results. It is also proved that the improved inversion algorithm is effective and feasible. The performance of parallel algorithm we designed is better than the other ones with CUDA. The maximum speedup could be more than 200. In the performance analysis, multi-GPU speedup and multi-GPU efficiency are applied to analyze the scalability of the multi-GPU programs. The designed parallel algorithm is demonstrated to be able to process larger scale of data and the new analysis method is practical.

A GOCE only gravity model GOSG01S and the validation of GOCE related satellite gravity models

We compile the GOCE-only satellite model GOSG01S complete to spherical harmonic degree of 220 using Satellite Gravity Gradiometry (SGG) data and the Satellite-to-Satellite Tracking (SST) observations along the GOCE orbit based on applying a least-squares analysis. The diagonal components (Vxx, Vyy, Vzz) of the gravitational gradient tensor are used to form the system of observation equations with the band-pass ARMA filter. The point-wise acceleration observations (ax, ay, az) along the orbit are used to form the system of observation equations up to the maximum spherical harmonic degree/order 130. The analysis of spectral accuracy characteristics of the newly derived gravitational model GOSG01S and the existing models GOTIM04S, GODIR04S, GOSPW04S and JYY_GOCE02S based on their comparison with the ultra-high degree model EIGEN-6C2 reveals a significant consistency at the spectral window approximately between 80 and 190 due to the same period SGG data used to compile these models. The GOCE related satellite gravity models GOSG01S, GOTIM05S, GODIR05S, GOTIM04S, GODIR04S, GOSPW04S, JYY_GOCE02S, EIGEN-6C2 and EGM2008 are also validated by using GPS-leveling data in China and USA. According to the truncation at degree 200, the statistic results show that all GGMs have very similar differences at GPS-leveling points in USA, and all GOCE related gravity models have better performance than EGM2008 in China. This suggests that all these models provide much more information on the gravity field than EGM2008 in areas with low terrestrial gravity coverage. And STDs of height anomaly differences in China for the selected truncation degrees show that GOCE has improved the accuracy of the global models beyond degree 90 and the accuracies of the models improve from 24 cm to 16 cm. STDs of geoid height differences in USA show that GOSG01S model has best consistency comparing with GPS-leveling data for the frequency band of the degree between 20 and 160.

A fast interpretation method of gravity gradiometry data based on magnetic dipole localization

In this paper, we proposed a fast interpretation method for gravity gradiometry data, based on the magnetic dipole localization method. It could automatically and rapidly locate the horizontal and vertical positions of gravity targets without prior information. This method was successfully tested on synthetic data. Compared with gradient ratio method (tilt-depth) and Euler deconvolution, our method provided good performance in the gravity gradiometry data with high noise levels and superimposed fields. Point selection was processed among the inversion results to improve the resolution of our method. Statistical analysis and Gaussian fitting were also used to improve the stability and accuracy of the calculation. Finally, we applied this algorithm to gravity gradiometry data over Vinton Dome; the results are consistent with previous research in this area.

Adaptive filtering of GOCE-derived gravity gradients of the disturbing potential in the context of the space-wise approach

Filtering and signal processing techniques have been widely used in the processing of satellite gravity observations to reduce measurement noise and correlation errors. The parameters and types of filters used depend on the statistical and spectral properties of the signal under investigation. Filtering is usually applied in a non-real-time environment. The present work focuses on the implementation of an adaptive filtering technique to process satellite gravity gradiometry data for gravity field modeling. Adaptive filtering algorithms are commonly used in communication systems, noise and echo cancellation, and biomedical applications. Two independent studies have been performed to introduce adaptive signal processing techniques and test the performance of the least mean-squared (LMS) adaptive algorithm for filtering satellite measurements obtained by the gravity field and steady-state ocean circulation explorer (GOCE) mission. In the first study, a Monte Carlo simulation is performed in order to gain insights about the implementation of the LMS algorithm on data with spectral behavior close to that of real GOCE data. In the second study, the LMS algorithm is implemented on real GOCE data. Experiments are also performed to determine suitable filtering parameters. Only the four accurate components of the full GOCE gravity gradient tensor of the disturbing potential are used. The characteristics of the filtered gravity gradients are examined in the time and spectral domain. The obtained filtered GOCE gravity gradients show an agreement of 63–84 mEotvos (depending on the gravity gradient component), in terms of RMS error, when compared to the gravity gradients derived from the EGM2008 geopotential model. Spectral-domain analysis of the filtered gradients shows that the adaptive filters slightly suppress frequencies in the bandwidth of approximately 10–30 mHz. The limitations of the adaptive LMS algorithm are also discussed. The tested filtering algorithm can be connected to and employed in the first computational steps of the space-wise approach, where a time-wise Wiener filter is applied at the first stage of GOCE gravity gradient filtering. The results of this work can be extended to using other adaptive filtering algorithms, such as the recursive least-squares and recursive least-squares lattice filters.

DEM sourcing guidelines for computing 1 Eö accurate terrain corrections for airborne gravity gradiometry

In this paper we investigate digital elevation model (DEM) sourcing requirements to compute gravity gradiometry terrain corrections accurate to 1Eötvös (Eö) at observation heights of 80m or more above ground. Such survey heights are typical in fixed-wing airborne surveying for resource exploration where the maximum signal-to-noise ratio is sought. We consider the accuracy of terrain corrections relevant for recent commercial airborne gravity gradiometry systems operating at the 10Eö noise level and for future systems with a target noise level of 1Eö. We focus on the requirements for the vertical gradient of the vertical component of gravity (Gdd) because this element of the gradient tensor is most commonly interpreted qualitatively and quantitatively.Terrain correction accuracy depends on the bare-earth DEM accuracy and spatial resolution. The bare-earth DEM accuracy and spatial resolution depends on its source. Two possible sources are considered: airborne LiDAR and Shuttle Radar Topography Mission (SRTM). The accuracy of an SRTM DEM is affected by vegetation height. The SRTM footprint is also larger and the DEM resolution is thus lower. However, resolution requirements relax as relief decreases. Publicly available LiDAR data and 1arc-second and 3arc-second SRTM data were selected over four study areas representing end member cases of vegetation cover and relief.The four study areas are presented as reference material for processing airborne gravity gradiometry data at the 1Eö noise level with 50m spatial resolution. From this investigation we find that to achieve 1Eö accuracy in the terrain correction at 80m height airborne LiDAR data are required even when terrain relief is a few tens of meters and the vegetation is sparse. However, as satellite ranging technologies progress bare-earth DEMs of sufficient accuracy and resolution may be sourced at lesser cost. We found that a bare-earth DEM of 10m resolution and 2m accuracy are sufficient for achieving 1Eö accuracy in the terrain correction independent of relief or vegetation cover. For AGG systems operating at greater noise levels the 3arc-second SRTM is adequate for areas having tens of meters of relief and sparse vegetation and even for areas of greater relief and sparse vegetation if a constant elevation survey is flown at 80m above terrain peak.

Magnetic and Gravity Gradiometry Framework for Mesoproterozoic Iron Oxide-Apatite and Iron Oxide-Copper-Gold Deposits, Southeast Missouri

High-resolution airborne magnetic and gravity gradiometry data provide the geophysical framework for evaluating the exploration potential of hidden iron oxide deposits in Mesoproterozoic basement rocks of southeast Missouri. The data are used to calculate mineral prospectivity for iron oxide-apatite (IOA) ± rare earth element (REE) and iron oxide-copper-gold (IOCG) deposits. Results delineate the geophysical footprints of all known iron oxide deposits and reveal several previously unrecognized prospective areas. The airborne data are also inverted to three-dimensional density and magnetic susceptibility models over four concealed deposits at Pea Ridge (IOA ± REE), Boss (IOCG), Kratz Spring (IOA), and Bourbon (IOCG). The Pea Ridge susceptibility model shows a magnetic source that is vertically extensive and traceable to a depth of greater than 2 km. A smaller density source, located within the shallow Precambrian basement, is partly coincident with the magnetic source at Pea Ridge. In contrast, the Boss models show a large (625-m-wide), vertically extensive, and coincident dense and magnetic stock with shallower adjacent lobes that extend more than 2,600 m across the shallow Precambrian paleosurface. The Kratz Spring deposit appears to be a smaller volume of iron oxides and is characterized by lower density and less magnetic rock compared to the other iron deposits. A prospective area identified south of the Kratz Spring deposit shows the largest volume of coincident dense and nonmagnetic rock in the subsurface, and is interpreted as prospective for a hematite-dominant lithology that extends from the top of the Precambrian to depths exceeding 2 km. The Bourbon deposit displays a large bowl-shaped volume of coincident high density and high-magnetic susceptibility rock, and a geometry that suggests the iron mineralization is vertically restricted to the upper parts of the Precambrian basement. In order to underpin the evaluation of the prospectivity and three-dimensional models, an extensive statistical summary of density and apparent magnetic susceptibility measurements is presented that includes data on several hundred samples taken from the deposits, altered wall rocks, and unaltered country rocks.

Fast 3D inversion of airborne gravity-gradiometry data using Lanczos bidiagonalization method

We developed a new fast inversion method for to process and interpret airborne gravity gradiometry data, which was based on Lanczos bidiagonalization algorithm. Here, we describe the application of this new 3D gravity gradiometry inversion method to recover a subsurface density distribution model from the airborne measured gravity gradiometry anomalies. For this purpose, the survey area is divided into a large number of rectangular cells with each cell possessing a constant unknown density. It is well known that the solution of large linear gravity gradiometry is an ill-posed problem since using the smoothest inversion method is considerably time consuming. We demonstrate that the Lanczos bidiagonalization method can be an appropriate algorithm to solve a Tikhonov solver time cost function for resolving the large equations within a short time. Lanczos bidiagonalization is designed to make the very large gravity gradiometry forward modeling matrices to become low-rank, which will considerably reduce the running time of the inversion method. We also use a weighted generalized cross validation method to choose the appropriate Tikhonov parameter to improve inversion results. The inversion incorporates a model norm that allows us to attain the smoothing and depth of the solution; in addition, the model norm counteracts the natural decay of the kernels, which concentrate at shallow depths. The method is applied on noise-contaminated synthetic gravity gradiometry data to demonstrate its suitability for large 3D gravity gradiometry data inversion. The airborne gravity gradiometry data from the Vinton Salt Dome, USE, were considered as a case study. The validity of the new method on real data is discussed with reference to the Vinton Dome inversion result. The intermediate density values in the constructed model coincide well with previous results and geological information. This demonstrates the validity of the gravity gradiometry inversion method.

Feasibility and Limitations of Void Detection Using Gravity Gradiometry

Detecting and characterizing near-surface voids is a long-standing problem in near-surface geophysics primarily because of the low signal-to-noise ratio due to the typically small sizes of these targets. Anticipated advances in gravity gradiometry instrumentation and data acquisition may provide the improved resolution required to address these targets. In this paper, we investigate void detection using simulated full tensor gravity gradiometry data. We show through numerical simulations that low-altitude gravity gradiometry can observe signals from voids well above the modern instrument noise level. We develop a practical detection algorithm to determine the tunnel orientation and its location in the subsurface. The algorithm first finds the tunnel orientation through a tensor rotation and then solves for the tunnel location in the subsurface based on the directional vectors obtained from the rotated tensor data. We use this algorithm to study the feasibility and limitations of the gravity gradiometry technique in void detection. We conclude that the method can be effective in many practical scenarios.

How do submarines use gravity gradients to avoid collisions with underwater mountains?

Gravity gradiometers in use today have their origins in naval special warfare because they ensure safe navigation and accurate detection of underwater objects. Submarines rely on accurate detection of their surroundings, and gravity gradiometry is a passive technique that does not compromise the submarine's position because it is a technique that does not emit energy. However, the way submarines achieve collision avoidance has never been addressed. Using gravity gradiometry data in real time warns of the existence of an underwater mountain in a submarine's trajectory. The method does not require accurate positioning, extensive measuring over large areas, or a gravity-gradient map of the ocean bottom. The results of a study demonstrate how gravity gradiometry can be used effectively to detect anomalous mass in a trajectory quickly, without involving sophisticated processing or interpretation algorithms. For many years, geophysicists have known the original use of the modern gravity-gradiometry technique without going into the details.

Fast inversion of probability tomography with gravity gradiometry data based on hybrid parallel programming

Geophysical exploration generates a very large amount of data, which require special techniques to process meaningfully. This paper presents a modification of the inversion method of probability tomography and a practical application of the method for the joint inversion with multiple gravity gradiometry tensors. The depth-weighting matrix is introduced to increase the vertical resolution. The problems associated with choosing tensors are discussed. We combine the high-performance computing techniques, Message Passing Interface with Compute Unified Device Architecture, for hybrid programming to build a faster parallel program. In the synthetic model tests, it is found that the joint inversion with multiple tensors is superior to the classical algorithm with a single tensor for delineating the boundary of the adjacent geological bodies. The hybrid parallel program has a speedup of far more than 100, which is higher than the program using one parallel technique alone; thus, the program could be used for large-scale data. The parallel algorithm is applied to real geophysical exploration data from Vinton Dome and we obtained a good density result. Our algorithm is demonstrated to be reliable and feasible.