Integration of geophysical constraints for multilayer geometry refinements in 2.5D gravity inversion

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. G95-G106 ◽  
Author(s):  
Jian Xing ◽  
Tianyao Hao ◽  
Ya Xu ◽  
Zhiwei Li
Keyword(s):  
Gravity Data ◽  
Inequality Constraints ◽  
Real Data ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Sharp Condition ◽  
Estimated Parameters ◽  
Multiple Interfaces ◽  
Variation Function ◽  
Different Depths

We have explored the feasibility of estimating depths of multiple interfaces from gravity data. The strata are simulated by an aggregate of 3D rectangular prisms whose bottom depths are parameters to be estimated. In the inversion process, we have integrated geophysical constraints including the borehole information and the sharp condition described by the total variation function. The iterative residual function is also introduced to adjust the weighting of the estimated parameters so that layers of different depths have nearly equal likelihood for deviation. The inversion is processed by minimizing the Tikhonov parametric functional by the reweighted regularized conjugate gradient method. Inequality constraints are adopted to deal with the coupling of the interfaces. Synthetic tests show that such integration is conducive to restoring the multilayer depth distribution. Real data applications in Mariana confirm that the inversion method is effective in complex geologic settings in practice. We have also evaluated several issues that specifically deserve attention for obtaining satisfactory results in multilayer gravity inversion.

Three-dimensional gravity inversion using graph theory to delineate the skeleton of homogeneous sources

Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. G53-G66 ◽  
Author(s):  
Rodrigo Bijani ◽  
Cosme F. Ponte-Neto ◽  
Dionisio U. Carlos ◽  
Fernando J. S. Silva Dias
Keyword(s):  
Genetic Algorithm ◽  
Graph Theory ◽  
Minimum Spanning Tree ◽  
Gravity Data ◽  
A Priori ◽  
Three Dimensional ◽  
Real Data ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Dimensional Gravity

We developed a new strategy, based on graph theory concepts, to invert gravity data using an ensemble of simple point masses. Our method consisted of a genetic algorithm with elitism to generate a set of possible solutions. Each estimate was associated to a graph to solve the minimum spanning tree (MST) problem. To produce unique and stable estimates, we restricted the position of the point masses by minimizing the statistical variance of the distances of an MST jointly with the data-misfit function during the iterations of the genetic algorithm. Hence, the 3D spatial distribution of the point masses identified the skeleton of homogeneous gravity sources. In addition, our method also gave an estimation of the anomalous mass of the source. So, together with the anomalous mass, the skeleton could aid other 3D methods with promising geometric a priori parameters. Several tests with different values of regularizing parameter were made to bespeak this new regularizing strategy. The inversion results applied to noise-corrupted synthetic gravity data revealed that, regardless of promising starting models, the estimated distribution of point masses and the anomalous mass offered valuable information about the homogeneous sources in the subsurface. Tests on real data from a portion of Quadrilátero Ferrífero, Minas Gerais state, Brazil, were performed for complementary analysis of the proposed inversion method.

A method for inversion of 1D vertical soundings of gravity anomalies

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. G15-G23
Author(s):  
Andrea Vitale ◽  
Domenico Di Massa ◽  
Maurizio Fedi ◽  
Giovanni Florio
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Gravity Data ◽  
Finite Size ◽  
Gravity Anomalies ◽  
Real Data ◽  
Gravity Inversion ◽  
Chain Process ◽  
Potential Field Data ◽  
Gamma Density

We have developed a method to interpret potential fields, which obtains 1D models by inverting vertical soundings of potential field data. The vertical soundings are built through upward continuation of potential field data, measured on either a profile or a surface. The method assumes a forward problem consisting of a volume partitioned in layers, each of them homogeneous and horizontally finite, but with the density changing versus depth. The continuation errors, increasing with the altitude, are automatically handled by determining the coefficients of a third-order polynomial function of the altitude. Due to the finite size of the source volume, we need a priori information about the total horizontal extent of the volume, which is estimated by boundary analysis and optimized by a Markov chain process. For each sounding, a 1D inverse problem is independently solved by a nonnegative least-squares algorithm. Merging of the several inverted models finally yields approximate 2D or 3D models that are, however, shown to generate a good fit to the measured data. The method is applied to synthetic models, producing good results for either perfect or continued data. Even for real data, i.e., the gravity data of a sedimentary basin in Nevada, the results are interesting, and they are consistent with previous interpretation, based on 3D gravity inversion constrained by two gamma-gamma density logs.

Three‐dimensional gravity inversion using simulated annealing: Constraints on the diapiric roots of allochthonous salt structures

Geophysics ◽  
2001 ◽  
Vol 66 (5) ◽  
pp. 1438-1449 ◽  
Author(s):  
Seiichi Nagihara ◽  
Stuart A. Hall
Keyword(s):  
Simulated Annealing ◽  
Gulf Of Mexico ◽  
Gravity Data ◽  
A Priori ◽  
Gravity Inversion ◽  
Inversion Method ◽  
A Priori Information ◽  
Final Density ◽  
Smoothing Effects ◽  
Priori Information

In the northern continental slope of the Gulf of Mexico, large oil and gas reservoirs are often found beneath sheetlike, allochthonous salt structures that are laterally extensive. Some of these salt structures retain their diapiric feeders or roots beneath them. These hidden roots are difficult to image seismically. In this study, we develop a method to locate and constrain the geometry of such roots through 3‐D inverse modeling of the gravity anomalies observed over the salt structures. This inversion method utilizes a priori information such as the upper surface topography of the salt, which can be delineated by a limited coverage of 2‐D seismic data; the sediment compaction curve in the region; and the continuity of the salt body. The inversion computation is based on the simulated annealing (SA) global optimization algorithm. The SA‐based gravity inversion has some advantages over the approach based on damped least‐squares inversion. It is computationally efficient, can solve underdetermined inverse problems, can more easily implement complex a priori information, and does not introduce smoothing effects in the final density structure model. We test this inversion method using synthetic gravity data for a type of salt geometry that is common among the allochthonous salt structures in the Gulf of Mexico and show that it is highly effective in constraining the diapiric root. We also show that carrying out multiple inversion runs helps reduce the uncertainty in the final density model.

scholarly journals 3D Gravity Inversion with Correlation Image in Space Domain and Application to the Northern Sinai Peninsula

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Xu Zhang ◽  
Peng Yu ◽  
Jian Wang
Keyword(s):  
Density Distribution ◽  
Gravity Data ◽  
Descent Method ◽  
Steepest Descent Method ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Sinai Peninsula ◽  
Space Domain ◽  
Correlation Image ◽  
Starting Model

We present a 3D inversion method to recover density distribution from gravity data in space domain. Our method firstly employs 3D correlation image of the vertical gradient of gravity data as a starting model to generate a higher resolution image for inversion. The 3D density distribution is then obtained by inverting the correlation image of gravity data to fit the observed data based on classical inversion method of the steepest descent method. We also perform the effective equivalent storage and subdomain techniques in the starting model calculation, the forward modeling and the inversion procedures, which allow fast computation in space domain with reducing memory consumption but maintaining accuracy. The efficiency and stability of our method is demonstrated on two sets of synthetic data and one set of the Northern Sinai Peninsula gravity data. The inverted 3D density distributions show that high density bodies beneath Risan Aniza and low density bodies exist to the southeast of Risan Aniza at depths between 1~10 and 20 km, which may be originated from hot anomalies in the lower crust. The results show that our inversion method is useful for 3D quantitative interpretation.

Gravity data as a tool for detecting faults: In-depth enhancement of subtle Almada’s basement faults, Brazil

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. B59-B68 ◽  
Author(s):  
Valeria C. Barbosa ◽  
Paulo T. Menezes ◽  
João B. Silva
Keyword(s):  
Gravity Data ◽  
Synthetic Data ◽  
Normal Fault ◽  
Northeastern Brazil ◽  
Normal Faults ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Basement Faults ◽  
Depth Enhancement ◽  
Fault Displacement

We demonstrate the potential of gravity data to detect and to locate in-depth subtle normal faults in the basement relief of a sedimentary basin. This demonstration is accomplished by inverting the gravity data with the constraint that the estimated basement relief presents local abrupt faults and is smooth elsewhere. We inverted the gravity data from the onshore Almada Basin in northeastern Brazil, and we mapped several normal faults whose locations and plane geometries were already known from seismic imaging. The inversion method delineated well both the discontinuities with small or large slips and a sequence of step faults. Using synthetic data, we performed a systematic search of normal fault slips versus fault displacement depths to map the fault-detectable region in this space. This mapping helps to assess the ability of gravity inversion to detect normal faults. Mapping shows that normal faults with small [Formula: see text], medium (about [Formula: see text]), and large (about [Formula: see text]) vertical slips can be detected if the maximum midpoint depths of the fault planes are smaller than 1.8, 3.8, and [Formula: see text], respectively.

Clustering and constrained inversion of seismic refraction and gravity data for overburden stripping: Application to uranium exploration in the Athabasca Basin, Canada

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. B133-B146 ◽  
Author(s):  
Mehrdad Darijani ◽  
Colin G. Farquharson ◽  
Peter G. Lelièvre
Keyword(s):  
Gravity Data ◽  
Seismic Refraction ◽  
Real Data ◽  
Drill Hole ◽  
Gravity Inversion ◽  
Glacial Sediments ◽  
Athabasca Basin ◽  
Overburden Thickness ◽  
Uranium Exploration ◽  
Fuzzy C Means Clustering

Gravity signatures from features associated with the footprints of uranium deposits within the sandstones and basement of the Athabasca Basin are masked in the measured gravity by the contribution from glacial sediments (overburden), in particular by the variable thickness of the overburden. The 2D inversions of seismic refraction and gravity data are assessed as a means of reliably mapping overburden thickness, enabling the contribution to gravity from the overburden to be taken into account and density anomalies associated with deeper mineralization and alteration to be reconstructed through further inversion. Results show that independent inversion of seismic refraction data using the fuzzy c-means clustering method is able to determine the base of overburden well. Subsequent gravity inversion constrained by the overburden thickness reveals possible subtle density variations at depth, which could be associated with alteration in the sandstones associated with the uranium mineralization. Application of the seismic clustering inversion followed by constrained gravity inversion to both representative synthetic scenarios and real data from the Athabasca Basin, Canada, are considered. Drill-hole data show that the inversion results can predict the base of the overburden well, and there is an acceptable match between geologic information and possible alteration zones suggested by the inversions.

scholarly journals Density Structure of the Von Kármán Crater in the Northwestern South Pole-Aitken Basin: Initial Subsurface Interpretation of the Chang’E-4 Landing Site Region

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4445
Author(s):  
Chikondi Chisenga ◽  
Jianguo Yan ◽  
Jiannan Zhao ◽  
Qingyun Deng ◽  
Jean-Pierre Barriot
Keyword(s):  
Gravity Data ◽  
Landing Site ◽  
Gravity Inversion ◽  
Inversion Method ◽  
South Pole ◽  
Impact Cratering ◽  
Near Surface ◽  
Von Karman ◽  
Multiple Impact ◽  
Von Kármán

The Von Kármán Crater, within the South Pole-Aitken (SPA) Basin, is the landing site of China’s Chang’E-4 mission. To complement the in situ exploration mission and provide initial subsurface interpretation, we applied a 3D density inversion using the Gravity Recovery and Interior Laboratory (GRAIL) gravity data. We constrain our inversion method using known geological and geophysical lunar parameters to reduce the non-uniqueness associated with gravity inversion. The 3D density models reveal vertical and lateral density variations, 2600–3200 kg/m3, assigned to the changing porosity beneath the Von Kármán Crater. We also identify two mass excess anomalies in the crust with a steep density contrast of 150 kg/m3, which were suggested to have been caused by multiple impact cratering. The anomalies from recovered near surface density models, together with the gravity derivative maps extending to the lower crust, are consistent with surface geological manifestation of excavated mantle materials from remote sensing studies. Therefore, we suggest that the density distribution of the Von Kármán Crater indicates multiple episodes of impact cratering that resulted in formation and destruction of ancient craters, with crustal reworking and excavation of mantle materials.

scholarly journals 3D Gravity Inversion on Unstructured Grids

2021 ◽  
Vol 11 (2) ◽  
pp. 722
Author(s):  
Siyuan Sun ◽  
Changchun Yin ◽  
Xiuhe Gao
Keyword(s):  
Objective Function ◽  
Unstructured Grids ◽  
Gravity Data ◽  
Depth Resolution ◽  
Continuous Model ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Model Parameters ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering

Compared with structured grids, unstructured grids are more flexible to model arbitrarily shaped structures. However, based on unstructured grids, gravity inversion results would be discontinuous and hollow because of cell volume and depth variations. To solve this problem, we first analyzed the gradient of objective function in gradient-based inversion methods, and a new gradient scheme of objective function is developed, which is a derivative with respect to weighted model parameters. The new gradient scheme can more effectively solve the problem with lacking depth resolution than the traditional inversions, and the improvement is not affected by the regularization parameters. Besides, an improved fuzzy c-means clustering combined with spatial constraints is developed to measure property distribution of inverted models in both spatial domain and parameter domain simultaneously. The new inversion method can yield a more internal continuous model, as it encourages cells and their adjacent cells to tend to the same property value. At last, the smooth constraint inversion, the focusing inversion, and the improved fuzzy c-means clustering inversion on unstructured grids are tested on synthetic and measured gravity data to compare and demonstrate the algorithms proposed in this paper.

Adaptive learning 3D gravity inversion for salt-body imaging

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. I49-I57 ◽  
Author(s):  
Fernando J. S. Silva Dias ◽  
Valéria C. F. Barbosa ◽  
João B. C. Silva
Keyword(s):  
Adaptive Learning ◽  
Learning Strategy ◽  
Gravity Data ◽  
Density Contrast ◽  
Piecewise Constant Function ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Outer Loop ◽  
Bottom Depth ◽  
Geometric Elements

We have developed an iterative scheme for inverting gravity data produced by salt bodies with density contrasts relative to the sediments varying from positive to negative, crossing, in this way, the nil zone. Our inversion method estimates a 3D density-contrast distribution, through a piecewise constant function defined on a user-specified grid of cells. It consists of two nested iterative loops. The outer loop uses an adaptive learning strategy that starts with a coarse grid of cells, a set of first-guess geometric elements (axes and points) and the corresponding assigned density contrasts. From the second iteration on, this strategy refines the grid and automatically creates a new set of geometric elements (points only) and associated density contrasts. Each geometric element operates as the first-guess skeletal outline of a section of the salt body to be imaged. The inner loop estimates the 3D density-contrast distribution for the grid of cells and for the set of geometric elements defined in the outer loop. The outer loop allows for easy incorporation of prior geologic information about the lithologic units and automatic evolution of the prior information. The inner loop forces the estimated density contrast of each cell to be close either to a null or to a non-null prespecified value. The iteration stops when the geometries of the estimated salt bodies are invariant along successive iterations. We apply our method to synthetic gravity data produced by a homogeneous salt body embedded in heterogeneous sediments. We tested two geologic hypotheses about the real gravity data from Galveston Island salt dome, USA. In the first, the estimated salt body attains a maximum bottom depth of 5 km, whereas in the second hypothesis, it is shallower and discloses an overhang. Both solutions fit the data and are feasible geologically, so both hypotheses are acceptable.

scholarly journals Gravity inversion by means of growing bodies

Geophysics ◽  
2000 ◽  
Vol 65 (1) ◽  
pp. 95-101 ◽  
Author(s):  
Antonio G. Camacho ◽  
Fuensanta G. Montesinos ◽  
Ricardo Vieira
Keyword(s):  
Data Model ◽  
Gravity Data ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Positive Parameter ◽  
Mass Model ◽  
Regional Trend ◽  
Gran Canaria ◽  
Systematic Exploration ◽  
Anomalous Bodies

This paper presents a gravity inversion method for determining the volumes of bodies with pre‐established density contrasts. The method works step‐by‐step on a prismatic partition of the subsurface volume, expanding the anomalous bodies to fit the observed gravity values in a systematic exploration of model possibilities. The process is treated in a 3-D context; at the same time, it can determine a simple regional trend. Moreover, positive and negative density contrasts are simultaneously accepted. The solution is obtained by a double condition: (1) the 𝓁2-fitness to the observed gravity data (model fitness) and (2) the minimization of the total (weighted) anomalous mass (model smoothness). A positive parameter is used to balance the two minimization terms. The method is applied to a simulated example and also to a real example: the volcanic island of Gran Canaria (Canary Islands, Spain). In both cases, the results obtained show the possibilities of the method.

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