Gravity modeling for crustal-scale models of rifted continental margins using a constrained 3D inversion method

Geophysics ◽  
2019 ◽  
Vol 84 (4) ◽  
pp. G25-G39 ◽  
Author(s):  
Meixia Geng ◽  
J. Kim Welford ◽  
Colin G. Farquharson ◽  
Xiangyun Hu
Keyword(s):  
Weighting Function ◽  
Gravity Data ◽  
A Priori ◽  
Probabilistic Approach ◽  
Gravity Modeling ◽  
Inversion Method ◽  
Continental Margins ◽  
Linear Equality Constraints ◽  
Boundary Information ◽  
Regional Gravity

We have developed a new constrained inversion method that is based on a probabilistic approach for resolving crustal structure from regional gravity data. The smoothness of estimated structures is included in the inversion by using a model covariance matrix, and the sparse boundary information obtained from seismic data is incorporated in the inversion by using linear equality constraints. Moreover, constraints on the average anomalous densities expected for different crustal layers are applied instead of using a depth-weighting function. Bathymetric data and sediment thicknesses are included in the inversion by using an a priori model. Using the proposed method, model structures with sharp boundaries can be obtained while the existing boundary information and sparse seismic constraints are honored. We determine through a synthetic example and a real-world example that the proposed constrained inversion method is a valid tool for studying crustal-scale structures.

Highly efficient density inversion of gravity data using nonlinear density polynomial fitting

Geophysics ◽  
2021 ◽  
pp. 1-34
Author(s):  
Guoqing Ma ◽  
Zongrui Li ◽  
Lili Li ◽  
Taihan Wang
Keyword(s):  
Weighting Function ◽  
Gravity Data ◽  
Real Life ◽  
Density Variation ◽  
Density Change ◽  
Inversion Method ◽  
Density Inversion ◽  
Perspective View ◽  
Polynomial Fitting ◽  
Polynomial Coefficients

The density inversion of gravity data is commonly achieved by discretizing the subsurface into prismatic cells and calculating the density of each cell. During this process, a weighting function is introduced to the iterative computation to reduce the skin effect during the inversion. Thus, the computation process requires a significant number of matrix operations, which results in low computational efficiency. We have adopted a density inversion method with nonlinear polynomial fitting (NPF) that uses a polynomial to represent the density variation of prismatic cells in a certain space. The computation of each cell is substituted by the computation of the nonlinear polynomial coefficients. Consequently, the efficiency of the inversion is significantly improved because the number of nonlinear polynomial coefficients is less than the number of cells used. Moreover, because representing the density change of all of the cells poses a significant challenge when the cell number is large, we adopt the use of a polynomial to represent the density change of a subregion with fewer cells and multiple nonlinear polynomials to represent the density changes of all prism cells. Using theoretical model tests, we determine that the NPF method more efficiently recovers the density distribution of gravity data compared with conventional density inversion methods. In addition, the density variation of a subregion with 8 × 8 × 8 prismatic cells can be accurately and efficiently obtained using our cubic NPF method, which can also be used for noisy data. Finally, the NPF method was applied to real gravity data in an iron mining area in Shandong Province, China. Convergent results of a 3D perspective view and the distribution of the iron ore bodies were acquired using this method, demonstrating the real-life applicability of this method.

scholarly journals Basement Mapping of the Fucino Basin in Central Italy by ITRESC Modeling of Gravity Data

Geosciences ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 398
Author(s):  
Federico Cella ◽  
Rosa Nappi ◽  
Valeria Paoletti ◽  
Giovanni Florio
Keyword(s):  
Seismic Activity ◽  
Site Response ◽  
Gravity Data ◽  
A Priori ◽  
Central Italy ◽  
Gravity Anomalies ◽  
Gravity Modeling ◽  
Ground Shaking ◽  
Sedimentary Evolution ◽  
Fucino Basin

Sediments infilling in intermontane basins in areas with high seismic activity can strongly affect ground-shaking phenomena at the surface. Estimates of thickness and density distribution within these basin infills are crucial for ground motion amplification analysis, especially where demographic growth in human settlements has implied increasing seismic risk. We employed a 3D gravity modeling technique (ITerative RESCaling—ITRESC) to investigate the Fucino Basin (Apennines, central Italy), a half-graben basin in which intense seismic activity has recently occurred. For the first time in this region, a 3D model of the Meso-Cenozoic carbonate basement morphology was retrieved through the inversion of gravity data. Taking advantage of the ITRESC technique, (1) we were able to (1) perform an integration of geophysical and geological data constraints and (2) determine a density contrast function through a data-driven process. Thus, we avoided assuming a priori information. Finally, we provided a model that honored the gravity anomalies field by integrating many different kinds of depth constraints. Our results confirmed evidence from previous studies concerning the overall shape of the basin; however, we also highlighted several local discrepancies, such as: (a) the position of several fault lines, (b) the position of the main depocenter, and (c) the isopach map. We also pointed out the existence of a new, unknown fault, and of new features concerning known faults. All of these elements provided useful contributions to the study of the tectono-sedimentary evolution of the basin, as well as key information for assessing the local site-response effects, in terms of seismic hazards.

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 SIMULATION MODELLING IN THE STRUCTURAL GRAVITY PROSPECTING

2019 ◽  
pp. 38-48
Author(s):  
S. H. Anikeyev ◽  
S. M. Bahriy ◽  
B. B. Hablovskiy
Keyword(s):  
Cross Sections ◽  
Gravity Data ◽  
A Priori ◽  
Structural Type ◽  
Simulation Modelling ◽  
Gravity Modeling ◽  
Gravity Inversion ◽  
Density Structure ◽  
Data Modelling ◽  
Computer Technologies

In accordance with the purpose of geophysical exploration, the gravity data interpretation is aimed at prospecting mineral resources which is based on the study of the geological cross-section structure. The task of quantitative interpretation, which uses methods of gravity modeling and gravity inversion, is the modelling of a gravity field (gravity modeling) and of a density structure of geological environments (gravity inversion). The article presents the definition and steps of the gravity data modelling technique. This technique is based on the construction of an informal sequence of equivalent solutions. The technological and geological features of methods for modelling the density structure of complex geological environments are given; among them geological content, consistency with a priori data and the subordination of modelling to geological hypotheses are important. The topicality and methods of simulation modelling are outlined. The purpose of simulation modelling is to study the properties of gravity inversion in the general formulation, as well as to evaluate the degree of detail and reliability of the methods and technologies of gravity modelling, which claim to be an effective solution to geological problems. The example of structural simulation testing of the methods of informal sequence of equivalent solutions and its computer technologies shows that a complex interpretation of seismic and gravity measurements data enables the creation of detailed density models of structural cross-sections. The ways of increasing the veracity of gravity data modelling of structural cross-sections have been studied. It is revealed that the best approximation of the regional background is an inclined plane which approximates the observed field of gravity according to characteristic pickets over the research areas that are better studied. The increase in the veracity of modeling can also be achieved by rebuilding the near side zones in the structural type models in an interactive process of solving structural gravity inversion problems. Substantive modeling depends primarily on the experience of the interpreter since computer technologies for gravity modeling and gravity inversion are merely an interpretation tool.

scholarly journals 3D stochastic inversion of gravity data using cokriging and cosimulation

Geophysics ◽  
2010 ◽  
Vol 75 (1) ◽  
pp. I1-I10 ◽  
Author(s):  
Pejman Shamsipour ◽  
Denis Marcotte ◽  
Michel Chouteau ◽  
Pierre Keating
Keyword(s):  
Gravity Data ◽  
A Priori ◽  
Inversion Method ◽  
Geostatistical Techniques ◽  
Priori Information ◽  
Surface Geology ◽  
Synthetic Models ◽  
Secondary Variable ◽  
Good Agreement

A new application has been developed, based on geostatistical techniques of cokriging and conditional simulation, for the 3D inversion of gravity data including geologic constraints. The necessary gravity, density, and gravity-density covariance matrices are estimated using the observed gravity data. Then the densities are cokriged or simulated using the gravity data as the secondary variable. The model allows noise to be included in the observations. The method is applied to two synthetic models: a short dipping dike and a stochastic distribution of densities. Then some geologic information is added as constraints to the cokriging system. The results show the ability of the method to integrate complex a priori information. The survey data of the Matagami mining camp are considered as a case study. The inversion method based on cokriging is applied to the residual anomaly to map the geology through the estimation of the density distribution in this region. The results of the inversion and simulation methods are in good agreement with the surface geology of the survey region.

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.

The 4-D microgravity method for waterflood surveillance: A model study for the Prudhoe Bay reservoir, Alaska

Geophysics ◽  
1999 ◽  
Vol 64 (1) ◽  
pp. 78-87 ◽  
Author(s):  
Jennifer L. Hare ◽  
John F. Ferguson ◽  
Carlos L. V. Aiken ◽  
Jerry L. Brady
Keyword(s):  
Total Mass ◽  
Least Squares Method ◽  
Gravity Data ◽  
Water Injection ◽  
Gravity Modeling ◽  
Inversion Method ◽  
Model Parameters ◽  
Worst Case ◽  
Inverse Models ◽  
Prudhoe Bay

Forward and inverse gravity modeling is carried out on a suite of reservoir simulations of a proposed water injection in the Prudhoe Bay reservoir, Alaska. A novel surveillance technique is developed in which surface gravity observations are used to monitor the progress of a gas cap waterflood in the reservoir at 8200-ft (2500-m) depth. This cost‐effective method requires that high‐precision gravity surveys be repeated over periods of years. Differences in the gravity field with time reflect changes in the reservoir fluid densities. Preliminary field tests at Prudhoe Bay indicates survey accuracy of 5–10 μGal can be achieved for gravity data using a modified Lacoste & Romberg “G” type meter or Scintrex CG-3M combined with the NAVSTAR Global Positioning System (GPS). Forward gravity modeling predicts variations in surface measurements of 100 μGal after 5 years of water injection, and 180–250 μGal after 15 years. We use a constrained least‐squares method to invert synthetic gravity data for subsurface density distributions. The modeling procedure has been formulated and coded to allow testing of the models for sensitivity to gravity sampling patterns, noise types, and various constraints on model parameters such as density, total mass, and moment of inertia. Horizontal‐feature resolution of the waterflood is about 5000 ft (1520 m) for constrained inverse models from synthetic gravity with 5 μGal standard deviation (SD) noise. The inversion method can account for total mass of injected water to within a few percent. Worst‐case scenarios result from inversion of gravity data which are contaminated by high levels (greater than 10–15 μGal SD) of spatially correlated noise, in which case the total mass estimate from inverse models may over or underestimate the mass by 10–20%. The results of the modeling indicate that inversion of time‐lapse gravity data is a viable technique for the monitoring of reservoir gas cap waterfloods.

2-D inversion of gravity data using sources laterally bounded by continuous surfaces and depth‐dependent density

Geophysics ◽  
2000 ◽  
Vol 65 (4) ◽  
pp. 1128-1141 ◽  
Author(s):  
Juan García‐Abdeslem
Keyword(s):  
Sensitivity Analysis ◽  
Gravity Data ◽  
Synthetic Data ◽  
Gravity Modeling ◽  
Inversion Method ◽  
Data Sets ◽  
Nonlinear Inversion ◽  
Correlation Matrices ◽  
Significant Difference ◽  
Dependent Density

A description is given of numerical methods for 2-D gravity modeling and nonlinear inversion. The forward model solution is suitable for calculating the gravity anomaly caused by a 2-D source body with depth‐dependent density that is laterally bounded by continuous surfaces and can easily accommodate different kinds of geologic structures. The weighted and damped discrete nonlinear inverse method addressed here can invert both density and geometry of the source body. Both modeling and inversion methods are illustrated with several examples using synthetic and two field gravity data sets—one over a sulfide ore body and other across a sedimentary basin. A sensitivity analysis is carried out for the resulting solutions by means of the resolution, covariance, and correlation matrices, providing insight into the capabilities and limitations of the inversion method. The inversion of synthetic data provides meaningful results, showing that the method is robust in the presence of noise. Its sensitivity analysis indicates an almost perfect resolution and small covariance, but high correlation between some parameters. Differences in the asperity aspect of the inverted‐field data sets turned out to be important for the inversion capabilities of the algorithm, making a significant difference in the resolution achieved, its covariance, and the degree of correlation among parameters.

3D inversion of potential field data using a marginalizing probabilistic method

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. G93-G106 ◽  
Author(s):  
Meixia Geng ◽  
Xiangyun Hu ◽  
Henglei Zhang ◽  
Shuang Liu
Keyword(s):  
Covariance Matrix ◽  
Field Data ◽  
Weighting Function ◽  
Probabilistic Method ◽  
A Priori ◽  
Inversion Method ◽  
Spatial Gradient ◽  
Underlying Assumption ◽  
Potential Field Data ◽  
Probabilistic Inversion

Probabilistic inversion methods have proven effective in solving many geophysical inverse problems. Structural orientation and spatial extent information can be efficiently incorporated the probabilistic inversion by the use of parameter covariances to produce a geologically realistic model. However, the use of a single model covariance matrix, with the underlying assumption of the presence of only one type of feature (e.g., similar size, shape, and orientation) in the subsurface, limits the ability of probabilistic inversions to recover geologically sound models. An approach based on marginalizing the probabilistic inversion is presented, which makes it possible to partition the inverse domain into various zones, each of which can have its own covariance matrix depending upon the features and/or depths of the sources. Moreover, a spatial gradient weighting function is introduced to enhance or attenuate the structural complexity in different zones. Thus, sources with different shapes, sizes, depths, and densities (or magnetic susceptibilities) can be simultaneously reconstructed. The sensitivity of the solutions to uncertainties in the a priori information, including the orientation, depth, and horizontal position as well as subdivision of the inversion domain, is analyzed. We found through synthetic examples and field data that the developed inversion method was a valid tool for exploration geophysics in presence of a priori geologic information.

scholarly journals 3D Gravity Modeling of Complex Salt Features in the Southern Gulf of Mexico

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Mauricio Nava-Flores ◽  
Carlos Ortiz-Aleman ◽  
Mauricio G. Orozco-del-Castillo ◽  
Jaime Urrutia-Fucugauchi ◽  
Alejandro Rodriguez-Castellanos ◽  
...  
Keyword(s):  
Gravity Data ◽  
Three Dimensional ◽  
Complex Salt ◽  
Gravity Modeling ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Oil Exploration ◽  
Potential Field Data ◽  
Estimation Algorithms ◽  
3D Gravity

We present a three-dimensional (3D) gravity modeling and inversion approach and its application to complex geological settings characterized by several allochthonous salt bodies embedded in terrigenous sediments. Synthetic gravity data were computed for 3D forward modeling of salt bodies interpreted from Prestack Depth Migration (PSDM) seismic images. Density contrasts for the salt bodies surrounded by sedimentary units are derived from density-compaction curves for the northern Gulf of Mexico’s oil exploration surveys. By integrating results from different shape- and depth-source estimation algorithms, we built an initial model for the gravity anomaly inversion. We then applied a numerically optimized 3D simulated annealing gravity inversion method. The inverted 3D density model successfully retrieves the synthetic salt body ensemble. Results highlight the significance of integrating high-resolution potential field data for salt and subsalt imaging in oil exploration.

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