3D gravity inversion with optimized mesh based on edge and center anomaly detection

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. G13-G23 ◽  
Author(s):  
Min Yang ◽  
Wanyin Wang ◽  
J. Kim Welford ◽  
Colin G. Farquharson
Keyword(s):  
Edge Detection ◽  
Gravity Data ◽  
Signal Amplitude ◽  
Spatial Extent ◽  
Gravity Inversion ◽  
Unknown Parameters ◽  
Vertical Derivative ◽  
Cpu Time ◽  
3D Gravity ◽  
Total Horizontal Derivative

Gravity inversion is inherently nonunique. Minimum-structure inversion has proved effective at dealing with this nonuniqueness. However, such an inversion approach, which involves a large number of unknown parameters, is computationally expensive. To improve efficiency while retaining the advantages of a minimum-structure-style inversion, we have developed a new method, based on edge detection and center detection of geologic bodies, to help to focus the spatial extent of meshing for gravity inversion. The chosen method of edge detection, normalized vertical derivative of the total horizontal derivative, helps to outline areas to be meshed by approximating the edges of key geophysical bodies. Next, the method of center detection, normalized vertical derivative of the analytic signal amplitude, helps to confirm the center of the areas to be meshed, then a binary mesh flag is generated. In this paper, the binary mesh flag, restricting the spatial extent of meshing, is first undertaken using the two methods, and it is shown to dramatically reduce the number of grid cells from 574,992 for the whole research volume to 170,544 for the localized mesh by the same size of cell, which is decreased by almost 70%. Second, gravity inversion is performed using the spatially restricted mesh. The recovered model constructed using the binary mesh flag is similar to the model obtained using the mesh spanning the whole volume and saves approximately 80% of the CPU time. Finally, a real gravity data example from Olympic Dam in Australia is successfully used to test the validity and practicability of this proposed method. The geologic source bodies are resolved between 250 and 750 m depth. Overall, the combination of edge detection and center detection, and our binary mesh flag, succeed in reducing the number of cells and saving the CPU time and computer storage required for gravity inversion.

3D gravity inversion of basement relief for a rift basin based on combined multinorm and normalized vertical derivative of the total horizontal derivative techniques

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. G107-G118 ◽  
Author(s):  
Xuliang Feng ◽  
Wanyin Wang ◽  
Bingqiang Yuan
Keyword(s):  
Objective Function ◽  
Gravity Data ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Rift Basin ◽  
Constraint Function ◽  
Vertical Derivative ◽  
Model Constraint ◽  
3D Gravity ◽  
Total Horizontal Derivative

The basement of a rift sedimentary basin, often possessing smooth and nonsmooth shapes, is not easily recovered from gravity data by current inversion methods. We have developed a new 3D gravity inversion method to estimate the basement relief of a rift basin. In the inversion process, we have established the objective function by combining the gravity data misfit function, the known depth constraint function, and the model constraint function composed of the [Formula: see text]-norm and [Formula: see text]-norm, respectively. An edge recognition technology based on the normalized vertical derivative of the total horizontal derivative for gravity data is adopted to recognize the discontinuous and continuous parts of the basin and combine the two inputs to form the final model constraint function. The inversion is conducted by minimizing the objective function by the nonlinear conjugate gradient algorithm. We have developed two applications using synthetic gravity anomalies produced from two synthetic rift basins, one with a single graben and one with six differently sized grabens. The test results indicate that the inversion method is a feasible technique to delineate the basement relief of a rift basin. The inversion method is also tested on field data from the Xi’an depression in the middle of the Weihe Basin, Shaanxi Province, China, and the result illustrates its effectiveness.

An integrated geophysical approach for imaging subbasalt sedimentary basins: Case study of Jam River Basin, India

Geophysics ◽  
2007 ◽  
Vol 72 (6) ◽  
pp. B141-B147 ◽  
Author(s):  
V. Chakravarthi ◽  
G. B. K. Shankar ◽  
D. Muralidharan ◽  
T. Harinarayana ◽  
N. Sundararajan
Keyword(s):  
Gravity Field ◽  
River Basin ◽  
Gravity Data ◽  
Sedimentary Basins ◽  
Gravity Inversion ◽  
Data Points ◽  
3D Gravity ◽  
Regional Gravity ◽  
Godavari Basin

An integrated geophysical strategy comprising deep electrical resistivity and gravity data was devised to image subbasalt sedimentary basins. A 3D gravity inversion was used to determine the basement structure of the Permian sediments underlying the Cretaceous formation of the Jam River Basin in India. The thickness of the Cretaceous formation above the Permian sediments estimated from modeling 60 deep-electric-sounding data points agrees well with drilling information. The gravity effect of mass deficit between the Cretaceous and Permian formations was found using 3D forward modeling and subsequently removed from the Bouguer gravity anomaly along with the regional gravity field. The modified residual gravity field was then subjected to3D inversion to map the variations in depth of the basement beneath the Permian sediments. Inversion of gravity data resulted in two basement ridges, running almost east to west, dividing the basin into three independent depressions. It was found that the Katol and Kondhali faults were active even during post-Cretaceous time and were responsible for the development of the subsurface basement ridges in the basin. The inferred 3D basement configuration of the basin clearly brought out the listric nature of these two faults. Further, the extension of the Godavari Basin into the Deccan syneclise and the fact that the source-rock studies show the presence of hydrocarbons in the Sironcha block in the northern part of the Godavari Basin also shed some light on the hydrocarbon potential of the Jam River Basin.

scholarly journals Reservoir Identification Based on Gravity Method at “AUN” Geothermal Field

2019 ◽  
Vol 125 ◽  
pp. 14008
Author(s):  
Annisa Dwi Hafidah ◽  
Yunus Daud ◽  
Alfian Usman
Keyword(s):  
Gravity Data ◽  
Geothermal Field ◽  
Gravity Inversion ◽  
Eurasian Plate ◽  
Gravity Method ◽  
Vertical Derivative ◽  
Horizontal Derivative ◽  
Sumatra Island ◽  
Result Show ◽  
Subsurface Layers

Sumatra Island has the largest geothermal potential in Indonesia spread along the subduction zone between the Indian-Australian plate and the Eurasian plate. “AUN” geothermal field located in Sumatra Island and considered to be one of the largest potential geothermal prospects in Indonesia. This study is focused on identifying the prospect of “AUN” geothermal field using gravity method. First Horizontal Derivative (FHD) and Second Vertical Derivative (SVD) analysis were applied in order to determine a more accurate boundary of the fault. 3D inversions of gravity data were used to reconstruct subsurface model. The result show that analysis of First Horizontal Derivative (FHD) and Second Vertical Derivative (SVD) can confirm southwest-northeast fault and caldera structure as a boundary of geothermal reservoir and 3D gravity inversion can show subsurface layers with density 2.5 gr/cc to 2.8 gr/cc inside the boundary which is determined as a heat source in “AUN” geothermal field.

scholarly journals Subsurface structure investigation of the United Arab Emirates using gravity data

2021 ◽  
Vol 13 (1) ◽  
pp. 262-271
Author(s):  
Hakim Saibi ◽  
Diab Bakri Hag ◽  
Mohammed Saeed Mohammed Alamri ◽  
Hamdan Abdo Ali
Keyword(s):  
United Arab Emirates ◽  
Crustal Structure ◽  
Gravity Data ◽  
Three Dimensional ◽  
Petroleum Exploration ◽  
Gravity Inversion ◽  
Subsurface Structure ◽  
Bouguer Anomalies ◽  
Groundwater Aquifers ◽  
3D Gravity

Abstract The crustal structure beneath the United Arab Emirates (UAE) is still relatively unknown. Here, we use regional gravity data to constrain the subsurface density distribution and structure of the crust of the UAE by applying diverse gravity derivatives methods such as horizontal derivative (HDR), analytic signal (AS), and tilt angle (TA) to analyze the subsurface structure and perform three-dimensional (3D) gravity inversion for imaging crustal structure from the surface down to 35 km depth. The results are compared with known geological regional structures and the location of the petroleum fields. The Bouguer anomalies range from −100.8 to 113.5 mGal. The 3D gravity inversion results and the maximum Bouguer values coincide with the ophiolitic Hajar mountains in the east and the successive anticlines (uplifted basement rocks) and synclines in different parts of UAE, which could be promising sites for future mining and petroleum exploration. Also, the 3D density model results and the minimum Bouguer anomalies are located over the Aruma Basin, eastern UAE Platform, and Low Central UAE Platform, which can be the places for deep groundwater aquifers. These new results from HDR, AS, and TA successfully identify known geological structures, especially in the eastern part of UAE.

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.

Numerical modeling and 3D-gravity inversion of the Vargeão impact structure formed in a mixed basalt/sandstone target, Paraná Basin, Brazil

2021 ◽  
pp. 103396
Author(s):  
Laian de Moura Silva ◽  
Marcos Alberto Rodrigues Vasconcelos ◽  
Vinamra Agrawal ◽  
Alvaro Penteado Crósta ◽  
Emilson Pereira Leite
Keyword(s):  
Numerical Modeling ◽  
Gravity Inversion ◽  
Impact Structure ◽  
Paraná Basin ◽  
3D Gravity ◽  
Parana Basin

scholarly journals Subsurface modelling of Kei Kecil Island with 3D gravity inversion

2021 ◽  
Vol 1918 (2) ◽  
pp. 022033
Author(s):  
Supriyadi ◽  
E Wijanarko ◽  
Khumaedi
Keyword(s):  
Gravity Inversion ◽  
3D Gravity

scholarly journals 3D Gravity Data Modelling for Determining a Subsurface structure of The SDP Geothermal Field

2019 ◽  
Vol 1217 ◽  
pp. 012042
Author(s):  
T Meilasandi ◽  
A Sugianto ◽  
R D Indriana ◽  
U Harmoko
Keyword(s):  
Gravity Data ◽  
Geothermal Field ◽  
Data Modelling ◽  
Subsurface Structure ◽  
3D Gravity

3D gravity inversion and uncertainty assessment of basement relief via Particle Swarm Optimization

2017 ◽  
Vol 139 ◽  
pp. 338-350 ◽  
Author(s):  
J.L.G. Pallero ◽  
J.L. Fernández-Martínez ◽  
S. Bonvalot ◽  
O. Fudym
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Uncertainty Assessment ◽  
Gravity Inversion ◽  
Swarm Optimization ◽  
3D Gravity

Assessing Model Uncertainty for the Scaling Function Inversion of Potential Fields

Geophysics ◽  
2021 ◽  
pp. 1-39
Author(s):  
Mahak Singh Chauhan ◽  
Ivano Pierri ◽  
Mrinal K. Sen ◽  
Maurizio FEDI
Keyword(s):  
Simulated Annealing Algorithm ◽  
Scaling Function ◽  
Vertical Section ◽  
Gravity Data ◽  
Geometric Model ◽  
Salt Dome ◽  
The Body ◽  
Gravity Inversion ◽  
Geometrical Parameters ◽  
The Scaling Function

We use the very fast simulated annealing algorithm to invert the scaling function along selected ridges, lying in a vertical section formed by upward continuing gravity data to a set of altitudes. The scaling function is formed by the ratio of the field derivative by the field itself and it is evaluated along the lines formed by the zeroes of the horizontal field derivative at a set of altitudes. We also use the same algorithm to invert gravity anomalies only at the measurement altitude. Our goal is analyzing the different models obtained through the two different inversions and evaluating the relative uncertainties. One main difference is that the scaling function inversion is independent on density and the unknowns are the geometrical parameters of the source. The gravity data are instead inverted for the source geometry and the density simultaneously. A priori information used for both the inversions is that the source has a known depth to the top. We examine the results over the synthetic examples of a salt dome structure generated by Talwani’s approach and real gravity datasets over the Mors salt dome and the Decorah (USA) basin. For all these cases, the scaling function inversion yielded models with a better sensitivity to specific features of the sources, such as the tilt of the body, and reduced uncertainty. We finally analyzed the density, which is one of the unknowns for the gravity inversion and it is estimated from the geometric model for the scaling function inversion. The histograms over the density estimated at many iterations show a very concentrated distribution for the scaling function, while the density contrast retrieved by the gravity inversion, according to the fundamental ambiguity density/volume, is widely dispersed, this making difficult to assess its best estimate.

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