We have developed a new phase-based filter to enhance the edges of geologic sources from potential-field data using the local phase in the Poisson scale-space monogenic signal. The Poisson scale-space representation of a potential-field data is equivalent to performing an upward continuation of the data. We created a band-pass filter by taking the differences between two Poisson scale-space representations of the data. The local phase was defined as the arctangent of the ratio of the magnitude of the x-and y-components of the first-order Riesz transform of the filtered data to these data. These components were computed in the wavenumber domain and then transformed back into the space domain by the inverse Fourier transform. In the wavenumber domain, we found that these components are the multiplication of the Fourier transform of the filtered data by a Fourier-domain kernel, which in turn is the multiplication of the first-order horizontal derivative filter by the first-order vertical integral filter. This operation is stable, making the local phase of the monogenic signal quite insensitive to noise. We proved that if the data were the vertical component f z of a conservative field F, the x-and y-components of the first-order Riesz transform of f z were the horizontal components f x and f y of F. Hence, the local amplitude of the monogenic signal of f z is the 3D analytic signal amplitude of the scalar potential of F and the local phase resembles the tilt angle (TILT). Tests on synthetic total-field anomalies and a real aeromagnetic anomaly over the Pará-Maranhão Basin, Brazil, showed that the local phase in the scale-space monogenic signal had better performance than the TILT in delineating the geologic contacts that were not seen in the original data.
We have developed codes to calculate the local amplitude, the local phase, and the local orientation of the nonscale and the Poisson’s scale-space monogenic signals of potential-field data in version 1.0 of the open-source program Monogenic. The monogenic vector of a generic function is calculated in the wavenumber domain and then transformed back into the space domain to find the monogenic signal attributes. We compare the use of the nonscale monogenic signal with the Poisson’s scale-space monogenic signal in magnetic data. This comparison shows that the latter can produce better results as an edge detection filter. The implementation of the monogenic signal can be used to enhance other geophysical data, such as seismic, ground-penetrating radar, gravity, multiple-component gravity gradiometry, and magnetic gradient data.
ABSTRACT. Airborne geophysical surveys are widely used in geological prospecting of hydrocarbon reservoirs. The efficiency and acquisition speed of these methods in covering large areas accredit them as a key tool for any exploration project where there are sparse technical data available to support the exploratory decisions. Among the airborne geophysical methods, potential methods, namely, gravity and magnetics are the most spread in oil & gas projects of this nature. Such methods are used to support the generation of regional geological knowledge and also in detailed approaches, integrated with seismic, geochemical and well data. The objectives of this work were to describe the FalconTM Airborne Gravity Gradiometry System, explaining acquisition and processing steps, and crosscheck the results of its application in the southeastern portion of the Parecis Basin with two proposed models for the structural genesis and evolution proposed by the academy. Throughout the integration of the airborne gravity gradiometry and magnetic data along 2D seismic section it was possible to infer the geometry of the Pimenta Bueno Graben. While many works have mapped basement depth about 7,000 m, the current modeling shows basement deeper than 10,000 m.Keywords: airborne gravity gradiometry, 2D forward modeling, Parecis Basin, FalconTM, tectonic framework.RESUMO. Levantamentos aerogeofísicos são amplamente utilizados na prospecção geológica de reservatórios de hidrocarbonetos. A eficiência e a velocidade de aquisição desses métodos na cobertura de grandes áreas os credenciam como uma ferramenta fundamental para qualquer projeto de exploração onde há poucos dados técnicos disponíveis para apoiar as decisões exploratórias. Dentre os métodos geofísicos aéreos, os potenciais gravimétricos e magnetométricos são os mais utilizados em projetos da natureza de prospecção de óleo e gás. Tais métodos são utilizados para apoiar a geração de conhecimento geológico regional e também em abordagens de detalhe, integrados com seções sísmicas, dados geoquímicos e de poço. Este trabalho pretende apresentar o Sistema FalconTM de Gravimetria Gradiométrica, descrevendo suas etapas de aquisição e processamento, e interpretação dos resultados de sua aplicação na porção sudeste da Bacia do Parecis, em confronto com dois modelos propostos para a gênese e evolução estrutural da Bacia. Através da integração dos dados de gravimetria gradiométrica com dados magnéticos extraídos ao longo da secção sísmica 2D foi possível inferir a geometria detalhada do graben de Pimenta Bueno. Enquanto trabalhos anteriores mapearam a profundidade do embasamento em cerca de 7.000 metros, uma modelagem 2D direta e vinculada mostra que o mesmo pode alcançar, de forma localizada, profundidades maiores que 10.000 metros.Palavras-chave: gravimetria gradiométrica aérea, modelagem direta 2D, Bacia dos Parecis, FalconTM, arcabouc¸o tectônico.
We have developed a fast 3D regularized magnetic inversion algorithm for depth-to-basement estimation based on an efficient way to compute the total-field anomaly produced by an arbitrary interface separating nonmagnetic sediments from a magnetic basement. We approximate the basement layer by a grid of 3D vertical prisms juxtaposed in the horizontal directions, in which the prisms’ tops represent the depths to the magnetic basement. To compute the total-field anomaly produced by the basement relief, the 3D integral of the total-field anomaly of a prism is simplified by a 1D integral along the prism thickness, which in turn is multiplied by the horizontal area of the prism. The 1D integral is calculated numerically using the Gauss-Legendre quadrature produced by dipoles located along the vertical axis passing through the prism center. This new magnetic forward modeling overcomes one of the main drawbacks of the nonlinear inverse problem for estimating the basement depths from magnetic data: the intense computational cost to calculate the total-field anomaly of prisms. The new sensitivity matrix is simpler and computationally faster than the one using classic magnetic forward modeling based on the 3D integrals of a set of prisms that parameterize the earth’s subsurface. To speed up the inversion at each iteration, we used the Gauss-Newton approximation for the Hessian matrix keeping the main diagonal only and adding the first-order Tikhonov regularization function. The large sparseness of the Hessian matrix allows us to construct and solve a linear system iteratively that is faster and demands less memory than the classic nonlinear inversion with prism-based modeling using 3D integrals. We successfully inverted the total-field anomaly of a simulated smoothing basement relief with a constant magnetization vector. Tests on field data from a portion of the Pará-Maranhão Basin, Brazil, retrieved a first depth-to-basement estimate that was geologically plausible.
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