Focusing iterative migration of gravity gradiometry data acquired in the Nordkapp Basin, Barents Sea

Abstract

Geological interpretation based on gravity gradiometry data constitutes a very challenging problem. Rigorous 3D inversion is the main technique used in quantitative interpretation of the gravity gradiometry data. An alternative approach to the quantitative analysis of the gravity gradiometry data is based on 3D smooth potential field migration. This rapid imaging approach, however, has the shortcomings of providing smooth images since it is based on direct integral transformation of the observed gravity tensor data. Another limitation of migration transformation is related to the fact that, in a general case, the gravity data generated by the migration image do not fit the observed data well. In this paper, we describe a new approach to rapid imaging that allows us to produce the density distribution which adequately describes the observed data and, at the same time, images the structures with anomalous densities having sharp boundaries. This approach is based on the basic theory of potential field migration with a focusing stabilizer in the framework of regularized scheme, which iteratively transfers the observed gravity tensor field into an image of the density distribution in the subsurface formations. The results of gravity migration can also be considered as an a priori model for conventional inversion subsequently. We demonstrate the practical application of migration imaging using both synthetic and real gravity gradiometry data sets acquired for the Nordkapp Basin in the Barents Sea.

Magnetic Field Imaging of Salt Structures at Nordkapp Basin, Barents Sea

“…Also, the depths inferred by our 3‐D model agree with the interpretation results of 2‐D seismic reflection profiles (Koyi et al, 1993). Finally, our results fairly agree with the salt structures of basin imaged by Tu and Zhdanov (2020), Wan and Zhdanov (2008), and Xu et al (2020) from gravity gradiometry data.…”

“…Diapirs # 1, 2, and 4 ("Uranus"; Stadtler et al, 2014) are the deepest ones and extend down to 3,500-4,000 m b.s.l. Diapirs # 6 and # 7 ("G2" and "F2", respectively, in Tu &Xu et al, 2020) reach 2000 m b.s.l., whereas diapirs #3 and #5 are the shallowest ones, with #5 not exceeding 1,500 m depth and having the weakest magnetization contrast. A comparison between the input and predicted data from CDEXP imaging (Figures 3c-3e) shows that the fitting is rather good.…”

“…Nevertheless, in some cases seismic imaging of salt diapirs has given rise to considerable problems in defining the geometries of salt flanks and subsalt reflectors, as the well‐studied Nordkapp Basin in the Barents Sea demonstrates (e.g., Koyi et al, 1993; Nilsen et al, 1995; Xu et al, 2020). The uncertainty derives from seismic imaging distortion around the salt diapir area that makes the creation of a velocity model difficult.…”

“…The reason is the large contrast in the physical properties of the evaporites (high seismic velocities and low densities) with respect to the overlying and surrounding sedimentary materials (e.g., Choi et al, 2011;Hayward et al, 2014). Nevertheless, in some cases seismic imaging of salt diapirs has given rise to considerable problems in defining the geometries of salt flanks and subsalt reflectors, as the well-studied Nordkapp Basin in the Barents Sea demonstrates (e.g., Koyi et al, 1993;Nilsen et al, 1995;Xu et al, 2020). The uncertainty derives from seismic imaging distortion around the salt diapir area that makes the creation of a velocity model difficult.…”