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L0-norm gravity inversion with new depth weighting function and bound constraints

100%

Gebre M. G. , Lewi E.

Acta Geophysica

2022

tom Vol. 70, no 4

1619--1634

Delineating geologic features through the inversion of gravity data is an important goal in a range of geophysical investigations. However, it is a well-known fact that gravity data inversion has no inherent depth resolution. In order to overcome this limitation, different depth weighting approaches have been developed. With the purpose of finding an effective and a more convenient way to precisely estimate the depth of the anomalous body, we have tested the most popularly used depth weighting function. Our test showed that it does not properly counteract the decay of the gravity kernel and is strongly dependent on the exponent term. To resolve this, we have proposed a new depth weighting function that can easily be automated and counteracts the depth dependent natural decay of the gravity kernel more appropriately. Through this, the challenges in trial and error selection of the exponent of the old depth weighting function are avoided. The new depth weighing function was then implemented to improve a gravity inversion method, which produces compact and sharp images of the subsurface density distributions. The inversion method is obtained from the minimization of an objective function, which consists of data misfit and L0-norm stabilizing functions, by iteratively reweighted least-squares algorithm. To evaluate the practicality and resolution capability of the method, it was tested using a number of synthetic data sets from geometrically complex models and real data. The inversion results proved the effectiveness of our method in producing geologically acceptable multiple localized bodies with improved depth resolution. This in turn illustrates the applicability of the newly proposed function in the inversion of gravity data.

3D Gravity Inversion using Tikhonov Regularization

72%

Toushmalani R. , Saibi H.

tom Vol. 63, no. 4

1044--1065

Subsalt exploration for oil and gas is attractive in regions where 3D seismic depth-migration to recover the geometry of a salt base is difficult. Additional information to reduce the ambiguity in seismic images would be beneficial. Gravity data often serve these purposes in the petroleum industry. In this paper, the authors present an algorithm for a gravity inversion based on Tikhonov regularization and an automatically regularized solution process. They examined the 3D Euler deconvolution to extract the best anomaly source depth as a priori information to invert the gravity data and provided a synthetic example. Finally, they applied the gravity inversion to recently obtained gravity data from the Bandar Charak (Hormozgan, Iran) to identify its subsurface density structure. Their model showed the 3D shape of salt dome in this region.