A computer program to perform the upward continuation of potential field data between arbitrary surfaces

1989 ◽  
Vol 15 (6) ◽  
pp. 889-903 ◽  
Author(s):  
Marcello Ciminale ◽  
Mariano Loddo
2020 ◽  
Author(s):  
Jinlan Liu ◽  
Wanyin Wang ◽  
Shengqing Xiong

<p>It is vital to quickly and effectively determine the extent and depth of geological body by using potential field data in gravity and magnetic survey. In this study, three key techniques studying the extent and depth of geological sources based on curvature attribute are studied: the optimal solutions to the objective function, the edge of geological bodies and picking out solutions. Firstly, the optimal solution to the objective function is studied, that is, the key extraction algorithm about the curvature attribute. The Huber norm is introduced into the extraction algorithm of curvature attribute, which more accurately detect the depth of edge of the geological bodies. Secondly, the normalized vertical derivative of the total horizontal derivative (NVDR-THDR) technique is introduced into curvature attribute, which shows more continuous results about the edge position of the geological bodies and more sensitive to the small-scale tectonic structure. Finally, we study the way to pick out the inversion solution, that is, to solve the multi-solution equations in the inversion. The upward continuation of a certain height with strict physical significance was introduced into the inversion method, which was used to suppress the noise, and the final and actual inversion depth was equal to the inversion depth minus the height of upward continuation. And the average value of threshold limitation technology of the potential fields data was also introduced into this method. Using the two technologies, solutions of non-field source edge positions were eliminated, and make the inversion solutions closer to the actual situation. Through the above three key techniques, the accuracy, continuity and recognition to the small-scale structure of the inversion result are optimized. The theoretical models are used to verify the effectiveness of the above key technologies, the results show that the three key technologies have achieved good results, and the combined models are used to verify the effectiveness of the optimized inversion method. The measured aeromagnetic data were used to inversing the edge depth of the intrusive rock in a mining area, and the inversion results are in good agreement with the rock depth revealed by borehole.</p>


Geophysics ◽  
2012 ◽  
Vol 77 (1) ◽  
pp. G13-G24 ◽  
Author(s):  
Maurizio Fedi ◽  
Mark Pilkington

Several noniterative, imaging methods for potential field data have been proposed that provide an estimate of the 3D magnetization/density distribution within the subsurface or that produce images of quantities related or proportional to such distributions. They have been derived in various ways, using generalized linear inversion, Wiener filtering, wavelet and depth from extreme points (DEXP) transformations, crosscorrelation, and migration. We demonstrated that the resulting images from each of these approaches are equivalent to an upward continuation of the data, weighted by a (possibly) depth-dependent function. Source distributions or related quantities imaged by all of these methods are smeared, diffuse versions of the true distributions; but owing to the stability of upward continuation, resolution may be substantially increased by coupling derivative and upward continuation operators. These imaging techniques appeared most effective in the case of isolated, compact, and depth-limited sources. Because all the approaches were noniterative, computationally fast, and in some cases, produced a fit to the data, they did provide a quick, but approximate picture of physical property distributions. We have found that inherent or explicit depth-weighting is necessary to image sources at their correct depths, and that the best scaling law or weighting function has to be physically based, for instance, using the theory of homogeneous fields. A major advantage of these techniques was their speed, efficiently providing a basis for further detailed, follow-up modelling.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Luan Thanh Pham ◽  
Ozkan Kafadar ◽  
Erdinc Oksum ◽  
Ahmed M. Eldosouky

Geophysics ◽  
2014 ◽  
Vol 79 (1) ◽  
pp. IM1-IM9 ◽  
Author(s):  
Nathan Leon Foks ◽  
Richard Krahenbuhl ◽  
Yaoguo Li

Compressive inversion uses computational algorithms that decrease the time and storage needs of a traditional inverse problem. Most compression approaches focus on the model domain, and very few, other than traditional downsampling focus on the data domain for potential-field applications. To further the compression in the data domain, a direct and practical approach to the adaptive downsampling of potential-field data for large inversion problems has been developed. The approach is formulated to significantly reduce the quantity of data in relatively smooth or quiet regions of the data set, while preserving the signal anomalies that contain the relevant target information. Two major benefits arise from this form of compressive inversion. First, because the approach compresses the problem in the data domain, it can be applied immediately without the addition of, or modification to, existing inversion software. Second, as most industry software use some form of model or sensitivity compression, the addition of this adaptive data sampling creates a complete compressive inversion methodology whereby the reduction of computational cost is achieved simultaneously in the model and data domains. We applied the method to a synthetic magnetic data set and two large field magnetic data sets; however, the method is also applicable to other data types. Our results showed that the relevant model information is maintained after inversion despite using 1%–5% of the data.


Sign in / Sign up

Export Citation Format

Share Document