Data analysis of potential field methods using geostatistics

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. G35-G44 ◽  
Author(s):  
Pejman Shamsipour ◽  
Michel Chouteau ◽  
Denis Marcotte

Processing of potential field data is commonly done by spectral methods because of their low computational complexity. However, we have studied some geostatistical methods to process the potential field data, and we find the advantages of using these spatial methods. First, we investigate transformation of data by kriging using a gravimetric model of covariance, we compare this approach with the spectral method, and we find its advantage when the data were sparse and not on a regular grid using a synthetic example as well as a field data example. Then, we use factorial kriging for noise reduction and separation of the regional and residual components. This method does not have some of the practical limitations that the spectral-based methods encounter. Finally, we determine the flexibility of interpolation using nonstationary covariances.

2012 ◽  
Vol 4 (3) ◽  
Author(s):  
Salah Saleh ◽  
Ahmed Saleh

AbstractThe aim of the present work is to evaluate the stress direction and the tectonic trends of the study area using magnetic anisotropy and potential field data interpretations (Bouguer and aeromagnetic). The specific objective of the gravity and aeromagnetic interpretation is to establish the trend and depth of the structural configuration of the basement rocks. Horizontal gradient techniques could to delineate directions of deep sources and enabled tracing several faults, lineaments and tectonic boundaries of basement rocks. The trend analysis shows N40°–50°W, N10°–20°W and N10°–20°E which may be related to the Gulf of Suez, Red Sea and Gulf of Aqaba stresses. However, Euler Deconvolution technique was applied using the aeromagnetic data to provide reliable information about penetrated source depth (100 m and ∼10.0 km) and trends of the subsurface sources (principally in NW and NE directions). Moreover, representative 72 oriented rock samples have been collected from seven sites in the study area. The rock magnetic properties and magnetic anisotropy analysis have been determined for all the studied samples. The interpretation clearly defined magnetic lineation at all sites and anisotropy of magnetic susceptibility (AMS) parameters. The stress direction of the studied area has been evaluated using magnetic anisotropy and geophysical analysis. Generally the estimated geophysical data analysis (Bouguer and aeromagnetic) are well consistent with the AMS interpretations of this study. The results indicated that the directions of predominant faults and foliations are NW-SE (related to the Gulf of Suez and Red Sea rifting) which indicate that the main stress and tectonic trend is NE-SW, which is more predominant in southern Sinai region. Moreover, it is clear that, the studied area was affected also by less predominant sources trended in NE-SW direction, which related to the tectonic activity of Gulf of Aqaba. The least predominant is north 40°–50° east that is probably due to the Syrian Arc system. Finally, our results are extremely coincided with the previous stress directions derived from geological, seismological and tectonic analysis in northern Red Sea rift, Gulf of Suez and Sinai regions.


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.


2010 ◽  
Author(s):  
M. Shyeh Sahibul Karamah ◽  
M. N. Khairul Arifin ◽  
Mohd N. Nawawi ◽  
A. K. Yahya ◽  
Shah Alam

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