Distance field computation for geological slab surface data sets

2011 ◽  
Vol 14 (4) ◽  
pp. 143-156
Author(s):  
Marek Vančo ◽  
Bernd Hamann ◽  
Oliver Kreylos ◽  
Magali I. Billen ◽  
Margarete A. Jadamec
Keyword(s):  
Data Sets ◽  
Slab Surface ◽  
Distance Field ◽  
Field Computation ◽  
Surface Data

Shear and compressive wave data acquisition using multicomponent vibrating source and landstreamer

2021 ◽  
Author(s):  
Andre Pugin ◽  
Barbara Dietiker ◽  
Kevin Brewer ◽  
Timothy Cartwright
Keyword(s):  
Leading Edge ◽  
Data Sets ◽  
Compressive Wave ◽  
Near Surface ◽  
Source Type ◽  
Receiver Array ◽  
Surface Data ◽  
Source Orientation ◽  
Refracted Waves ◽  
Wave Modes

<p>In the vicinity of Ottawa, Ontario, Canada, we have recorded many multicomponent seismic data sets using an in-house multicom­ponent vibrator source named Microvibe and a landstreamer receiver array with 48 3-C 28-Hz geophones at 0.75-m intervals. The receiver spread length was 35.25 m, and the near-offset was 1.50 m. We used one, two or three source and three receiver orientations — vertical (V), inline-horizontal (H1), and transverse-horizontal (H2). We identified several reflection wave modes in the field records — PP, PS, SP, and SS, in addition to refracted waves, and Rayleigh-mode and Love-mode surface waves. We computed the semblance spectra of the selected shot records and ascertained the wave modes based on the semblance peaks. We then performed CMP stacking of each of the 9-C data sets using the PP and SS stacking velocities to compute PP and SS reflection profiles.</p><p>Despite the fact that any source type can generate any combination of wave modes — PP, PS, SP, and SS, partitioning of the source energy depends on the source orientation and VP/VS ratio. Our examples demonstrate that the most prominent PP reflection energy is recorded by the VV source-receiver orientation, whereas the most prominent SS reflection energy is recorded by the H2H2 source-receiver orientation with possibility to obtain decent shear wave near surface data in all other vibrating and receiving directions.</p><p>Pugin, Andre and Yilmaz, Öz, 2019. Optimum source-receiver orientations to capture PP, PS, SP, and SS reflected wave modes. The Leading Edge, vol. 38/1, p. 45-52. https://doi.org/10.1190/tle38010045.1</p>

Joint inversion of surface and three‐component borehole magnetic data

Geophysics ◽  
2000 ◽  
Vol 65 (2) ◽  
pp. 540-552 ◽  
Author(s):  
Yaoguo Li ◽  
Douglas W. Oldenburg
Keyword(s):  
Field Data ◽  
Joint Inversion ◽  
Magnetic Data ◽  
Data Sets ◽  
Source Depth ◽  
Inversion Algorithm ◽  
Borehole Data ◽  
Weighting Functions ◽  
Surface Data ◽  
Geometric Decay

The inversion of magnetic data is inherently nonunique with respect to the distance between the source and observation locations. This manifests itself as an ambiguity in the source depth when surface data are inverted and as an ambiguity in the distance between the source and boreholes if borehole data are inverted. Joint inversion of surface and borehole data can help to reduce this nonuniqueness. To achieve this, we develop an algorithm for inverting data sets that have arbitrary observation locations in boreholes and above the surface. The algorithm depends upon weighting functions that counteract the geometric decay of magnetic kernels with distance from the observer. We apply these weighting functions to the inversion of three‐component magnetic data collected in boreholes and then to the joint inversion of surface and borehole data. Both synthetic and field data sets are used to illustrate the new inversion algorithm. When borehole data are inverted directly, three‐component data are far more useful in constructing good susceptibility models than are single‐component data. However, either can be used effectively in a joint inversion with surface data to produce models that are superior to those obtained by inversion of surface data alone.

Hybrid Distance Field Computation

2001 ◽  
pp. 195-209 ◽  
Author(s):  
Richard Satherley ◽  
Mark W. Jones
Keyword(s):  
Distance Field ◽  
Field Computation ◽  
Hybrid Distance

scholarly journals Inferring ice thickness from a glacier dynamics model and multiple surface data sets

2017 ◽  
Vol 29 (5-6) ◽  
pp. e2460 ◽  
Author(s):  
Yawen Guan ◽  
Murali Haran ◽  
David Pollard
Keyword(s):  
Ice Thickness ◽  
Data Sets ◽  
Dynamics Model ◽  
Surface Data ◽  
Glacier Dynamics

scholarly journals Layered manufacturing for medical imaging data

2019 ◽  
Vol 11 (8) ◽  
pp. 168781401987139
Author(s):  
Shyh-Kuang Ueng ◽  
Hsin-Cheng Huang ◽  
Chieh-Shih Chou ◽  
Hsuan-Kai Huang
Keyword(s):  
Medical Image ◽  
Three Dimensional ◽  
Image Data ◽  
Target Object ◽  
Layered Manufacturing ◽  
Boundary Representation ◽  
Data Sets ◽  
Imaging Data ◽  
Distance Field ◽  
Dimensional Image

Layered manufacturing techniques have been successfully employed to construct scanned objects from three-dimensional medical image data sets. The printed physical models are useful tools for anatomical exploration, surgical planning, teaching, and related medical applications. Before fabricating scanned objects, we have to first build watertight geometrical representations of the target objects from medical image data sets. Many algorithms had been developed to fulfill this duty. However, some of these methods require extra efforts to resolve ambiguity problems and to fix broken surfaces. Other methods cannot generate legitimate models for layered manufacturing. To alleviate these problems, this article presents a modeling procedure to efficiently create geometrical representations of objects from computerized tomography scan and magnetic resonance imaging data sets. The proposed procedure extracts the iso-surface of the target object from the input data set at the first step. Then it converts the iso-surface into a three-dimensional image and filters this three-dimensional image using morphological operators to remove dangling parts and noises. At the next step, a distance field is computed in the three-dimensional image space to approximate the surface of the target object. Then the proposed procedure smooths the distance field to soothe sharp corners and edges of the target object. Finally, a boundary representation is built from the distance field to model the target object. Compared with conventional modeling techniques, the proposed method possesses the following advantages: (1) it reduces human efforts involved in the geometrical modeling process. (2) It can construct both solid and hollow models for the target object, and wall thickness of the hollow models is adjustable. (3) The resultant boundary representation guarantees to form a watertight solid geometry, which is printable using three-dimensional printers. (4) The proposed procedure allows users to tune the precision of the geometrical model to compromise with the available computational resources.

scholarly journals Registration of Dental Tomographic Volume Data and Scan Surface Data Using Dynamic Segmentation

2018 ◽  
Vol 8 (10) ◽  
pp. 1762 ◽  
Author(s):  
Keonhwa Jung ◽  
Sukwoo Jung ◽  
Inseon Hwang ◽  
Taeksoo Kim ◽  
Minho Chang
Keyword(s):  
Computer Aided Design ◽  
Automatic Segmentation ◽  
Iterative Closest Point ◽  
Data Sets ◽  
Volume Data ◽  
Metal Artifacts ◽  
Registration Method ◽  
Dynamic Segmentation ◽  
Surface Data ◽  
Edge Points

Over recent years, computer-aided design (CAD) has become widely used in the dental industry. In dental CAD applications using both volumetric computed tomography (CT) images and 3D optical scanned surface data, the two data sets need to be registered. Previous works have registered volume data and surface data by segmentation. Volume data can be converted to surface data by segmentation and the registration is achieved by the iterative closest point (ICP) method. However, the segmentation needs human input and the results of registration can be poor depending on the segmented surface. Moreover, if the volume data contains metal artifacts, the segmentation process becomes more complex since post-processing is required to remove the metal artifacts, and initially positioning the registration becomes more challenging. To overcome these limitations, we propose a modified iterative closest point (MICP) process, an automatic segmentation method for volume data and surface data. The proposed method uses a bundle of edge points detected along an intensity profile defined by points and normal of surface data. Using this dynamic segmentation, volume data becomes surface data which can be applied to the ICP method. Experimentally, MICP demonstrates fine results compared to the conventional registration method. In addition, the registration can be completed within 10 s if down sampling is applied.

scholarly journals Influence of the sunspot cycle on the Northern Hemisphere wintertime circulation from long upper-air data sets

2013 ◽  
Vol 13 (13) ◽  
pp. 6275-6288 ◽  
Author(s):  
Y. Brugnara ◽  
S. Brönnimann ◽  
J. Luterbacher ◽  
E. Rozanov
Keyword(s):  
Northern Hemisphere ◽  
Sunspot Cycle ◽  
Lower Troposphere ◽  
Data Sets ◽  
Seasonal Temperature ◽  
Data Set ◽  
Temperature Changes ◽  
European Climate ◽  
Surface Data ◽  
Wintertime Circulation

Abstract. Here we present a study of the 11 yr sunspot cycle's imprint on the Northern Hemisphere atmospheric circulation, using three recently developed gridded upper-air data sets that extend back to the early twentieth century. We find a robust response of the tropospheric late-wintertime circulation to the sunspot cycle, independent from the data set. This response is particularly significant over Europe, although results show that it is not directly related to a North Atlantic Oscillation (NAO) modulation; instead, it reveals a significant connection to the more meridional Eurasian pattern (EU). The magnitude of mean seasonal temperature changes over the European land areas locally exceeds 1 K in the lower troposphere over a sunspot cycle. We also analyse surface data to address the question whether the solar signal over Europe is temporally stable for a longer 250 yr period. The results increase our confidence in the existence of an influence of the 11 yr cycle on the European climate, but the signal is much weaker in the first half of the period compared to the second half. The last solar minimum (2005 to 2010), which was not included in our analysis, shows anomalies that are consistent with our statistical results for earlier solar minima.

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