+1 510-522-0700


3D Visualization of Hyperspectral Data

| |

Point Loma, California—LiDAR merged with aerial photo. LiDAR data generated for the Scripps Institution of Oceanography by the Center for Space Research, the University of Texas at Austin (CSR), with support provided by the Bureau of Economic Geology, the University of Texas at Austin (BEG), and the Government Flight Services of the Texas Department of Transportation. Aerial photo from the Joint Airborne Lidar Bathymetry Technical Center of eXpertise, 2008.

Across many industries, the use of hyperspectral data has seen an increasing trend in recent years. Advanced technology has elevated the way these data can be used and the information that can be inferred from them. Now, more than ever, it is easier for industries like geothermal or oil and gas to identify their potential sources just through careful visual analysis of the surface imagery. However, with 2D imagery, it may not always be possible to identify objects or obstacles with a greater amount of detail as desired.

With software capable of 3D visualization of hyperspectral data for analysis, geologists and engineers can integrate a surface or topographical model with hyperspectral imagery to get a more focused view into the surface features—such as the presence of natural wells, oil spills or natural oil seeps, or vegetation, and its economic effect in the planning and development of the project.

The Importance of Hyperspectral Data and Imagery

In the study of surface features, the use of multispectral remote sensing for imaging has been in use for a long time. However, with its limited band measurements, it has not been as successful in the purpose of narrowing down the land surface details. Hyperspectral sensors are able to acquire data from over a hundred narrow spectral bands across the electromagnetic spectrum. Simply put, they are able to record shorter or longer wavelengths of visible light coming from the area. This supports continuous data collection to obtain the spectrum for each pixel in the imagery, providing much more sensitivity to identify surface attributes and their subtle variations.

In many industries, these hyperspectral data have been useful in making decisions regarding their potential resource exploration and operational effectiveness.

  • In the oil and gas industry, hyperspectral data can be used to identify oil seepages or contaminated soil which can indicate the possibility of the presence of a deeper hydrocarbon reservoir.
  • The presence of different minerals can be detected through different wave spectrums for mining purposes.
  • The geothermal industry can utilize the data to visually detect the heat signatures and thermal anomalies to identify targets.

This indication of surface signatures through hyperspectral imagery is ideal for industries to perform rapid diagnosis of the study area. 3D volume visualization of these quantified data can be further beneficial in enhancing geospatial analysis.

Leveraging 3D Visualization for Enhanced Decision-Making

In contrast to the 2D analysis, 3D visualization of hyperspectral data provides a better way to view, scan, and identify surface attributes. Data visualization, integration, and analysis software—such as CoViz 4D—enables the formation of a 3D grid model through the integration of hyperspectral data with other topographical and surface data. The different color bands depicting the reflected electromagnetic spectrum can be optimized to identify the area of interest. CoViz 4D allows for:

  • Integration of a large amount of data with each pixel having multiple spectrums
  • Identification of surface features at their correct geospatial position
  • Color mapping within a user-defined frequency range
  • Filtering of the color bands to identify surface features such as water, different vegetation types, different rock types, etc.
  • Identification of variation in real-time and in 3D

The powerful visualization of hyperspectral data, with hundreds of bands on each dataset, not only identifies the presence of any object but also the details of the scene is revealed. For example, with hyperspectral data visualization of vegetation, not only the presence of trees but also the concentration of specific species can be identified.

CoViz 4D: Enhancing Economic Consequence Across Multiple Discipline

The visualization of hyperspectral data can be facilitated by CoViz 4D. Without being on the field, it is possible to narrow in on the possible hydrocarbon, geothermal, and mineral targets. The wide spectrum of color bands can be used to recognize the surface feature and the band filter can be changed conveniently to identify the desired feature. Furthermore, with 3D visualization, the accuracy of data analysis can be enhanced as the visual interpretation gives the ability to dive into the details of features rather than just the color and appearance that can be identified with 2D.

Geologists, geoscientists, and engineers can leverage the 3D visualization of hyperspectral data to gain more confidence in data interpretation and classification. With more accuracy in results, it is easier to make more informed and economic decisions.

CoViz 4D, a data visualization and analytics software from Dynamic Graphics Inc. gives oil and gas professionals the ability to easily access and analyze relevant data associated with HPHT reservoirs. Powerful visualization capabilities enable reservoir teams to explore data relationships, calculate gradients, and more accurately analyze how subsurface conditions influence drilling and completion methods. To learn more about CoViz 4D contact our team.


Multilateral Well Drilling Technology: Reducing Risk & Improving Production

Multilateral well drilling technologies have evolved significantly since being pioneered in the Bashkiria fields in Russia in 1953. Today, the diversity of drill string and bottom hole assembly designs combined with the ever-increasing volumes of subsurface data allow...

How to Increase Oil Well Production Through Reservoir Analytics

When determining how to increase oil well production, analysts must consider the ways in which production can be improved through reservoir analytics. By analyzing surface and subsurface data, potential roadblocks—such as sediment clogging, condensate blocks,...

Integrating Seismic Data and Well Logs within a 3D Geospatial Volume

Gamma ray logs for multiple wells drilled into a sand body (semi-transparent orange) with seismic amplitude shown.  Data used by permission of owner.Accurate analysis of geological and geophysical data is the basis for understanding reservoir characteristics in oil...

How to Improve Hydraulic Fracturing With Data Visualization & Analysis

Achieving more optimum, cost-effective recovery from unconventional reservoirs—particularly at a time when independents are cautious about these investments—begins with an in-depth analysis of subsurface conditions. These conditions, which are critical...

Site Selection for Geothermal Power Plants: Comprehensive Visualization of Geographical Data

With the increase in sustainable energy demand across the globe, there has also been an increase in interest in geothermal energy sources. Industries are increasingly seeking an interest in the exploration of potential geothermal sites for geothermal reserves....

Depth Conversion of 3D Seismic Data Through Visualization

Time-domain on top with a velocity cube, seismic cube, and interpreted horizons. Depth domain below with the depth-converted seismic cube, wells, well tops, and reservoir simulation grid derived from the depth-converted horizons. Data used by permission of the...

4D Comparative Analysis of Seismic Reflection Data

Seismic reflection data have been utilized in the oil and gas industry and other geological studies to identify subsurface characteristics, calling attention to prevalent uncertainty and variations. The data is dependent upon the presence of acoustical contrasts...

Visual Evaluation of Infill Well Spacing

Potential Infill well plans showing different sidetrack opportunities while targeting bypassed oil in an onshore oil field. Data courtesy of RMOTC and US DOE.The economic and engineering risk associated with the development of hydrocarbon assets is immense. In...

Share on Social Media