Geospatial Visualization of Well Log Cross-Plot Data

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Cross plot of two logs from hundreds of wells. A small correlation is shown. Outliers are easy to spot as well.

Cross plot of two logs from hundreds of wells. A small correlation is shown. Outliers are easy to spot as well.

A cross plot of well log data is essential in establishing the accurate correlation between the well parameters. Not only does it help in understanding the reservoir behavior and its quality, but data interpreters can also utilize this to examine the productivity of the well. However, 3D interpretations of cross plots can be significantly challenging, especially when looking at opens in a new window big data. Engineers and geoscientists can be looking at thousands of wells and their corresponding data to gather information on subsurface geological characteristics and make predictions about well performance. The risk of discrepancy in the geospatial analysis of big well log data can be minimized with the help of a visualization tool that can ideally integrate different data and models in an efficient manner.

Accurate Geospatial Interpretation with Cross-plot

Well log data play an important role in opens in a new windowcharacterizing the reservoir. The logs collected from different techniques provide data regarding density, gamma ray, sonic, photoelectric, resistivity, and neutron porosity. Often, this data acts as a supplement to one another. Cross plotting is a way to establish the correlations between these data. The plotting of multiple data types helps interpreters to see the trends and identify the outliers and relative variation in the data, facilitating enhanced understanding of the rock properties and reservoir behavior.

Traditionally, the 2D interpretation of a cross plot, in log form, has been the ideal method of analysis for reservoir engineers, geologists, and geophysicists. However, when big data is involved, the 2D cross plot might provide incomplete opens in a new windowanalysis in understanding the multi-faceted correlation. To get a more accurate geospatial picture of the reservoir, opens in a new windowwell log data can be tied with a 3D opens in a new windowgeological model of the subsurface. The data and anomalies can be visualized and filtered in their correct geospatial location, providing asset teams an enhanced understanding of the reservoir quality.

Visualizing the Well Log Interrelation

Well log cross-plot data is an efficient way of analyzing log responses to identify the correlation between multiple rock properties and their attributes. For analysis, team members can look at a cross plot between neutron log porosity vs. density log porosity, for example. This plot can be used to identify the presence of shale or sands or hydrocarbon-bearing zones in the reservoir. In the petrophysical study, well-log cross-plot data when integrated with a 3D geological map can help in identifying the accurate geospatial location of the data and its effect on the quality of the reservoir.

With the aid of software platforms like CoViz 4D and EarthVision, cross-plot analysis is much more efficient. It facilitates:

  • Integration and visualization of the massive amount of well log data with a 3D geological model for enhanced well log cross-plot data analysis
  • Filtering of multiple attributes, including well log attributes, while the plot updates simultaneously
  • Analysis of the effect of multiple parameters in context of well performance and reservoir quality
  • Identification of inter-well correlation and data outliers
  • Analysis of rock properties and examination of producible reserves

CoViz 4D and EarthVision: Enhancing Geospatial Understanding with Visual Analysis

CoViz 4D and EarthVision—ideal geospatial analysis software packages—are capable of easily cross plotting well logs, and many other types of reservoir data, and combining them with a 3D geological model. CoViz 4D can import .las files in the proper depth location along a wellbore trajectory to get a 3D property scattered data file, such as in a .pdat format. This .pdat file is much smaller and can be easier for data interpreters to manage. The “lasso” feature allows the selection of data points, to highlight while displaying in the 2D cross plot and the 3D viewer at the same time to see the data distribution within the 3D model. With EarthVision, data interpreters can take a 3D geological model, and label the data on a zonal basis. This data can be filtered and only the output of interest can be viewed in the cross plot. This allows engineers to conduct in-depth analysis which provides the benefit of making comprehensive development plans efficiently in less time.

EarthVision, and CoViz 4D from Dynamic Graphics, Inc., offer oil and gas professionals the leading solution for 3D analysis and visualization of well log cross-plot data. These powerful visualization tools allow data visualization in its actual geospatial position, facilitating better well planning and operations in a timely and efficient manner. To learn more about EarthVision and CoViz 4D contact our team.

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