DGI Blog

Lithologic distribution—shale, sandstone, silt, etc.—has a major impact on the recoverable reserves in unconventional reservoirs. Many of the most successful unconventional plays, such as Williston, Permian, and Anadarko Basins rely on thinner conventional reservoirs embedded in the major source rock shales for their most prolific portions of the play.

One of the essential aspects of visualization is the ability to view and analyze the data and information in many different platforms at varying scales. 2D, 3D, or 4D seismic data analysis involves the interpretation of a large volume of subsurface attributes. While a more complete analysis and visualization requiring collaboration may use visualization centers for better results, smaller platforms such as laptops can be sufficient when scaling 3D seismic data for visualization and analysis. The ability to integrate non-seismic data into the interpretation in its correct geospatial position, process, and scale them for any size visualization platform provides interpreters the unique opportunity to view the data in 3D or 4D while collaborating with multi-discipline asset teams.

When it comes to hydrocarbon exploration, risks are inevitable; there’s no way to completely eliminate risks but there are ways to reduce them and optimize asset production. One such mitigation strategy is 4D seismic monitoring of reservoir change.

Doglegs are a fact of life in most/many well planning and drilling operations. Properly planned and drilled, doglegs are part of an optimized wellpath, avoiding problematic formations and maintaining the right drilling angle to reach the pay zone. Many factors influence whether the dogleg location and curvature are appropriate or undesirable.

With so many oil and gas software applications and so much multidisciplinary data to analyze, it can be cumbersome sharing vital information across disciplines. Many have found a solution in the collaboration of data visualization software, Python, and Jupyter Notebook, which makes it easier to organize data and share and document custom workflows.

With the proper instrumentation, a wide range of logging data can be acquired during and after the drilling process. Open hole data acquired before casing the wellbore is generally used by production engineers and geoscientists to gain a better understanding of key subsurface and reservoir characteristics. A large volume of log data collected helps engineers and geoscientists to develop a well-informed completion strategy.