DGI Blog

Reservoir teams obtain a better understanding of well production when real-time well monitoring data can be acquired and visualized in context of the geologic formations and changing reservoir conditions. Based on this information, engineers can assess the effectiveness and efficiency of current production strategies and continually make adjustments to optimize recovery.

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.

Time is a crucial factor when maximizing hydrocarbon assets for all team members involved, especially when operating under tight deadlines. Analysts must develop viable extraction strategies to recover upfront costs while making a healthy profit. Engineers need fast and accurate analysis that will hasten the development phase, leading to efficient extraction campaigns in the short-term.

Subsurface data analysis requires software that offers great flexibility. In terms of visualization, a precise level of detail is required, especially when magnifying spatial data. To obtain further analysis, it’s often beneficial when a software package has temporal features that allow users to examine subsurface conditions ranging from milliseconds to years.

Reservoir engineers build reservoir simulation models from geological models, well logs, seismic data, oil and gas production data, and with a good dose of intuition. They must iterate the model building process to generate models that best match the production history. Often, they will generate a collection of models, each matching the production history.

From interpreting seismic surveys that identify the most promising hydrocarbon resources to monitoring daily fluid and pressure metrics, there are dozens of factors and activities that impact oil and gas production. Yet, the biggest challenge for asset teams is finding the means to holistically evaluate these factors, explore their interdependencies, and make modifications to optimize production.