Visualization for pore pressure prediction

Joanne Wang, Duane Dopkin and Huw James (Paradigm Geophysical) discuss how visualization and interpretation of multi-disciplinary data volumes can improve risk assessment of predicted overpressures. Seismic data transformations are used routinely by geoscientists to enhance geometric features and physical property descriptions of the subsurface. These transformations can range from the application of one-dimensional operators to migrated and stacked seismic amplitude data to the application of complex transforms that make use of multiple dimensions (e.g. amplitude versus angle) or multiple data inputs (e.g. seismic inversion procedures). They can be extended with the application of linear or non-linear operators (e.g. neural networks) to relate the resultant elastic properties (e.g. impedance) to other rock properties or reservoir conditions making use of petrophysics and rock physics data. While these transformations exploit the dynamic properties of seismic data, other transforms make use of the kinematic properties of multi-offset seismic data to estimate or predict subsurface conditions. Pore pressure predictions and transformations that make use of seismic velocity measurements, for example, have had a huge impact on drilling safety and the economics of drilling design and well construction. The pore pressure models derived from the integration and careful calibration of wireline, petrophysical, seismic velocity and field test measurements provide the data needed to make critical pre-drill stress and overpressure predictions in order to secure a safe and economic well program. Because most exploration and development projects incorporate many data transformations, a heavy burden is often placed on the geoscientist and drilling engineer to integrate a broad range of data volumes and models. Although automated procedures (e.g. PCA analysis, neural network classification) are available to facilitate multi-volume integration, high-end visualization technologies and strategies often provide the most effective and informative data integration vehicles. The multi-disciplinary pore pressure prediction and transformation process that integrates seismic, well log, petrophysical, field test data with structural frameworks and directional well paths can return a wide range of deliverables (outputs) that are natural for creative co-visualization and concurrent interpretation by geophysicists, geologists, and drilling engineers. These co-visualizations are often the most effective way to understand the ‘interplay’ or dependencies of one transformation with another.