Schlumberger announced at the 2016 SPE Annual Technical Conference and Exhibition the release of GeoTesting geology-based well test design and interpretation services.
GeoTesting services, built in the Petrel E&P software platform, maximize the value of well tests by integrating geological and geophysical models with dynamic well test data in a shared earth model for more accurate interpretation compared with conventional analysis limited to geometrical models.
“GeoTesting services bring a new level of certainty to reservoir characterization with optimized well test designs that validate and calibrate reservoir models using dynamic measurements,” said Wallace Pescarini, president, Testing Services, Schlumberger. “With high-quality data and analysis representative of the reservoir, customers can vastly improve production forecasting, determine reservoir connectivity and identify sweet spots.”
The Petrel GeoTesting plug-in features Global Sensitivity Analysis designed for targeting geological features of interest and incorporating uncertainty in the geological model during well test design and execution—maximizing confidence in the data while minimizing well test duration and cost.
New grid-based inversion technology automatically calibrates reservoir models with dynamic well test data for direct integration into the reservoir model, enabling more accurate reservoir characterization. In addition, the naturally fractured reservoir pressure transient simulator provides new insight into the complex behavior of transients and the matrix–fracture interaction, which is critical for field management in carbonates and unconventional reservoirs.
Operating in the Norwegian Barents Sea, OMV used GeoTesting services to characterize a geologically complex reservoir, which presented many challenges including proximity to nearby faults, oil/water contact, uncertainty in fault conductivities, permeability and anisotropy. Success was achieved using GeoTesting services to optimize the well test design and calibrate the reservoir model with dynamic well test data—establishing confidence in the final model and confirming reservoir connectivity.