We have seasoned subsurface professionals who aim to deliver best-in-class technical analysis by leveraging the knowledge and expertise gained through participation in oil and gas projects for E&P companies in the United Kingdom, Europe, the Middle East, Africa, Latin America, and North America.

We have taken all this knowledge and experience to the next level with Sweet Characterisation™, Strados’ service for integrating and reconciling geophysical, geological, and well-test data interpretation models to enhance the characterisation of complex geological reservoirs.

Formerly, information on the extent and configuration of reservoir boundaries was only obtainable through seismic and geological data but not through the traditional, simplified well-test interpretation models. In routine well-test analysis, engineers derive well and reservoir parameters from pressure data such as wellbore storage coefficient, skin, and permeability-thickness product. However, they often do not consider the data after the radial flow derivative stabilisation, ignoring the information they contain.

The uncertainties associated with the static data require validation from dynamic data. Such validation is possible when the assumed reservoir-description simplifications for deriving analytical well-test models are consistent with the reality of reservoir settings but not so likely with geological complex reservoirs. That is the case of extensive intersecting networks of eroded meandering channels with crevasses and splays represented in well-test analysis with two parallel impermeable boundaries of infinite extent.

However, during the last two decades, the well-testing discipline has developed geologically complex enhanced models and advanced interpretation techniques. Ground-breaking well-test data interpretation models, deconvolution techniques, and widespread used down-hole pressure gauges have made it possible.

With our Sweet Characterisation™ services, you can realise the full value of your enterprise data from multiple monitoring and surveillance systems across all geosciences and reservoir engineering disciplines into a unified view and increase decision support across disparate upstream disciplines.