Pressure Gauge Performance Prediction in Real Wellbore Conditions for Pressure Transient Testing
Authors:   SLB, Milne Jason , Gisolf Adriaan ,   SLB, Jackson Richard ,   SLB, Tao Chen ,   SLB, Dumont Hadrien ,   SLB, Dubost Francois-Xavier ,   SLB, Partouche Ashers ,   SLB
Published: November 2024

Pressure transient testing with formation tester tools has existed for decades but was historically constrained to formations of limited thickness and permeability. With advances in formation tester technology, the permeability-thickness envelope and the tested radius of investigation have increased. Formation testers can be conveyed on wireline and drillpipe, enabling highly efficient operations. However, this can also expose pressure gauges to pressure and temperature variations over time, which can lead to gauge drift. This paper addresses the quantification of pressure gauge dynamic response and performance for improving pressure transient test design, execution, and analysis. In practice, all pressure sensors have response errors, including short-duration and long-term drift as well as temperature response effects which can impact gauge accuracy and resolution. The consequence of non-ideal pressure gauge responses can lead to uninterpretable data or to misinterpretation of reservoir effects. Reservoir engineers continue to emphasize the need to quantify the actual performance and limitations of pressure gauges in pressure transient testing in real well conditions for specific wellbore and reservoir environments. A new method to separate the dynamic effects and gauge response errors from the true reservoir response has been developed. The method hinges on a model to quantify the dynamic uncertainty in a pressure gauge’s output. This enables estimation of the error in calibrated pressure over time in response to the recent history of pressure and temperature that the gauge has been exposed to. The dynamic uncertainty model has been established by integrating physics-based modeling with over 10 years of calibration data, with short-term and medium-term drift measurements on thousands of high-performance pressure gauges passing through in-house calibration and test facilities. The dynamic uncertainty model is applied to a pressure and temperature profile provided by a wellbore dynamics simulator for a specific job sequence. The pressure transient derivative is then calculated from this simulated data together with the quantified uncertainty, yielding the worst-case impact of gauge response on the derivative plot. We demonstrate the application of this approach for several different scenarios and describe the impact of gauge performance for planned operational and test sequences. In each example, the well pressure and temperature profile are simulated for a planned operational sequence, and the gauge drift and resolution are quantified for that specific sequence for different gauge technologies. In one of the example scenarios, the gauge drift can be easily mistaken for a reservoir boundary. By changing the operational sequence, the drift impact can be reduced to the extent that it no longer impacts the simulated pressure transient response for the target reservoir zone. The ability to predict pressure gauge drift magnitude is new and unique. It is combined with a simulator to predict the gauge temperature and pressure exposure for operational sequences, creating an extremely powerful tool for understanding the impacts of real gauge behavior on pressure transient analysis. Job sequences can now be designed to maximize pressure transient value while simultaneously minimizing the risk of misinterpretation.