In this presentation we will look at using digital data for detecting symptoms that often lead to drilling problems such as poor hole cleaning, fluid influx, mud losses, hole collapse, and/or stuck pipe.  This technique requires performing advanced torque and drag, thermodynamic and hydraulic calculations in real-time.

These Engineering-While-Drilling calculations are similar to predrill torque and drag and hydraulic modeling, with the added complication that they are performed and calibrated in real-time.  These calculations continuously provide the drilling team with a narrow band showing a range of acceptable values for the surface and downhole measurements being digitally recorded.  These calculations were not possible previously, because the required computing power did not exist to solve the complex finite difference equations nor was there a method to automatically calibrate the model in real-time.

Today it is possible to build a single model that dynamically links the transient mechanical, thermodynamic, and hydraulic effects with each other, and to compensate for the not-so-well-defined model parameters through automatic calibration of those parameters.  This Engineering-While-Drilling delivers the following benefits:

• Provides a Baseline for quality checking of the sensor data on the rig in real-time,
• Provides the Capability to detect symptoms that often lead to serious drilling problems (based on deviations from the modeled ideal baseline),
• Provides the Foundation for adaptive drilling automation. (Automated control of the drilling equipment based on changing hole conditions)

In this presentation we will show a number of case studies documenting this new methodology for the detection of symptoms that lead to drilling problems.