Real-Time Models for Drilling Process Automation: Equations and Applications

Abstract

How good are your models? Can they be used to improve your drilling processes? These are questions often posed in relation to real-time model applications, including models integrated with drilling control. Do the models fulfill requirements with regards to accuracy and calculation speed? Can the data be applied by the models to both interpret the state of the process and provide reliable input for calculations? Can the rig equipment be used safely and securely to control the processes? This paper seeks to answer these questions and further elaborate on current activities and near-term challenges in drilling automation. While static models are generally accepted, the use of dynamic models is emerging. In real-time model applications, it has been found that rig equipment analysis is necessary to assess applicability or upgrading requirements. Controlling machines for drilling operations using outputs from models has been successfully achieved. This paper provides examples of recent developments within drilling automation, drawing from applications of closed-loop control systems in the North Sea. Challenges regarding interpreting state-of-the-process are discussed, with respect to existing rig instrumentation, while examining the need for enhanced surface and downhole sensors. Mathematical models used with the drilling control system must communicate regularly with the drilling process to extract information from sensors and provide updated control commands for automation. How sensor data is applied through models to enable automation functionality is also illustrated.

Drilling Systems Automation: Current State, Initiatives and Potential Impact

“…Very high quality downhole instrumentation and measurement systems (such as in rotary-steerable-systems) are connected by a digital backbone that extends a communication network from the drill bit to an engineer's desk in an onshore office (Pink et al 2012). While surface instrumentation has lagged in development, automation quality sensors are available (Florence and Iversen 2010;Ronaes et al 2012). Software models are being developed and tested that provide monitoring and prediction capability in real-time, as the well is drilled (Dashevskiy et al 2003;Rommetveit et al 2004;Iversen et al 2006;Cayeux and Daireaux 2009;Cayeux et al 2011;Wong et al 2013;among others).…”

Drilling-Systems Automation: Current State, Initiatives, and Potential Impact

“…Very high-quality downhole instrumentation and measurement systems (such as in rotary-steerable systems) are connected by a digital backbone that extends a communication network from the drill bit to an engineer's desk in an onshore office (Pink et al 2012). Even though surface instrumentation has lagged in development, automationquality sensors are available (Florence and Iversen 2010;Ronaes et al 2012). Software models are being developed and tested that provide monitoring and prediction capability in real time as the well is drilled (Dashevskiy et al 2003;Rommetveit et al 2004;Iversen et al 2006;Cayeux and Daireaux 2009;Cayeux et al 2011;Wong et al 2013;among others).…”

From machine control to drilling control

“…With a hoisting system based on a draw-works, the most common sensor makes a measurement of the tension in the drill line connected to the dead line anchor. The measurement itself can be quite biased as explained in [11]. The reading from this sensor is physically far away from the desired value (the top of string force) and several additional physical effects then affecting the quantity that is actually measured.…”