Digital Well Construction with Mud Motor Applications

Abstract

It is often essential that the behavior of certain tools inside of the bottomhole assembly (BHA) be understood, prior to automating the well construction process. The mud motor is one of the most frequently used BHA components worldwide. This paper presents several digital well construction procedures in which a mud motor is located inside of the BHA. Mud motors can be directly used in a steering mode or can be combined with the most advanced rotary steerable system (RSS) tools in power only mode because their downhole power ability is unrivaled, and their usage reduces the power needed from surface, making the well construction more sustainable. When considering the six primary surface measurements of well construction (hookload, block position, torque, rpm, pressure, and flow), the interpretation of four of the measurements is directly affected by the presence or not of a mud motor inside the BHA, whether the mud motor is in steering mode or in power only mode. To understand these measurements, a basic understanding of the mud motor physics is required. This paper will present some of the kinematics of the mud motor power section and how it relates to the monitoring, advising, or controlling of the drilling process. In particular, some key equations will be shown that correlate surface measurements to the downhole drill-bit motion through the motor physics. It will be shown that when a mud motor is present, there is a torque discontinuity between the upper portion (above the motor) of the BHA and drillstring and the lower portion of the BHA (below the motor). In addition, equations to fit mud motor power curves are derived, which enables interpretation of the motor power section performance based on the chosen configuration. The acoustic impedance theory for the mud motor will also be shown, which enables understanding the transient effect of flow fluctuations when different torque demands from the drill-bit exist. All these derivations are included in a new mechanical specific energy (MSE) calculation which will be used to derive an autonomous well construction scheme. A novel approach to understanding the monitoring, advising, and controlling of the drilling process when a mud motor is present within the BHA is presented. This approach, which is based on the careful understanding of the mud motor physics and enables automation of the well construction, would be a forerunner for most artificial intelligence (AI) and machine learning (ML) algorithms used to optimize drilling operations when a hydromechanical power generator is present in the BHA.