Modeling-and-simulation software that is used in the design and development of drilling equipment provides testing and redesigning of offshore machines early in the product-development process. Typically, models of offshore equipment are complex and suitable only for offline simulations that allow testing of just predefined functions of the system without the possibility of controlling it with the operator's inputs in real time (RT). This is related to the fact that, usually, complex models put high demands on the computational power of the simulator hardware and, thus, limit its RT performance. On the basis of the authors' observations, it is concluded that RT performance can be difficult to achieve even on modern computers because of the stiff nature of hydraulic mechanical models and high demands on computational power. Therefore, it is often necessary to optimize complex models of drilling machinery for RT operation to extensively test its real control systems in a virtual-modeling environment. The methodology presented in the current paper provides for controlling a virtual model in RT by means of full-scale control hardware and software. This, in turn, allows for performing a hardware-in-the-loop (HIL) test and evaluation of developed control algorithms early in the machine-design phase as well as verification determining if the chosen control equipment meets the desired specifications and performance.

The current work presents an efficient way to optimize large, high-fidelity models of offshore drilling equipment. First, a complex virtual model of the selected hoisting system is created, and its simulation results are compared with the reference data logs recorded on a full-scale rig. Second, rules and guidelines for conversion of a complex model to a low-fidelity model that could be simulated in RT are formulated. Simulation results prove that both high- and low-fidelity models of the analyzed cylinder hoisting system yield comparable outcomes that correspond satisfactorily to the reference real-world rig measurements. It is concluded that, to simplify a model, it is important to determine how its particular components affect the computational efficiency of the simulation hardware and to clearly understand the functions of the machine under consideration.

The paper contributes in two areas. First, a high-fidelity virtual model of an existing hoisting system is established and validated against real measurements from the offshore-drilling rig. Second, such a complex model is simplified and confirmed to be applicable for RT HIL simulations. The results of the current work can be successfully applied to evaluate and examine real control systems in a virtual-simulation environment, to reduce the need to conduct costly on-site tests on full-scale equipment and reduce the time spent by control-systems engineers offshore, as well as to shorten commissioning time and product-delivery period.

You can access this article if you purchase or spend a download.