Overview
Transocean is a Swiss offshore drilling company that provides rig-based well construction services worldwide. The company is one of the largest contractors in its sector and has offices in 20 countries. It operates a fleet of versatile, mobile, offshore units comprised of midwater, deep water, ultra-deep water, and harsh environment floaters. The company decided to build a digital twin of its well construction processes to enable prediction and advanced planning capabilities with the aim of optimizing operations across its fleet.
Problem
Oil and gas drilling rigs are very complex systems that contain thousands of processes which must operate 24 hours a day in remote environments and harsh weather conditions. New drilling rig construction can require more than a billion dollars of investment. The process has lots of interdependencies and there are many different failures that can occur. As a result, the operational and financial characteristics of a system during setup and production are often difficult to predict.
The well construction process consists of several stages. Some advanced simulations of the drilling process itself already exist, but Transocean wanted to have a simulation of the whole well construction process, including the stages of non-drilling: tripping, cementing, casing, etc. The result would be a digital twin of the well construction process (read more about digital twin technology – Introduction to Digital Twin Development).
Simulating the whole construction process would help the company plan oil well optimization more precisely. Transocean would be able to:
- Choose the best rig for a certain type of contract or environment.
- Get bonuses for early work completion and escape maluses for delays.
- Be confident in their predictions when giving commitments.
- Test and analyze potential benefits of any equipment, process, or policy changes in a safe virtual environment by running various what-if scenarios.
- Optimize and improve performance with in-depth analysis of real time operational data.
- Reduce downtime and invisible lost time by indicating possible problems in advance.
Solution
Transocean decided to begin with a proof-of-concept project and to continue development if it showed satisfactory results. The company chose AnyLogic as the platform for their simulation for several reasons, including AnyLogic’s multimethod simulation modeling capability. In this project, system dynamics modeling, agent-based modeling, and discrete event modeling were combined. The engineers used the flowchart-based approach for the model with Delay blocks for high-level processes.
Vast amounts of historical data from places such as well plans, machine operations, and the time logs of Transocean’s global fleet of drilling rigs (which record data every 15 minutes) were loaded into the model. This enabled the simulation of very complex dependent and interdependent processes.
The AnyLogic platform eased the creation of the well construction optimization model with multiple levels of fidelity that could combine precise data and statistical distribution. This means engineers can work at a high-level and then dive deep down into the model’s lower levels to investigate more. For example, it is possible to test new equipment by adding data about its characteristics to the model and running what-if scenarios. The results show the equipment’s performance in the overall system and its rate of return.
The well optimization model has an attractive and user-friendly interface in AnyLogic. Users can choose a well plant, set different parameters, and adjust any of the associated machines. As a result, it is possible to see the actual processes going on in a drilling rig in real-time and obtain predictions for the construction process. It is possible to run different what-if scenarios to test new equipment or changes in the supply chain according to the real or predicted situation on site. The results are shown in Gantt charts, logs, and 2D and 3D models.
Transocean created two 3D well optimization models. The polygonal model was made for verification purposes and implemented in AnyLogic, which quickly and easily allowed the building of an accurate and clear visualization. The second model was made in Unreal Engine for marketing purposes, so that customers could see and understand what certain processes look like. The AnyLogic platform API enabled seamless integration of the AnyLogic model with the Unreal Engine visualization.
Outcome
The well optimization simulation model was a proof-of-concept project, and the comparison of the real-world well construction cases and the virtual predictions showed a very good correspondence. Moreover, the model is already able to test equipment, process, or policy changes and compare the capital expense and reduction in operating expenses due to these changes. It shows how the company can save working days (each of which could cost Transocean several millions of dollars) and has boosted income by enabling more wells to be drilled per year. Furthermore, it has also helped improve safety by showing management when it is possible to remove people from dangerous zones without causing problems.
Now Transocean is planning to bring in more expertise and enhance the model with regards to:
- Adding more interruption events to the model (failures to function or operate, equipment failures, weather events, dynamic downhole conditions, etc.).
- Improving overall architecture with simplified logic and making it well and drill agnostic.
This project proved the efficiency of AnyLogic software in the offshore oil and gas domain.
You can download Jason Baker and Abe Hudson presentation from The AnyLogic Conference.