A Journey Through the Development of Drilling Fluids Automation System
Authors: Krishnan A. Geetha , Thompson C. , Onegova E. , Fevang F. , Postovalov S. , Razak F. Abdul , Knizhnik A. , Osgouei R. Ettehadi , Brevik J. , Jacob M. 
Published: February 2024

This manuscript presents a comprehensive account of the development and experimental validation of an automated drilling fluid mixing system. This project is a joint technology venture between Equinor and Baker Hughes. The paper explains the critical aspects of designing an automation solution for a traditionally manual-oriented workflow. The system comprises a rig site software application for creating and managing mix sheets, a machine learning algorithm that suggests chemical mixes based on fluid properties, a real-time sensor system for monitoring fluid properties, and an OPC-UA communication protocol for sharing a digital mix sheet with automation hardware systems.

The development of an automation system entails a comprehensive software application design that enables a gradual shift from manual to an automated workflow, fostering increased user confidence. The initial phase involved providing field engineers with the ability to manually create and organize the mix sheet. The second stage integrated a machine learning algorithm that allowed engineers to generate suggested mix sheets based on available products, current and target fluid properties. Once reviewed, the mix sheet is dispatched to an external automation solution for execution. Any changes made by the engineer to the suggested mix sheet are recorded to improve the algorithm. In the third phase, a real-time sensor system monitors and feeds data to the software, enabling the algorithm to generate a chemical mix in response to deviations or projected variations from target specifications. The use of OPC-UA communication protocol ensures versatility, scalability, and the seamless transmission of digital mix sheets to third-party automation systems.

The automation software system was tested in drilling fluid automation lab of Equinor located at Sandsli Automatic Drilling Fluid Laboratory, Norway with three objectives: 1) Demonstrate the usability in rig and remote operations scenario, 2) Communication with rig automation system, and 3) Verifying the algorithm output. The testing proved the viability of using the application and a seamless transition from manual workflows to automation. This also demonstrated the ability of the application to support remote operation by lowering the workload and improve efficiency. A water-based fluid system was prepared at the lab for testing the algorithm output validity. The generated mix sheet was published to the OPC-UA server hosted in the application. The accuracy of the algorithm has already been verified earlier in a lab experiment.

To conclude, the design of an automation system for the drilling fluid operations must consider the human factors, support rig and remote operations workflow and eventually capable of working in full autonomy. It must be able to communicate with other automation system via a standard, scalable and secure protocol like OPC-UA to ensure adoption. The solution developed for drilling fluid automation, the ML algorithm and communication methodology is novel in the industry and helps operators and service companies to improve service delivery quality, safety, and sustainability.