Determining Real-Time Composite Safe Maps from Multiple Digital Advisors
Authors: Kabi Bibek , Marck Julien , Germain Olivier 
Published: September 2023

The development of digital infrastructure in the oil and gas industry has led to the proliferation of advisory systems that provide recommendations in real time to mitigate a variety of risks. To deliver their full potential, these advisory systems need to coexist on a common platform across vendors and disciplines (e.g., hydraulic and pressure management, directional drilling, mechanical integrity of the drilling system, and vibration mitigation). Despite the rise of closed-loop automation, however, there is a lack for a scalable tool or platform that can orchestrate multiple digital advisors to coordinate sometimes-conflicting recommendations. Whilst industry players are well versed about determining recommendations, the conventional approach for this problem has been rule- and experience-based. That methodology is not scalable nor transferable.

Through this paper we present a framework that structures the process of determining a unified recommendation in real time by integrating the advice from multiple independent digital advisors. The novelty of the approach resides in its ability to structure the process of determining safe and robust recommendations using a scalable and computationally inexpensive algorithm that can run on standard engineering computers at the rig site and virtual-remote-operations centers.

INTRODUCTION

Digital transformation has become an indispensable and significant part in drilling engineering. The digital transformation sweeping through the industry has led to the development of a variety of applications and algorithms to help drive drilling efficiencies, offset-well learning, and automated detection and interpretation of drilling events and dysfunctions. However, this global push has led to multiple challenges, discussed below.

Different teams, divisions, entities, and companies have developed differing solutions that target similar or complementary problems, and the differing solutions may not be compatible or combinable. These solutions can rely on different methodologies (e.g., data-based, physics-based, or hybrid) and can have different technology readiness levels. Some solutions can have conflicting objectives that need to be harmonized to provide a consistent set of actions, such as advisory drilling parameters for automating operations. Typical examples are rate of penetration (ROP) that is typically to be maximized while not exceeding a technical threshold from a hole cleaning point of view, or drilling parameter targets and limits from directional, mechanical, or hydraulic objectives that can conflict as they seek to optimize different aspects of the drilling process. For instance, a vibration advisor (a case study is shown in (Greenwood (2016a,b))) can recommend increasing the rotations per minute (RPM) of the drill pipe and reducing the weight-on-bit (WOB) if a stick/slip vibration occurs. However, from a hole cleaning and pressure management standpoint it may not be advisable to increase the RPM because doing so might exceed the equivalent circulating density (ECD) limit. Similarly, to mitigate a bit bounce or whirl vibration, the advisor can recommend decreasing the RPM, whereas from a hole cleaning point of view the RPM can be recommended to be increased to achieve the target ROP under current average conditions. During such conflicting scenarios it can be difficult for a user or an automation platform to consistently determine the best recommendation from a drilling efficiency standpoint. There may not be a cohesive framework that encompasses the above challenges and the other factors that go into the well construction decision process. Also, there may not exist a common platform where independent advisory systems from different vendors and disciplines can coexist and an open composite advice produced in real time by integrating their recommendations.