Reducing Time Losses in Well Construction Operations by Improving Early Detection through a Digital Operation Integrity Center and Digital Aids
Authors: Al Fakih Abdulqawi M. , Dorantes Arnott Dorantes , Perez Carlos Alberto , Duque Gerardo Javier , Dewidar Mohamed Nabil , Nafi Mohamed Khalil 
Published: March 2023

Optimizing well time and its expenditures have become a necessity for which all drilling operators and service companies are challenged on. This requires a combination of well engineering and operations efforts, from avoiding service quality issues that lead to Non-Productive Time (NPT) to reducing or eliminating Invisible Lost Time (ILT). Traditionally, more focus and efforts are concentrated around NPT avoidance, as its impact is visible and has a huge and direct financial consequence that leads to an impact on well cost. The ILT was left out of focus due to needing proper measurement tools. In turnkey projects, the real-time monitoring concept was adopted to reduce the ILT and, at the same time, the NPT.

From 2018 to 2022, the time interval selected for this study, nearly 800 wells were drilled with good progressive performance of feet per day (Ft/day) year on year and continuous reduction in NPT impact. The performance was measured on 40,000 days of operating time which was impacted by almost 5,000 days of related non-productive time. The multi-hour loss events were classified according to their root cause, divided into four major categories, hole condition, human decision, tool failure, and other external (i.e., waiting times). This paper will describe the solution for the first two causes categories of time losses.

During the problem definition process, a common factor was the criticality of having a short response time at the early stages of the events. The evidence showed a direct correlation between the response time and the total lost hours in any event; hence the efforts focused on reducing the time between early detection and execution of corrective actions. Implementing an Operational Integrity Center aimed to standardize the detection of events and establish a central support team that will recognize wrong actions and recommend corrective actions quickly. The Center integrated multiple digital solutions to maximize the accuracy and reliability of predictions.

The introduction of the digital operation integrity center (DOIC) resulted in a 30% reduction in the global NPT in terms of the number of days up to the end of 2022, considering the increasing operating time. This success is based on three major pillars: process, people, and tools.

In terms of process, the team established a new set of processes (SOP)to monitor operations and set an iterative do-learn-improve cycle. Those processes have enhanced the workflows of transforming data into insights and delivering these insights to Well Site Leader (WSL), reducing the response time.

In terms of people, the team was trained in process assurance, digital tools, event detection, stress management, and effective communication; the training focused on reducing the response time after identifying signs of possible events.

The final pillar was implementing digital tools; the DOIC used monitoring and prediction tools. Monitoring tools are well known and have been used for many years to detect early signs of problems and deviation of trends from the drilling program; however, these tools rely majorly on human interpretation, becoming susceptible to bias or noise. Predictive tools will resolve the human impact since they are based on algorithms, and the new generations of algorithms have a certain level of interpretation. These tools have been identified as the major step toward reducing the response time to signs of events and increasing the reliability of the alerts. The new version of predictive tools is being introduced and trailed one by one in DOICs based on their maturity and business needs.

The manuscript describes the methodology to implement a Digital Operation Integrity Centre, the lessons learned, and an in-depth view of the digital tool's capabilities to increase the prediction of events and their capability to advise on corrective actions before the event happens.