The digital era of the industry: more than a desire, it is a duty

For Global Energy, July 2021 issue

The long time of the pandemic, in addition to the pain caused to many people and families, has forced us to review the way we used to think, make decisions and act. Both in our private lives and in our work, the great challenge has been to rethink the way we conduct ourselves in society and to create, adopt or adapt new work schemes, new practices to communicate and thus make the performance of our daily tasks more efficient.

The oil industry, which has been a pioneer in many changes and implementation of technologies throughout more than 100 years of history, has understood this situation, as it has experienced the havoc caused by the interruptions or closure of operations along its value chain.

One of the areas whose development has had a great growth in these times has been Data Management and the automation of equipment and processes to ensure the efficiency of the activities performed daily. Never before has the industry required the automation of its processes as much as it does today. And although we cannot deny the progress achieved in some links of the hydrocarbon value chain, upstream and downstream, and also in the supply chain of the sector, we must recognize that progress has been slow.

Despite the existence of novel experiences in the exploration and production of hydrocarbons, such as the digital well (Oil Digital) and intelligent fields, this slow progress had its consequences for many companies during this time of pandemic, where for the first time the industry in general, like other sectors of the world economy, had to close operations as people had to be physically absent from their work to minimize the risks of contagion.

Undoubtedly, the health and safety precautions created and adapted in operational activities helped to mitigate the severity of the coronavirus issue, but, even so, the impact has been devastating for many companies, mainly small, specialized niche companies, which did not have enough capital to address temporary closures, or to establish home office arrangements.

But the opportunity became a way to survive as a result of the pandemic, and those companies that were better positioned in data management, the implementation of automated systems and the transfer of information in real time, have managed to overcome, with less impact, the closures of activities and restrictions during this pandemic process, which is not over yet.

Some years ago, the operating companies had delegated this activity to service companies, and even to consulting firms that had neither the experience nor the commitment to manage the data; in that sense, the management and registration of this data in a consistent manner was very far from the best practices established for its use. This is still the case in some national operating companies.

Nothing is more damaging to a company’s decision making than to delegate this activity to a third party without proper supervision or mentoring from experts with experience in the various activities of the business. The purity or quality of data represents the foundation of information, which underpins critical decision making in any process.

If we use an analogy with medicine, a cardiologist, for example, depends entirely on the daily recording of three critical indicators to diagnose, prescribe and improve a patient: blood pressure, pulse and oxygen content in the blood, which are the indicators that allow him to make timely decisions to restore the patient’s health, and this can range from simple treatments, related to the type of food, the need for exercise and change in work habits, to open heart surgeries to repair veins, arteries and muscles, since his mission is to save a life.

Today, medicine is a pioneer in the field of data management and the use of advanced technologies to store and process it, ensure its quality and use it to make intelligent decisions. It has also taken giant steps in the use of artificial intelligence to, in some places, replace specialists in the execution of an analysis or diagnosis and even the execution of complex surgical interventions, even remotely.

In many cases the oil industry is similar to medicine, where wells, reservoirs and production facilities are the patients and optimal data management facilitates making the best decisions, analysis and proposals to ensure the design and construction of a well, to make the best real time follow up of the reservoir behavior seeking to ensure the best recovery factor and guarantee the optimal and timely transport of the hydrocarbons produced, from the wells to the batteries in onshore fields, or production platforms in offshore activities and then from there to the tank yards and terminals for their treatment, final storage and dispatch to tankers or refineries.

The care that geoscientists and petroleum engineers must take with these systems is equivalent to that of a doctor with his patient. The task is facilitated by tools such as subsurface tomography or geophysical logs, among others. Some of these are borrowed from the fundamentals or principles of medical engineering.

The lessons learned from this epidemic have managed to generate serious reflections in decision makers in companies, giving them real basis to question the efficiency of remote work even before the pandemic, the agility and updating of their technological intelligence organizations, and the acceptance of customers to recognize the cost of having new digital technologies available.

Operators and service companies are, because of this, now assigning the necessary consideration and priority to four key issues to increase their internal efficiency. In the case of operators, improving operational efficiency, and in the case of service companies, technological support and response time, to enable the respective assets as soon as possible and thus contribute to the early creation of value for their customers. These issues have to do with: data collection and analysis, automation of activities and processes, prediction and proactive monitoring, all considered elements of Artificial Intelligence.

Some companies have established Centers of Excellence responsible for the control of Artificial Intelligence issues, with the specific purpose of determining what they have, and classifying those activities that necessarily require the participation of people, and those that can be performed digitally, or robotically. The important thing for all participants in the sector is to learn the lessons from this cycle of experiences lived in times that could be described as catastrophic and to be one step ahead of the possibility of events that, perhaps, we previously considered improbable.