Full-scale adoption of data analytics and digitization in the process automation market is likely to aid in significant automation and control solutions (ACS) market growth.
Introduction:
Automation, digitization, and smart systems are not new to the oil &gas (O&G) industry. However, with tight capital expenditure (CAPEX) budgets and stringent deadlines, there is high pressure among service providers to complete the projects with increased productivity, operational efficiency, and process optimization—all at reduced operational expenditure (OPEX). A section of the energy industry that incorporates data analysis and advanced software techniques to improve the productivity of the business is known as digital oilfield. Digitization involves integration of IT services in O&G business for process optimization, improving safety, and utilization of the reserves to the fullest.
Although the digital oilfield technology has significant growth opportunities within the O&G industry, its full-scale adoption is being limited by the numerous challenges in its implementation. Some of the challenges that need to be addressed are lack of sufficient robust cyber security, lack of standardization across platforms, and conservative mindset of the top management of the end-user companies. Some ways to address these challenges are also discussed here.
If the challenges are addressed, significant growth can be expected in the near future.
Digital Oilfield:
Digital oilfield might seem like a recent concept but attempts were made by O&G companies even before 1980 to increase the productivity by implementing horizontal drilling and 3D seismic testing technology in offshore oil fields. In 2005-2006, there were advancements in wireless/smart field technology, where sensors with fiber optic cables to communicate data to the surface came about. Information such as pressure, temperature, and magnetic property of the wells was relayed to the surface systems, which helped oil companies learn about the reservoir’s properties. The next generation is expected to transform the offshore fields by bringing in 4G connectivity for reliable, high-speed communications.
Currently, the real-time data measured at remote locations is stored in computers and the operation is monitored to optimize the production of oil. These data points are obtained from sensors mounted on wellheads, pipelines, and other equipment. The computer then studies and analyzes the output data. From the analysis performed with the obtained data, important business decisions are taken to improve the productivity of the well. Through collaborative technology, control systems are connected together to a common information cloud-based network. Huge volumes of data can be accessed through the network from remote locations. Quick access to stored/real-time data from any location results in an increase in productivity and gain in process optimization, and helps managers to make quick and well-informed decisions.
Need for Digital Oilfield in O&G Industry:
According to Frost & Sullivan’s research, the decline in crude oil prices by up to 70% during mid-2014 to 2015 has resulted in many greenfield projects being shelved or cancelled. The supply-demand gap is not expected to narrow down any time before 2018. Companies had been forced to slash their CAPEX by an average of 25% in 2016 and even lower in 2014 and 2015. In this competitive market, it is important for companies to focus on providing best solutions and customer service at reduced operational costs. Due to greater concern for environmental conservation (such as reducing Co2 emission), the European Union (EU) has increased the number of safety regulations, especially for offshore operations. As a result, service providers are paying attention to providing green solutions apart from process optimization. If these challenges are not addressed, it could shrink the growth of the end-user industry. Digitization, to a great extent, can address these challenges and also provide value-added service to O&G producers.
Collaboration of automation and digitization:
Automation has evolved through the years with integration of data analytics and process automation is the most common trend observed in the O&G industry to improve process efficiency. The digital oil field encompasses both the tools and the process involved in data and information management obtained from different sectors of the industry such as upstream, midstream, and downstream. The need to build a comprehensive service portfolio to satisfy the needs of the O&G producers has resulted in collaboration of automation companies with IT companies.
From initial stages of being operated in the PC, to being used for supervisory control and data acquisition, SCADA has been under constant development for 30 years. For instance, the systems that are installed on-site are used to collect and transfer videos of pipeline transporting resources and data captured in the field to the off-site control room. Safety systems collect real-time data from acquisition systems and trigger an alarm when the safety threshold value is reached. Automated shutdown systems trigger signals to stop further activities until the problem is resolved at the field. Accidents and loss of lives can be prevented by automatic shutdown, which, in the case of offshore drilling, can save the environment as well. In remote communication technology, real-time video, audio, and data can be exchanged between offsite and onsite workers rapidly. There have been further advancements in SCADA technology; besides being used for remote data transmission, it also acts as an interface between industrial processes and business operations. SCADA is strongly believed to be a powerful tool in the future to better control processes and coordinate complex operations, which will further curb production costs of O&G.
Ways to Overcome Challenges:
The challenges and ways to overcome them are summarized as shown in Exhibit 1 following the discussion. Companies are increasingly concerned about protecting their systems from cyber attacks by unauthorized users, usually with the intent of theft, damage, or disruption of stored data. The act of protecting the storage systems with algorithms and fuzzy-logic is termed as cyber security. The environment that stores all the data is accessible through a common connected cloud network. Attacks from hackers are increasing at a rapid rate. Huge volumes of collected data may be prone to malware and cyber attacks. This makes it necessary for companies to be equipped to tackle them. These attacks can be prevented by secure network management, user identification and authentication, installation of powerful and updated antivirus software, usage of safe and effective network protocols, and firewall for endpoint security.
Control systems have to be implemented with strong cyber security technology to ensure that the network is safe and reliable, as the companies rely on the data available here for strategizing their business. Moreover, to ensure authenticity of data, effective network protocols should be built into the control system to avoid time delays or data packet losses. Network Intrusion Detection Systems (NIDS) and Dynamic Endpoint Modeling are some of the recent security measures taken. With NIDS technology, a flag is raised if any anomalies are tracked from authorized users. With Dynamic Endpoint Modeling, which is newer of the two technologies, the device behavior within the network is learnt and an alert is created when abnormal functionality is detected.
Although digitization throws the door open to several opportunities, top managements of most oil companies are skeptical about adopting this technology throughout their production processes. The reason could be that they are unwilling to experiment with the new approach as it requires more CAPEX to revamp the entire process chain. Digitization, at this point, is seen more as an expense than an investment. According to Frost & Sullivan’s analysis, among companies that have made investments in Big Data, only 10-13% use the information effectively. If embedded data were used to the full extent, the impact on productivity would be significant.
Data acquired by sensors is not standardized across platforms, or it is too complex or obscure to comprehend. For O&G, maximum efficiency and higher productivity are achieved only when the data obtained is integrated and shared by systems, sensors, and other equipment along the value chain. Standardization in terms of protocols to be used, universal sensors, and software could be set across all service providers to get the maximum benefit. The efforts to standardize will help to assure compliance with government regulations, demonstrate that oil companies can meet the needs of the global industry, and also incorporate interchangeable equipment in their designs. To reduce the resources spent on developing a company’s internal procurement specifications, the American Petroleum Institute (API) Standardization Committee provides procurement specifications for companies through its defined API product standards, quality, and certification programs. According to the publication of API, the German National Standards Body or DIN recently studied that by standardization in O&G, if the estimated CAPEX budget for this industry was $150-$200 billion annually, $200-$500 million was translated into savings.
Conclusion:
The current trend in the O&G industry is greater focus on OPEX than CAPEX. According to Frost & Sullivan’s analysis, although this industry has always been more OPEX driven than CAPEX with a ratio of 60:40 in the past, now the ratio has gradually changed to 80:20. End-user companies expect service providers to offer the best possible solution and service with brownfield projects to yield higher operational efficiency, increased productivity, and on-time project completion.
Digitization can provide all the above expected results when adopted to its fullest capabilities. There are some gaps that need to be filled such as lack of robust cyber security, introducing equipment, process and protocol standardization universally among all original equipment manufacturers (OEMs) and automation companies, and change in the conservative mindsets of top management to encourage innovation and promote digitization within the organization instead of being people centric. Data analytics and digitization need to be integrated with process automation for process optimization and to increase productivity. Significant growth for automation vendors can be expected when some of the listed digitization challenges are overcome.
