For years, the oil and gas industry has been slow in adapting to the new digital on account of their outdated, complex supply chains and unutilized data. Demand and price volatilities have remained its Achilles’ heel. Post COVID-19, it’s confronting several issues on many fronts, from stabilizing production, optimizing operational costs to ensuring employee well-being. Factors such as controlling emissions and managing an aging workforce seem to compound risks. Amidst these shaky circumstances, intelligent process automation is the linchpin to driving digital transformation in the oil and gas industry.
Meaning and Significance of Intelligent Process Automation
Intelligent automation is creating a paradigm shift in ways various industries operate. An umbrella term, which covers technologies of Robotic Process Automation (RPA), Artificial Intelligence (AI) and Machine Learning (ML), and Natural Language Processing (NLP), it is dramatically redesigning processes to reduce manual labor and transforming how humans collaborate.
Most organizations act on RPA, as a starting point, to automate routine, rules-based tasks. Later, while drawing on self-learning, they strive to expand on RPA by:
- Integrating AI and Machine Learning algorithms
- Introducing orchestration and governance layers
- Incorporating functional and industry expertise into automation initiatives
The end result, therefore, is intelligent process automation, enabling digitization of rules- and judgment-based tasks. This allows leaders to reap long-term benefits, which include effective asset utilization, augmented production, improved employee experience, higher safety, faster compliance, and ongoing profitability.
The oil and gas industry sits over a wealth of data. Devices such as logging tools, sensors, and geophones generate diverse data sets that hold transformative value. Digital enablers like intelligent process automation offer a way to leverage these streams of data for key insights and delivers enterprise-wide connectivity. It is emerging as a critical cornerstone of digital transition across upstream, midstream, and downstream oil and gas operations.
Growth of Intelligent Process Automation in Oil and Gas and Other Industries Globally
Research has claimed that over 72% of oil and gas firms are dissatisfied with their existing manual processes. Leaders are coming at the forefront of adopting RPA and other leading automation technologies to digitize their cores and deliver tangible results in the long term.
According to the Deloitte Global RPA Survey, over 53% of enterprises have already begun RPA journey, and that top adopters have earned 4X on their RPA investments, while others 2X. It has also been predicted that if the RPA growth trend continuous, it will achieve ‘universal adoption’ status in five years.
The AI in the oil and gas market was valued at USD 2,040.89 million in 2019, and it is predicted to grow at the CAGR of 10.15%, reaching USD 3,554.56 million over the forecast period 2020-2025.
A recent Institute of Business Value (IBV) survey has revealed that intelligent automation is making its way into the mainstream and that over seventy-six percent of respondents coming to realize its potential for constant value. Half of the operation executives, in the same survey, agree to the fact that NLP will introduce advanced cognitive capabilities to man-to-machine interactions, thus fostering understanding and trust like never before.
A Markets and Markets’ report has estimated that the global intelligent process automation market will grow at a CAGR of 12.9%, reaching USD 13.75 billion by 2023. This growth is attributed to many accelerators, including the spurt in demand for automated workforce functions and the integration of recent technologies with automation.
RPA Use Cases in Oil and Gas
- Typical: There are many aspects ripe for RPA adoption across oil and gas supply chains. See the figure to know the spots of opportunity where RPA is set to unleash value across downstream, midstream, and downstream oil and gas operations.
- Immediate: RPA holds the power to transform cross-company corporate functions such as HR, Finance, and Supply Chain Management. These opportunities can be immediately leveraged to drive rapid digital transformation. See the figure below.
Scope of Intelligent Automation in Oil and GasMost enterprises start with Robotic Process Automation (RPA) to automate tasks that lack variation. But starting with intelligent automation is a different ball game, and hence, we are discussing intelligent automation use cases in oil and gas separately.
Now that we are clear about the differences between IA and RPA, let’s go through the use cases of intelligent automation in the oil and gas industry and learn why it’s the ultimate game-changer.
- Upstream Oil and Gas
Upstream value chains are largely characterized by complex field activities and high capital intensity. Priorities to improve exploration, return on assets, and employee safety remain on the top. With intelligent automation at the forefront, oil and gas players can:
o Scan and identify acreage opportunities, drive subsurface modeling, and improve drilling performance.
o Dismantle silos and allow data analysis to enhance decision-making for field engineers.
o Integrate traditional well modeling applications.
o Enable information flow via AI-led bots and search optimization engines for field staff
- Midstream and Downstream Oil and Gas
Akin to upstream oil and gas, midstream and downstream operations have a keen interest in adopting intelligent automation.
o Use cases across activities such as inventory management, plant equipment downtime management, contract management, logistics monitoring, and coordination are emerging at a rapid pace.
o NLP- and NLG-led automated conversations can drive marketing and sales teams’ outcomes.
o Connected technologies around vision, intelligence, and conversation have made a place for themselves in COVID times, as the need for remote work increased substantially.
- Environmental and Social Impact
Oil and gas companies have grappled with the difficulty of minimizing the environmental and social impact. Using intelligent machines, they can:
o Monitor hazardous emissions and leverage predictive analytics to get real-time forecasts of emissions.
o Forewarn EHS personnel and avert incidents in case the emission breaches the predetermined threshold.
o Transform damage control from reactive to proactive, thus controlling the expensive environmental and social impact of the industrial emission.
The Road to Implementing Intelligent Automation for Oil and Gas CompaniesIt is important to emphasize that realizing the value of intelligent automation isn’t as easy as investing into the right spots of opportunity. Learning from our core expertise and the industry’s best practices, we underline four recommendations for implementing and scaling intelligent automation for oil and gas value chains.
a. The need for a pragmatic approach to planning, organization, and deployment can’t be overstated enough. Leaders must identify the viable scope of IA implementation to align investments with business strategy, competencies, and objectives.
b. Oil and gas players must refrain from force-fitting intelligent solutions to existing structures. It is important to optimize the right processes for IA and reach the magnified growth potential.
c. IA must be implemented for the core and support functions separately. Emphasis should be more on upstream and midstream activities.
d. A strong focus has to be laid upon nurturing multi-disciplinary skills and redeploying personnel so that they can be comfortable while operating around the expanding digital landscape.
Intelligent Automation in Oil and Gas: Awakening to a New Era
As oil and gas industry paves a new strategy for the future, digital is the lifeblood for the companies. With its direct impact on changing core bottom lines and spark breakthrough efficiency, intelligent automation has emerged as an indisputable agent of change for the entire oil and gas value chain. It is the moment of truth facing the industry that has long striven to be a leader from a laggard. The time is ripe for exploring innovative possibilities with intelligent automation and driving a holistic change across the board.