The oil and gas industry (O&G) has always been notoriously slow in adopting new technologies because of regulatory issues, safety measures, and rigid compliance standards. But if the sector can overcome these barriers and leverage automation technologies, such as IoT and RPA, it can:
- Lower engineering hours
- Lower data interpretation time
- Lower maintenance costs
- Increase productivity
- Lower time-to-market ratio
In this article, we aim to:
- Explain what automation in oil and gas is
- Why is the oil and gas industry behind other industries in automation
- What technologies can automate oil and gas
- What are the benefits of automation for the oil and gas industry
- What are the use cases of automation in oil and gas
What is automation in oil and gas?
Automation in oil and gas (O&G), also called oilfield automation, involves using automation solutions to improve how oil companies extract oil, build pipelines, market their products, stay compliant, and run a more efficient business overall.
What is the rate of technological adoption in the oil and gas sector?
In 2022, the automation solutions market in oil and gas industry was worth $17.5B in 2022. It is expected to reach $23B in 2028.
For context, the market size for AI banking is expected to reach $64B by 2030. One possible theory as to why this 2$T sector lacks behind in terms of automation, forcing Deloitte to give it the lowest “digital maturity ranking” amongst the 17 biggest industries, is the redtapes around it.
O&G companies have not changed how they operate because of regulatory, safety, and compliance issues. But things are slowly changing. They cannot, or do not want to, change how they operate because of regulatory, safety, and compliance issues.
What technologies can automate the oil and gas industry?
The following are some of the main technologies that can digitally transform the oil and gas industry:
1. IoT
IoT, or the Internet of Things, is the ecosystem of interconnected smart devices that have sensors in them, are capable of monitoring their environment, and their status and findings can be monitored by users.
2. RPA & Intelligent Automation
RPA, or robotic process automation, is software robots that can automate the undertaking of mundane and time-consuming tasks, thereby reducing the workload of employees and allowing them to focus on more value-driven tasks for higher efficiency. RPA combined with AI, called intelligent automation, can automate more complex tasks that require human judgment. Check our article on intelligent automation in the oil & gas industry.
3. WLA
Workload automation is a tool that can schedule or trigger the execution of tasks for increased punctuality and accuracy.
4. Process mining
Process mining is a technology that provides users with an “as-is” image of their processes to know where their inefficiencies are, what steps can be automated, and to estimate increased productivity.
5. Machine Learning (ML)
Machine learning (ML) is a subset of AI focused on creating algorithm-driven models that can learn and produce more accurate output through repeated interactions with data.
6. Digital twin of an organization (DTO)
The digital twin of an organization is a virtual replica of a digital or physical process that showcases the potential outcome of a soon-to-be-developed project before any actual steps are taken.
7. Web scraping
Web scrapers are software robots programmed to scrape websites to search for and extract predetermined information, such as prices.
What are the benefits of automation in the oil and gas industry?
A study done by BCG in 2019 argues that automation can bring about the following benefits in the O&G sector (Exhibit 1):
1. 50-60% reduction in data interpretation time and cost
Having data pipelines feeding different back-end, AI-driven ERP systems, such as automated accounting software, can ramp up the speed at which data is exchanged, interpreted, and reported to analysts and shareholders.
2. Up to 70% reduction in engineering hours
Thanks to technologies such as DTO, engineers can create simulated replicas of the ideal processes before physically building them. This feature makes engineering wells, for instance, less wasteful and more efficient by bridging the gap between the theoretical groundwork and the actual structure.
3. 20-30% faster construction
The engineers have an easier time recognizing the parts of the project, such as pipelines, that are taking longer to construct than others, thanks to sensors linked to construction equipment that monitor the construction progress and then send the information to the project engineers on visible dashboards.
The implication is that underperforming/faulty equipment, along with behind-scheduled projects, can be pinpointed and investigated, leading to quicker construction.
4. 3-5% increased production
The end consequence of the aforementioned aspects coming together will be a more lean and mean production capability, such as more effectively analyzing data or fixing any weak points—in well or pipeline construction, drilling, and oil extraction—as they appear.
5. 20-40% reduction in maintenance costs
A last benefit of automation is that maintenance costs are reduced thanks to predictive maintenance capability offered by real-time flow of information from the production silos onto the back office. Because engineers and technicians can tend to faulty equipment preemptively, the damage would be limited to the surface and operational area, thus reducing the overall maintenance costs.
What are the use cases of automation in the oil and gas industry?
The following are real-life, specific use cases of how digitization can transform the oil and gas industry:
1. Cost management
RPA bots can be leveraged to lower a company’s back-end costs. The RTP requisition to payment process, for instance, is one domain that can be automated to help reduce the workload of accounting teams. Delegating the subprocesses within the RTP—such as requisition and invoicing—to RPA bots can make them cheaper and more efficient.
Case study:
A petroleum company wanted to lower its costs to maintain its competitive advantage. The proof of concept showed that delegating RTP tasks to RPA bots could reduce manual efforts by 65-80%, expedite the RTP process by four times, and save 1,700 man-hours annually.
2. Real-time pricing
Oil prices are notoriously volatile. And with the recent geopolitical situation in Russia, they have become more unpredictable than before. Moreover, with recent international efforts to move the world economy away from fossil fuels and towards sustainable ones, O&G firms do not have much time left to maximize their earnings.
Automated pricing software leverages web scraping to scrape the sorts of data that affect the price of oil in real-time – supply, demand, prices of derivatives such as futures and options, cost of substitute products (such as solar panels or electricity), and more – that allows for a data-driven pricing strategy.
3. Pipelines and wells’ monitoring
The pricing software we mentioned above can provide a more accurate price by factoring in real-time production levels if it is integrated with IoT sensors that monitor pipeline and well levels.
Moreover, these sensors can also detect heat, vibration, and other factors that can determine the health of pipelines and wells. If deviations from usual thresholds occur, predictive maintenance can be undertaken to limit the damage.
4. Automated reporting
The price O&G producers charge is highly competitive. (OPEC countries, for instance, follow a uniform pricing strategy that discourages undercharging for market capture.) That’s why producers must release accurate reports of their production levels, revenues, balance sheets, etc.
RPA bots are again good candidates for executing tasks that alleviate the workload of the accounting teams and curate accurate and timely reports, thanks to the exchange of data between different ERP systems as they appear.
To learn more about RPA use cases in reporting, click here.
5. Regulatory compliance
Since 2000, O&G companies have been fined $53B because of 6,067 separate violations. Most of the fines are cited as “environmental violations.”
O&G companies can partner up with 3rd-party vendors that use automated software to calculate their carbon emissions, use AI/ML models to calculate their greenhouse gas emissions of their supply chain, and keep monitoring the integrated smart devices (e.g. IoT, CCTV cameras, etc) to make sure everything is aligned with environmental and safety regulations.
For more on oil and gas automation
To learn more about how automation is changing the oil and gas industry, read:
If you believe your business could benefit from business process automation, we have a data-driven list of BPM solutions.
And if you need consultants to advise you on transforming your business, we also have a data-driven list of digital transformation consultants prepared.
We will help you choose the best vendor tailored to your needs:
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