Embracing Digitalisation for Oil Industry Growth

As the global oil and gas sector witnesses sweeping changes occasioned by technological incursions, stakeholders have stressed the need for Nigeria to adopt Artificial Intelligence and Big Data solutions to bring about efficiency and enhanced operations in the nation’s oil and gas industry, writes Peter Uzoho

Last week, stakeholders in the Nigerian oil and gas sector were in Lagos for the 43rd Annual International Conference and Exhibition organised by the Society of Petroleum Engineers (SPE) Nigeria Council.

Deliberations at the three days programme focused on the theme: “Artificial Intelligence, Big Data and Mobile Technology: Changing the Future of the Energy Industry,” which was followed by a number of sub-themes at different panel sessions.

For speakers at the event, Nigeria should not to be left behind while other countries are fast shifting to technology as a new way of running their oil and gas industry.  They were of the view that Nigeria should embrace artificial intelligence and big data in order to optimise its oil and gas potential.

Nigeria currently produces about 1.9 million barrels per day (bpd) of crude oil, has about 37 billion barrels oil reserve, coupled with about 197 trillion standard cubic feet (tscf) of gas potential. 

This makes the nation a major player in the global crude oil and LPG market.

Nigeria is an oil-dependent nation with the oil and gas sector contribution about 80 per cent to the country’s Gross Domestic Product (GDP). The implementation of the country’s annual budget depends majorly on income from the proceeds of oil – it is the country’s cash cow, the most controversial and most sort after sector of the economy.

However, Nigeria, unlike its fellow oil producing nations, has not had the full benefit of its hydrocarbon potential due to various factors.

Whether in the upstream, downstream or midstream petroleum sub-sectors, challenges abound, thus the need to evaluate, adapt and embrace new technological initiative to lift the sector from its current quagmire.

For instance, there is this perennial argument about the quantity of crude lifted and what is accounted for. There is always controversy about the amount of petroleum products that leave the depot for a destination to what actually gets to the designated point. 

Oil bunkering has for long become a normal activity around pipeline locations with no solution to that. Fuel pumps at petrol stations are adjusted at will by attendants to cheat Nigerians with no end on sight. There is high opacity as to what transpires at the fields of oil operations.

Reports by the Nigerian Extractive Industries Transparency Initiative (NEITI) about huge losses recorded in the nation’s oil and gas sector abound. Some of these if not all could be solved by simple and purposeful adoption of right technological mix, as being done by some oil companies in other countries.

Saudi Aramco Example

While declaring the SPE annual conference open, the Permanent secretary, Ministry of Petroleum Resources, Dr. Folasade Yemi-Esan, said the ministry during its visit to Saudi Arabia earlier in the year, “discovered that Saudi Aramco has been utilising big data in its upstream business for years, and has implemented several advanced analytic solutions including operational, predictive, analytics.

“Currently, Saudi Aramco is also testing several advanced analytics and big data solutions.”

Yemi-Esan was right. Saudi Aramco’s petroleum upstream has been capitalising on the fourth industrial revolution which is driven by Artificial Intelligence, Big Data and Internet of Things (IoTs), to find breakthroughs that would increase discovery and recovery, reduce costs, enhance safety and protect the environment. 

From the use of autonomous underwater vehicles to revolutionise seismic data acquisition, to employing AI, deep learning, IT smart agents and big data mining to place wells more effectively and help correct abnormal performance in real time, Saudi Aramco has charted its leadership path in the world’s petroleum upstream digitalisation space.

Notably, the firm has launched GeoDrive – a seismic imaging software package designed for exascale computing, which would improve image-processing efficiency by 90 per cent, that would be helpful in areas with challenging and complex geology. 

The permanent secretary who alluded to a projection that the AI market in the oil and gas was estimated to reach approximately $2.85 billion by 2032, with a compound annual growth rate of 12.66 per cent, added that the growth, “is due to the adaptation of big data technology hence, artificial intelligence requires big data for efficiency.”

She said: “On changing the future of the energy industry, AI most certainly will impact on the sector in numerous ways. Therefore, the proliferation of AI in the oil and gas industry will lead to the development and revolutional transformation of application and task such as decision draining, reduction optimisation, reservoir management, inspection and oil and gas station monitoring, among others.

“Beyond all these benefits of AI, there is a need for capacity building in respect of this technology both to understand and to enhance the application in the oil and gas industry. 

“This is very critical and desires maximum priority. And so, I will like the national oil companies (NOCs) and the international oil companies (IOCs) and also the ministries, departments and parastatals (MDAs) of government to collaborate to bridge this skill gap required for effective utilisation of AI, especially at the policy and regulatory level. 

“I think this is the bedrock upon which operators and other stakeholders can lean on. I wish to conclude my remarks with a call on business leaders in the oil and gas industry in Nigeria to embrace artificial intelligence by learning from those who have succeeded and commit huge investment into the technology.

“On its part, the Ministry of Petroleum Resources will look towards developing policies for the mainstreaming of AI into the oil and gas operations in the country in a way that is fully sensitive to its likely impact on the labour market, and clearly defining the role that AI will bring to current and future jobs.”

NNPC’s Resolve

On his part, the Group Managing Director of the Nigerian National Petroleum Corporation (NNPC), Malam Mele Kyari, said the corporation would leverage technology and innovation to achieve the goal of building energy company of global excellence.

According to him, technology and innovation would, “permit us to test new ways of achieving better results, but the validity of such endeavor will depend squarely on the availability of quality data which will ultimately support the deployment of Artificial Intelligence with the overall effect of delivering more efficient and perhaps cheaper solutions.”

Mele Kyari added: “We are determined to improve transparency, accountability and the overall performance of our businesses to deliver maximum value to our stakeholders including 180 million Nigerians.

“Today, Artificial Intelligence is leading digital transformation across the oil and gas industry, from exploration to production and facility management. And many oil companies have taken advantage of this to enhance operations reliability and profitability.  

“Technology and innovation will therefore continue to shape the way we do our businesses, especially in the deep offshore and other hard to operate environments.

“Finally, artificial intelligence, big data and mobile technology will continue to shape our industry in practically unimaginable ways, but certainly the transformations it promises will lead to quantum shift in the delivery of our task”.

Tackling Risks

In his submission at a panel which focused on the topic; “Transforming Big Data and Technology to Business Value: Challenges and Strategic Options,” the Executive Operations Director at Seplat Petroleum Development Company Plc, Mr. Effiong Okon, said right adoption of contemporary technologies like AI, big data and mobile technology would not only drive planning and forecast in the Nigerian oil industry, but would help in addressing risks associated with the business.

Okon stated that leveraging cloud computing and big data promotes accurate forecast of oil production for planning, which in turn drives operational excellence –production optimisation and asset performance.

“The use of predictive and data-driven maintenance for production and cost efficiency has helped to reduce Mean Time To Repair (MTTR), and increase Mean Time Before Failure (MTBF) in the industry.

“For drilling, operators can get predictive analysis through smart drilling; guarantee early identification of drilling anomalies, hazards to well control problems; develop more Enhanced Oil Recovery (EOR) techniques; and real time data through Logging While Drilling (LWD) and Measurement While Drilling (MWD)”, he said.

He added that in the area of exploration and appraisal, technology had made it possible to obtain big data from sensors attached to equipment used during exploration/appraisal activities (seismic, wells), which would further help in improving subsurface mapping and new well delivery performance through micro-seismic 3D imaging.

According to him, “With the right technology, we can identify rock and fluid properties through Magnetic Resonance Imaging (MRI); locate new oil fields through Wide azimuth towed streamer (WATS) Acquisition; and analyse big data through Ground Penetrating Radar (GPR) for cost efficiency.

“It also applies to oil/gas transportation while connecting pipelines, sensors, leak detection, alarms and emergency shutdowns; using drone technology for pipeline surveillance.

“Internet of Things (IoT) is revolutionising midstream pipeline operations through Supervisory Control and Data Acquisition (SCADA)-based applications.”

The Seplat ED added that in the area of refining, operators can now analyse economic indicators and weather patterns for forecasting demand, pricing and resource allocation while optimising integrated refineries and leveraging machine learning for predictive analysis and self-diagnosis by refineries.

Okon added: “These technologies have a huge role to play in the future of the oil and gas industry. The need for smart, cost efficient ways to access unconventional reservoirs is undoubted. 

“It requires the combination of technology and thinking that redefines how firms manage and execute a more harmonised approach to early well life. As drilling projects grow in ambition, smarter equals faster.”

Fixing Friction

Also speaking at the conference, the Founder and Chairman of Fasmicro Group, Prof. Ndubuisi Ekekwe, said Nigeria needs to leverage opportunities offered by AI and big data to fix perennial lapses in the downstream sector of the nation’s oil and gas industry.

Ekekwe noted that even in the age of digital technology, Nigeria was still grappling with the problem of having petroleum products siphoned on-transit due to inability to digitally monitor the movement of the product from the depot to a designated location.

The professor, who said the government only tracks the movement of petroleum products from depot without knowing if it actually gets to the final destination, described that as a paralysis that must be fixed using big data.

He said: “So, let me go down to the downstream sector in Nigeria. We are still in the ecosystem where somebody loads a truck of gasoline from a depot in Lagos going to the northern part of Nigeria, now siphons that to Togo or one of the neighboring countries to Nigeria.

“What largely the government does is to track a truck going to northern part of Nigeria while the gasoline has already been sent to Togo.

“The exit truck will actually get to Kaduna or Bauchi but the gasoline is actually being used in Togo. This is a paralysis. It is a paralysis because they have not utilised a very critical tool that is not justrunning entities but also transforming entities. “Information technology is used to run companies but big data is going to be used to transform companies. And until you can transform entities through efficiency in understanding what is happening in those entities you cannot improve them.

“So imagine if you put IoT sensors so that those trucks can monitor the liquid contents as they are moving from Lagos to Kaduna; if the truck man removes the liquid content, somebody can see it in a monitor and say, I can see the truck going to Kaduna but there is no liquid content in that truck, it means that something is wrong.”

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