The Executive Operations Director at Seplat Petroleum Development Company Plc, Mr. Effiong Okon, has said the right adoption of contemporary technologies like Artificial Intelligence (AI), big data and mobile technology will not only drive planning and forecast in the Nigerian oil industry, but will help in addressing like risks associated with the business.
The Seplat EOD said this at the 43rd Society of Petroleum Engineers (SPE) Nigeria Annual International Conference and Exhibition held in Lagos recently, with the theme: Artificial Intelligence, Big Data and Mobile Technology: Changing the Future of the Energy Industry.
While delivering a presentation titled, Transforming Big Data and Technology to Business Value: Challenges and Strategic Options during a panel session, Okon said leveraging Cloud computing and big data, for instance, 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, according to him, 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), the Seplat Executive noted..
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 will further help in improving subsurface mapping and new well delivery performance through micro-seismic 3D imaging.
Narrating the Seplat technology story, Okon said the company had continued to make conscious efforts to drive operations using contemporary technologies, with the right investments. According to him, Seplat’s investments in technologies are driven by measurable and justifiable value accruable to the company.
He added: “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
In the area of refining, the Seplat EOD noted that operators could 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.
“Blockchain revolution is starting here and now. There is huge potential to reduce risk of fraud, error and invalid transactions in energy trading and enable interoperability. To revolutionise joint ventures (JVs), risk management, contracting and regulatory compliance. This is critical to unlocking the efficiency potential of distributed energy generation.”
According to Okon, technology will be a facilitator in the transformation of oil and gas companies, and this demands that companies make confident, data driven decisions using relevant, accurate and trusted information platforms.