One of the biggest challenges presented to the field of oil and gas is the rising pressure to innovate new and effective technology. As with most fields that heavily rely on IT innovation, oil and gas seeks to overcome challenges in its business by adopting digital transformations.
To combat problem areas in budgeting, emergencies, operational risks, and more – the industry of oil and gas must adopt portfolio optimization guidelines, leading tech innovations, and more.
Effective management of company resources allows for identification of potential impacts in new digital strategies. This goes a long way in bolstering the overall data analytics and IT toolkit of the enterprise.
Ultimately, the goal towards digitization depends on the ability to aggregate and analyze data. Shifting away from traditional methods to a more data-driven approach will drive connectivity, workflow, business processes, and asset management. At this point, it isn’t rare for rhetoric between the IT and business ends of the company to be blurred.
When oil prices rise, companies must be prepared to take countermeasures to ensure good cash flow. Changing market conditions accelerates improvement of old and adoption of new technology.
World oil supplies are being increasingly depleted as societies’ consumption of oil intensifies. In fact, oil consumption in 2017 exceeded its supply in every quarter.
To combat this, oil and gas corporations must expand their digital toolkit by enabling disruptive technologies. Business agility is also a good attribute for responding to rapidly changing conditions in the field.
For the oil and gas industry, automation is taking shape in form of robotic process automation, or RPA, remote operations, and extended industrial control. These automation roles and others are enabled by data analytics, cloud computing, edge computing, cybersecurity, digital twin, and other organizational and analytical tools.
Traditional methodologies of remote operation involve equipment surveillance, but this can be outdone by digital adaptations. Monitoring the oil field can result in acceptable data transmission and visualization of assets. Connecting the oil field, with devices and sensors, will allow for more invasive info aggregation, remote controlling, and asset management. Though it isn’t fully realized, autonomous management of oil fields will also result in huge optimization gains.
ML is the main culprit of cost-effective and high performing computational efficiencies that fuels oil and gas solutions. While the propensity for value is high with Machine Learning, very few companies are investing, let alone implementing, ML.
ML can be used to benefit reservoirs and assets by way of petrophysical property modeling, predictive maintenance, well and asset optimization, and other high-value capabilities. Companies looking to adopt ML should have the end goals of automation and AI in mind. From there, a reliable knowledge in AI, ML, NLP and data analytics must be developed and maintained.
Cloud computing enables quality data integration, efficient workflow, and sound decision making. As beneficial as this is, the area of edge computing is continuously expanding in tandem with AI developments.
More on cloud and edge computing can be found on our blog here.
Oil and gas companies’ well sites are strictly tied to laws and regulations. If there is a preferred location that companies are interested in, it may be an issue if the governing system at that location isn’t open to granting leases. Unstable political forces in ideal drilling locations will present high political risks – such factors depend upon careful decision making, relationship consideration, and extensive risk analysis.
With such a high demand for oil and gas, much of accessible well sites have been depleted. This results in companies having to explore unfriendly environments that may either have harsh weather or suboptimal living standards. Companies could risk operational continuity due to harsh geological barriers, but this can be alleviated if companies prepare precautionary strategies and constant preventive care for their assets.
As any oil and gas company knows, projects can rapidly rack up expenses. These expenses depend on many factors, but the trickiest ones are those that are uncertain or unforeseeable. As such, company’s portfolio management must be optimized to account for these costs and concerns – while exploring cost-saving methods that incorporates data analytics and technological innovation.