The 2017 World Economic Forum report stated that USD 1.7 trillion worth of value will be generated via digital transformation from 2016 to 2025 along with a reduction in carbon emissions by 1.2 million tonnes.
The oil and gas industry is no stranger to technology or data mechanisms. With effective data management, companies can utilize the benefits of digital transformation with data as its backbone.
Technological advances have led to a massive daily generation of data in the oil and gas exploration and production industries. The datasets are varied in nature and are produced in large volumes in different operations including upstream and downstream. If processed in an efficient manner, these datasets can boost agility and strategic, data-driven decision-making, resulting in new and advanced operating models.
Utilizing structured data for well-informed insights, precise answers to complexities, and for unraveling new growth opportunities can greatly benefit O&G companies by helping them become data-savvy.
The biggest challenge for this industry is selling its upper management on the long-standing benefits of artificial intelligence (AI) driven data management platforms. This is due to the extensive scale of operations in this industry, which slows down the adoption of new technologies. According to Sammy Haroon, CEO of AlphaX Decision Sciences, there is a a great need for the democratization of data in this sector; open source is the key to successful and speedy AI adoption.
The current economic downturn has led to a dip in demand for oil in many countries and a slowdown of operations. This leaves a lot of room for oil and gas companies to focus their attention on adopting data science technologies and becoming data efficient.
With a tsunami of data available, O&G companies need fully-equipped data management systems to govern equations that lie behind the big data. An enhanced analytical model can help companies analyze bigger, more complex data. Further, it delivers faster and more detailed results, even on a very large scale. With prompt usage of structured data and specific analytical models, O&G companies can benefit supremely by identifying profitable opportunities quickly and avoiding unknown risks. Industry applications include data on new energy sources, analyzing hydrocarbons in the ground, and predicting the lack and failure of refinery sensors. Data analytics can also help companies in responding efficiently to production failures, optimization of parameters of low-rate wells, etc. in an informed and measured manner.
Big data get generated consistently from oil and natural gas and upstream, midstream and, downstream processes. These processes can be analyzed quickly and effectively for curating better insights that could prevent equipment failures and enhance operational efficiency. For instance, through the integration of the Internet of Things (IoT) with offshore equipment, tracking, and monitoring of lifespan, and other elements can be done by employees. Using this knowledge, employees can maintain an offshore platform via predictive maintenance to help in detecting equipment failures before they occur.
M.R. Brulé, Group IBMS, stated in his report that over 50% of petroleum engineers’ and geoscientists’ time is invested in searching for and assembling data. Increasing amounts of data get integrated through upstream technology into databases or other data warehouses. Data management assists with accurate analytics and improved data quality, which is beneficial in terms of speed, reducing the necessary data movement, and promoting better data governance. Upstream decision-makers benefit from faster access to analytical results and more agile and accurate decision-making. Oil and gas companies function in a dynamic and competitive global economy. Many companies struggle to manage data and gather clean insights from it, making data structuring and data management an integral part of effective functioning, time-saving, and improving efficiency.
Analytics software can be used to monitor the drawing of oil from wells and subsea pipelines. It can draw out potential issues before they develop and ensure that all the processes are running smoothly without interruption. Currently, analytics software is being used for boosting efficiency in areas like simulating production assets to reflect potential operating performance, real-time monitoring of well abnormalities for optimizing safety and performance and conducting trials of analytical models in cloud environments through data science sandboxes.
Drones, along with 3D virtual modeling, not only help with saving time and money but also greatly improve safety. Oil and gas companies generate excessive data for huge infrastructure setup, which needs constant assessment, maintenance, and manual inspection. This inspection process can take weeks, or even months, while costing a fortune. A drone can quickly inspect issues and problems, leading to the development of better recovery plans. Data derived from the drones’ footage not only saves time and money but also ensures safety.
The above benefits highlight the fact that it’s important for organizations to have clean, usable data at every step of their operations in order to achieve operational efficiency without compromising on security. Investing in a data management platform like DataBlaze helps you consolidate your data from disparate sources, including IoT devices, to enable you to derive insights without writing a single line of code. It saves you time and money and offers you an unparalleled view of your data. Advanced analytics can become an essential part of your strategy, but what’s most important is that your organization adopts a data-driven approach.