Digital Transformation to Hike Oil and Gas Production
Inefficient Use of Data in Oil and Gas
E&P data acquired over decades on various media technologies is commonly stored in warehouses and cannot be accessed on today’s platforms, and that means missed opportunities. Geophysical companies are sitting on a wealth of information, and how they use subsurface data can make the difference between having to tolerate production plateaus instead of using new technology to wrest fresh income-generating insights from historical data.
Yesterday’s thinking about the value of E&P data is why, according to Teradata, upstream companies can lose as much as $8 bn per year in non-productive work as their geoscientists, petroleum engineers and data managers spend up to 70% of their time poring over mountains of well data (cores, logs, scans, samples) and seismic data (2D and 3D time and depth sections in digital and hardcopy). To make matters more complicated, the subsurface data is contained in myriad current and legacy software applications, databases, data recording sensors, paper and tape records. Storing, managing and organising massive volumes of hard-copy proprietary records and media archives, and then trying to locate and access the specific data needed for analysis, interpretation and processing, is a cumbersome, challenging and inefficient process.
It is so inefficient that a McKinsey Report (CNBC 20154; 2015) says the oil and gas industry currently generates value from only one percent of all the data it creates.
Getting Value from all Geological and Geophysical Data
MIT’s Sloan School and Deloitte rank the digital transformation maturity of the oil and gas industry among the lowest, at 4.68 on a scale of 1 to 10. Before pinpointing the exact reasons for low maturity in digital transformation, consider the challenges confronting today’s geoscientists, petroleum engineers and data managers:
- How to quickly find, access and make sense of all the proprietary subsurface data and metadata held within their company’s information stores and department silos?
- How to consolidate, manage and access all that information in order to then analyse and aggregate it into meaningful decisions?
- How to extract actionable knowledge about, and mine fresh insights into, potential subsurface hazards and opportunities, given all the current and legacy records that exist?
These challenges are the reality for many companies who need to focus on how digital transformation of E&P data can optimise operations and create new value from old seismic data.
Enter the power of data digitisation, data migration and digital transformation for E&P data. Simply by conducting daily operations, operators have amassed and stored a virtual goldmine of subsurface data – several petabytes by Deloitte’s estimation – of bankable geophysical information. When oil and gas companies digitise and transform these priceless libraries of paper records, recordings, 2D and 3D and other analogue information into secure cloud-based digital data records, decades of valuable E&P information become easily accessible to geoscientists and data managers to use whenever and wherever they need it. It is stored securely and privately in the cloud, where it is safe, protected and accessible.
With powerful data analytics, the secure treasure trove of digitised geoscience data can be instantly read, indexed, interpreted, manipulated, verified and accessed with smart-tool technologies that incorporate artificial intelligence (AI) and machine-learning. Companies can mine historical, current and future data to find new patterns contained within that accumulated wisdom to ask better questions and make faster and better decisions.
Using Big Data to Solve New Problems: Big Rewards
Many people think the term Big Data simply means having to deal with vast amounts of data. That is true, but it also means focusing on how to grow the business by effectively integrating all aspects of the data that have been accumulated over the decades to solve new problems and challenges. Big Data means breaking the barriers between departmental data silos, and increasing visibility throughout operations. It means creating the company’s own E&P Internet of Things (IoT) for geoscientists and data managers to harvest at will, making new discoveries with old data, reducing the costs of new discoveries, improving well success rate and increasing profitability.
In a recent GE/Accenture report, surveys show that 81% of senior executives believe that Big Data analytics is one of the top three corporate priorities for the oil and gas industry.
In E&P operations, Big Data can be used to uncover non-productive time and activities, highlighting not-so-obvious operational losses and oppressive sunk costs. It can identify opportunities to boost production from existing assets and extract financial value from all available operations, no matter where the subsurface data originated or where it currently resides.
Digital transformation of E&P data creates an open data culture with full governance and good analytical accessibility within a protected environment. Instead of just connecting the dots, Big Data connects the datasets by mining libraries of digitised seismic data to quickly access information and extract additional intelligence, pinpoint the most valuable assets, derive new patterns of strategic planning, and create new avenues of thinking about how to increase efficiency and escalate profits. Because of the vigorous process involved in digital transformation, digital assets have become more secure and of higher quality, which promotes greater confidence in decision-making.
But where does the vital E&P IoT data reside in the cloud? Where should it reside?
Clouds, Hybrid Clouds and Multi-Clouds
Cloud computing brings the benefits of digital transformation and data analytics to the local network – as well as a network of remote internet-hosted servers – to store, manage, process and manipulate through an online interface. Cloud computing allows companies to analyse a wealth of data quickly at a reduced cost, and provides an on-demand off-premise environment for disaster recovery solutions.
Beyond the cloud, oil and gas companies have expanded choices for visualising and mining seismic data, depending on dataset sizes, needs and budget. For example, a hybrid-cloud computing environment uses a mix of on-premises, private cloud and thirdparty services, with orchestration between. By allowing workloads to move between them as computing needs and costs change, hybrid cloud gives greater flexibility and more subsurface data deployment options. By comparison, a multi-cloud environment refers to the ability to leverage two or more cloud computing platforms but not necessarily requiring connectivity or orchestration between them.
E&P companies should choose the digitised-data storage method that fits their needs now, but keep an eye on the future. After all, the industry is growing.
Reasons for the Digital Transformation of E&P Data
Upstream companies can benefit from digital transformation of E&P data by:
- Generating value from the 9% of subsurface data estimated to be unutilised in paper records, recordings and other legacy media;
- Increasing annual production from existing assets by as much as 8%;
- Saving up to $1 bn per year by reducing non-productive activity by geoscientists, petroleum engineers, and data managers;
- Creating a cloud-based E&P IoT – an open data culture in a protected environment with full governance and analytical accessibility.
To get started, oil and gas companies should consider partnering with a subsurface data management service provider that has plenty of experience handling geoscience data and the media on which it has been recorded over the years. With over 40 years in the industry and 40 petabytes of data managed, Katalyst Data Management provides integrated, end-to-end data management and consulting services designed to help companies implement digital transformation of E&P data from every major basin worldwide.