Harnessing Energy Data for Sustainability and Profit

The current economic and geopolitical climate is compelling Energy industry leaders to rethink the business processes that support their exploration of hydrocarbons, which are the main component of petroleum and natural gas. There are multiple factors at play, and they’re all linked by an organisation’s ability to manage, integrate, and find the data needed — on demand.

Energy companies face a number of pressing business challenges that more effective data management and workflow automation can help them meet:

• Pressure from investors and regulatory bodies to lower their carbon footprints and improve overall environmental, sustainability, and governance (ESG) levels. It’s estimated that the Energy industry directly or indirectly accounts for about 42% of today’s global greenhouse gas emissions.
• The need to minimise financial risk, in part through the use of highly accurate, data-driven decisions about which potential hydrocarbon sources to explore.
• Finding ways to increase profitability, such as using predictive maintenance to minimise downtime in oil rigs, pipelines, and other expensive equipment and facilities.
• Overall cost control, which depends in part on access to critical documents that support business processes, collaboration, safety operations, and regulatory compliance.

Data is the common variable at the core of all these issues. But data is proliferating exponentially, and as it grows, it can easily become siloed, lost, or otherwise difficult to find and access. Manual or outdated data management practices can hamper Energy companies’ ability to meet their sustainability goals, automate their workflows for greater ROI, and control escalating operations costs.

Keeping Pace with Data

In addition to multiplying at an estimated 23% annual growth rate, data is taking on a wide variety of formats, making it far more complex to manage and act upon. Traditional approaches to sorting, classifying, and analyzing the massive volumes of documentation that accumulate in Energy companies are often manual and time-consuming, making them impractical for the modern competitive landscape.

Most Energy companies have created and stored subsurface information over many years or decades of exploration. It's estimated that these organisations have more than 25 years of data still in use today and that as much as 80% of that information consists of unstructured data that isn’t inherently searchable.

It’s not uncommon, for example, for companies to still store some wellhead, production, and financial data in physical file folders, while other information has been captured in electronic—yet difficult to find—spreadsheets, PDFs, and media files such as video, audio, and images. While some companies have deployed database software, many haven’t centralised the data in them, so locating it on demand remains challenging or even impossible, at least for a subset of their users.

Once thought to have little value, older Oil & Gas information was often stored away without meaningful indexing that would help personnel find, retrieve, and use it down the road. With newer, unconventional drilling approaches emerging, though, Energy companies can breathe new life into their hidden data—provided they can make it readily available to the geologists, geophysicists, scientists, engineers, and others who need it. Doing so requires finding the data and putting it into a format that’s searchable and accessible. From there, it must be continually monitored for security and compliance.

Top Priorities: Quick and Easy Access to Data

Providing authorised personnel with quick and easy access to the data they need requires company-wide data to be digitized. digitisation can be accomplished using document imaging/scanning services for paper files and migration services that convert data from older media such as tape drives to modern digital formats. Once energy companies put their seismic data, wellhead measurements, engineering diagrams, and other information into digitized formats, they can store it in a central, often cloud-based, repository that allows broad access to it, and has the scalability and compute power to run big data analytics on it. The data can then be used to inform and automate both back-end and upstream workflows and decisions.

Technology advances that combine image recognition with artificial intelligence/machine learning (AI/ML) are knocking down the barriers to the digitisation process. These services are components of the latest intelligent document processing (IDP) software, which captures data, organises it, and enables it to be shared and used to power workflow automation. These systems use AI/ML to identify scanned document types, load them into databases and applications, and tag them with metadata, a basic description of the data that makes it easy to find and use. This is much quicker and more thorough than companies having to manually find, classify, and index all their documents.

Once digitized, centralised, and tagged, data can be managed, secured, and accessed by authorised users for decision-making, collaboration and workflow automation. Project teams, for example, constantly need to consult procedures, policy documents, and other compliance reports as they carry out their jobs. Storing documents like contact and proposal files in the repository makes them readily available for consultation and modification by team members as they make decisions and create action plans.

Modern Intelligent Document Processing

Modern IDP platforms are built on cloud-native principles, which means they scale almost infinitely and can integrate with internal and customer-facing applications. For example, the system allows data to be integrated with foundational business applications such as enterprise resources planning (ERP) and human resources information systems (HRIS) as well as Energy-industry-specific software for simulation and modelling, engineering, production, asset management, and equipment maintenance. When aggregated and analyzed, the data can serve as a trusted source, with access to and integration with core geological data and images, safety regulations and best practices, and equipment maintenance schedules, as a few examples. The system can quickly generate important insights for key decisions—such as identifying top geographical location candidates for drilling—and enables the automation of operations, workflows, and business processes.

These are among the ways that content management and intelligent document processing systems unlock the potential of field and office data in Energy companies. They provide continuity across project and operational phases as the company stores, organises, manages, circulates, edits, and tracks its files and documents. Project managers, subcontractors, and engineering teams in different locations can collaborate, sharing plans, documents, and drawings throughout their life cycles, from concept and creation to disposal. Intelligent document processing systems support data governance with business rules for managing both structured and unstructured data, including where to store data, how to archive it, and when to destroy it. At the same time, the systems slash the administrative burden associated with managing records retention schedules and meeting industry compliance requirements.

A Wealth of Outcomes

Process automation and data integration allow Energy companies to meet their pressing goals by managing, aggregating, and analyzing data in ways that:

• Drive data-based decisions that minimise risk and enable accurate production forecasts,
• Automate and simplify back-end operations,
• Reduce the administrative burdens of regulatory compliance,
• Enable real-time operations adjustments,
• Foster interdepartmental collaboration,
• Improve worker safety,
• Minimise unplanned equipment downtime,
• Automatically monitor pricing fluctuations, and
• Enable standardised field operations.

It's important to protect, govern, and maximise the value of physical and digital assets company-wide. A well-defined document management and workflow automation strategy that starts with digitising, centralising, and indexing documents sets Energy organisations up to achieve their sustainability, revenue, and productivity goals while managing financial risk in an uncertain economy.

Iron Mountain helps you bridge the gap between physical and digital information with automated document management processes that put your data to work so you can make informed business decisions. Learn more at ironmountain.com/energy.