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  • Diego Gobernancia Jesus

A Beginners Guide To Data Management in the Oil and Gas Industry

Operators in the Oil and Gas Industry produce regularly produce huge swathes of data when they acquire new Seismic, Drill a well, or buy legacy assets. These Data Mountains come in various forms of Digital and Physical format.


This data provides the backbone for business leveraged decisions, and provides insight into the exploration, development and day to day operations which can help increase efficiency and profitability – but only if it is well-managed.


For a company that turns on insight and knowledge gained from Data, good Management practices are foundational to its success.





Data Management: The Basics

Data Management, at its core, is a consistent tracking of data throughout its lifecycle, ensuring it meets all internal and external compliance requirements. It is understanding the history of the data, from the point of its creation, through to the moment of disposition and ingestion – and whatever variations may come from processing, interpretation and use throughout that lifecycle.


Data Management is all about making informed decisions for business processes and efficiencies, so having a methodology and set of processes for managing large volumes of data is essential for companies to make informed decisions. It also provides a framework for assurance – understanding the history of the data also gives confidence in it – which adds more value to the decisions that spur from its use.


At GDDM, we have extensive experience working for, and in, Oil and Gas Companies to develop solutions to streamline workflows, maintain compliance, improve operational efficiency and increase profitability by ensuring there is an end to end understanding of the data, its uses and its requirements.


Core Components of a Data Management Strategy

Data management is a notoriously complex endeavor in the oil and gas industry, with many departments, different types of data, and different regulatory and internal compliance requirements. That said, the work we do at GDDM can generally be broken down into four main components:


  1. Data Collection: Extracting and storing data from the relevant sources (more on those later)

  2. Data Integration: Bringing together data from multiple sources, formats, and systems (e.g., sensors, reports, spreadsheets) into a single unified system

  3. Data Analysis: Using data to identify and evaluate trends, correlations, outliers, etc., with the aim of improving operational performance

  4. Data Visualization: Presenting data in a way that is easy to understand and interpret (e.g., graphs, charts, etc.)


These four components are the foundation of an effective data management strategy in the oil and gas industry. But depending on the specific needs of your business, these components may need to be tailored and adjusted.


An Introduction To Oil and Gas Data Management


Data Sources

To understand data management in the oil and gas industry, it’s important to first consider the sources of data. For Oil and Gas, these are typically in the form of either Geotechnical Data, or Corporate Data.


Let's briefly take a look at each of these data sources.




Geotechnical Data

Geotechnical Data is an data generated or collated directly from the source, or processed after acquisition. It typically covers areas like Seismic Acquisition, Site Surveys, Well Specific Data related to Drilling activities, Interpretation of the acquired data either through studies or projects, and the Infrastructure associated with the supply and demand of the Oil Products.


This includes things like:


Seismic Field Data (e.g., Seismic traces acquired over an area of interest)

Site Survey Data (e.g., Assessing an area to understand its structure and viability for drilling/platforms)

Drilling and Completion Data (e.g., drilling depth, formation characteristics)

Infrastructure Data (e.g., Pipeline routes, tie-backs, etc)

Interpretation Data (e.g., Data which relates to the understanding, manipulation and review of all of the above)


This data is crucial to Oil and Gas companies as it is the foundation upon which all decisions are made. More commonly this data is referred to as Structured Data, as it I has a consistent structure throughout and is often viewed with specialist tools.


Corporate Data

Corporate Data is generated from the business activities that spur from the above, such as Supply Chain Documentation, Logistics, Legal information relating to Licenses, Regulatory Compliance and communications, etc.


This includes things like:


Legal Data

Logistics Data

Cost and Financial Data

Inventory and Supply Chain Data

Safety and Compliance Data


Corporate data helps businesses in the oil and gas industry gain a better understanding of their operations and make smarter, more informed decisions. This data is commonly referred to as Unstructured Data as the contents within two similar files are disparate in their structure, but can be viewed with a generic or common tool, like Word.




Systems and Tools

Systems and tools augment the basic principles of Data Management, providing a secure and reliable way to store, manage, and analyze digital data that goes far beyond the capabilities of legacy methodology (i.e., spreadsheets and filing cabinets), while leveraging their basic principles.


There are many systems and tools already available for data management in the oil and gas industry, but some of the most popular include:


Data Lakes and Warehouses: Data lakes and warehouses can be used to store large volumes of structured or unstructured data for easy retrieval, analysis, and reporting.

Data Visualization Tools: Data visualization tools can be used to quickly analyze and present data in an easy-to-understand format.


These systems and tools can provide the vital infrastructure needed to manage oil and gas data effectively, but they are only part of the picture. To maximize efficiency and get the most out of their data, the industry must also consider how they organize and store it.


Storage and Organization

Data can be stored in a variety of ways, but the most important factor to consider is organization. It’s essential that data is properly categorized, resides within appropriate repositories and has accurate and usable meta-data, so it can be easily accessed and used by different stakeholders within an organization.


Common methods for oil and gas data storage include:


Relational Database Management System (RDBMS): An RDBMS stores data in tables that are related to one another via key-value pairs. This type of system is ideal for structured data with well-defined relationships between elements.

NoSQL Database Systems/Electronic Document Management Systems (EDMS): NoSQL databases store large volumes of unstructured or semi-structured data such as documents, images, video files, and audio files.

Data Lakes: Data lakes are used to store large volumes of structured, semi-structured, and unstructured data in a single repository. They can be used to store both raw and processed data for easy access and analysis.


By organizing data properly, businesses can ensure that their data is secure, readily accessible, and well-stored for future use. This will not only improve operational efficiency, but also help them make more informed decisions based on reliable insights derived from their data.


Visualization and Interpretation


Data visualization and interpretation are essential for oil and gas data management. Using the right tools and techniques, businesses in the industry can gain valuable insights from their data that can help them make better decisions.




Common data visualization and interpretation techniques include:


Graphs and Charts: Graphs and charts can be used to quickly visualize large datasets in an easy-to-understand format.

Heat Maps: Heat maps are a great way to see patterns or correlations between different variables in a dataset.

Statistical Analysis & Modelling: Statistical analysis and modelling can be used to explore complex relationships between different variables, identify key drivers of performance, or predict future outcomes.

ML and AI Solutions: Machine learning and AI solutions can be used to uncover hidden patterns and insights from large datasets that may otherwise go unnoticed.


By leveraging the power of data visualization and interpretation, businesses in the oil and gas industry can gain valuable insights into their operations, enabling them to optimize processes, drive efficiency gains, and make more informed decisions.


As with everything, these tools require clean, accurate and digitized data – It doesn’t take into account any data which needs to be transformed, or digitized directly, such as scanning physical items.


Security and Data Governance

The security and data governance of data are essential for ensuring its accuracy, integrity, and reliability. Without proper security measures in place, businesses risk exposing confidential information or putting sensitive data at risk of unauthorized access or manipulation.


Common security measures for oil and gas data include:


Data Encryption: Data encryption is an effective way to protect data from unauthorized access and manipulation.

Access Control: Access control measures such as password protection and two-factor authentication can help ensure that only authorized users have access to sensitive data.

Data Governance Policies: Data governance policies should be established to define who has access to what types of data, as well as how it should be used and shared.

Auditing and Monitoring: Auditing and monitoring tools can help businesses identify security breaches or suspicious activity in their systems.


By taking the necessary steps to secure and govern their oil and gas data, businesses will ensure that the information they use is reliable, accurate, and up-to-date. This will enable them to make informed decisions based on trustworthy insights derived from their data.


Should You Outsource Oil and Gas Data Management?


Data management can be a complex and time-consuming process. To ensure accuracy, reliability, and security of data, businesses in the industry should consider outsourcing their data management needs to experienced professionals – whom are also a dwindling resource, with many experienced and knowledgeable Data Managers retiring from the Industry with no-one to replace them.


Outsourcing data management can provide numerous benefits, including:


Cost Savings: Outsourcing will reduce upfront costs associated with setting up and maintaining in-house data management systems.

Expertise: Experienced professionals will be able to provide the necessary expertise and knowledge to manage data effectively.

Flexibility: Outsourcing provides greater flexibility, allowing businesses to scale up or down depending on their needs.

Security and Governance: Professionals can ensure that data is secure and properly governed.


At GDDM, we offer a range of data management services, tailored to the specific needs of our clients. Our experienced team of professionals can help you manage and analyze your data, enabling you to make more informed decisions and gain valuable insights into your business operations.


Contact us today to learn more!


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