Data Exchange Standards in the Oil & Gas Industry

12 min readJun 11, 2019

Data exchange standards arise as an effective solution against the effects of poor interoperability in Oil & Gas companies.

Authors: Javier J. Ceballo C.[1]. Osmer R. Parabavire M. [2]

[1]. Business Analyst at Karanta Software.

[2]. Business Manager / Chief Data Scientist at Karanta Software.


At present, the Oil & Gas industry it faces new challenges that are reflected in the constant fluctuation of oil prices and in increasingly stringent environmental regulations that must be met. Given this new panorama, companies use the most advanced technology in instrumentation and software for decisions making based on data, in order to optimize operations in the areas of exploration and production of oil and gas (Rockwell Automation, 2015).

In order to achieve this goal, it is essential that all these technologies work together exchanging data. However, it is very common for them not to do so properly because they have different and incompatible data formats (Cotton, Grisson, Spalding and Want, 2012).

Therefore, the existence of a standard format for the efficient exchange of data between software applications acquires, nowadays, a greater relevance, causing some standardization organizations from differents parts of the world to work actively to cover this niche (Petrolink, 2016).

This paper presents the main features of three standards that cover the needs inherent to an effective data exchange in the Oil & Gas industry. These standards are: ISO 15926, OPC UA and PRODML. Likewise, the interoperability in oil companies is described and the advantages associated with the use of these standards in the hydrocarbon sector are made known.

Interoperability in Oil & Gas Industry

In the Oil & Gas industry, interoperability (or data exchange between two or more computer systems, as defined by the IEEE) is often affected by the variety of devices and software tools that coexist in this sector.

According to Hollingsworth and Ormerod (2014), today’s oilfields feature state-of-the-art technology, such as downhole sensors for capturing field-generated data, and software tools to monitor, manage and optimise hydrocarbon production from this data.


The interoperability between these tools must occur without problems in order to ensure the good performance of work-flows. However, when provided by different software companies, as it usually happens, these applications they support their own data formats, as for example, spreadsheets and PDF files (Baaziz and Quonian, 2014).

This hampers efficient automation in the oil sector, because companies have to resort to manual data transfer between software applications destined to production analysis, which is time consuming, costly and prone to human errors (Morrison and Shields, 2013).

It is for this reason that, faced with the repercussions of poor interoperability, data exchange standards arise as an effective solution, as will be seen below.

Data exchange standards

The data exchange standards create opportunities to improve interoperability in companies in the hydrocarbons sector. This is because they allow the data to be added in a common environment that facilitates its transfer between different software tools (Hollingsworth and Ormerod, 2014).

Many organizations around the world make efforts to standardize the exchange of data in areas as diverse as construction, building automation and the Oil & Gas industry.

In the latter area, specifically in the sector of exploration and production of hydrocarbons (E & P), there is a set of “detailed and complex” standards aimed at improving interoperability (Brulé, 2010).

For purposes of this work, three of these standards will be described below, which were selected in agreement on the literature review, namely: ISO 15926, OPC UA and PRODML. Principally, the scope and the practical uses of each of these specifications will be presented.


ISO 15926 is an international standard for the representation and exchange of data concerning the life cycle of industrial plants, which includes the engineering, construction and maintenance phases. This standard not only covers oil and gas production, but also other process industries associated with the refining of hydrocarbons; generation of electric power; and manufacture of chemical and pharmaceutical products (ISO, nd).


The standard ISO 15926 was initiated in 1997 by POSC Caesar(PCA), an organization that promotes the development of standards for data exchange and is member of ISO (International Organization for Standardization). Since that year, PCA chairs the ISO TC184/SC4 group, responsible for the maintenance and improvement of the standard (POSC Caesar, nd).

ISO 15926 defines a format to represent data on the current status of process plants taking into account the following aspects (ISO, sf):

  • Physical objects that exist in a process plant;
  • identifications, properties and classifications of physical objects;
  • how physical objects are assembled and connected.

Likewise, the data model of ISO 15926 allows to represent the changes that occur in the process plants, after carrying out maintenance and redesign tasks.

ISO 15926, also known as “Integration of life-cycle data of process plants, including oil and gas production facilities”, currently consists of 7 parts that have been published separately. According to POSC Caesar, these parts are:

Part 1- Overview and Principles Fundamental (published in 2004). It describe the purpose of the standard.

Part 2- Data Model (published in 2003). It offers a conceptual data model for the representation of information about the objects of a plant. This model is designed to be used together with the reference data of parts 3 and 4.

Part 3- Reference Data for Geometry and Topology (published in 2009). It includes a dictionary to represent curves and surfaces to be used with computer-aided design (CAD).

Part 4- Initial Reference Data (published in 2007 / updated in 2010). It contains a dictionary of the data that are used in the different industries covered by the standard.

Part 5- Procedures for Registration and Maintenance of Reference Data (discontinued).

Part 6- Scope and Representation of Additional Reference Data. It describes a methodology to validate new reference data.

Part 7- Implementation Methods for the Integration of Distributed Systems: Templates Methodology.

One of the applications of ISO 15926 in the Oil & Gas industry, is the Integrated Operations (OI) program of the Norwegian Petroleum Industry Association (OLF), where the data model is used ISO 15926 for the exchange of data between oil rigs and onshore facilities (POSC Caesar, nd).


OPC UA (OPen Connectivity Unified Architecture) is a standard developed by OPC Foundation and published for the first time in 2008. This specification defines an information model and communication model client-server that allows various devices and computer systems can exchange data in a standard way (OPC Foundation, 2017).

In the communication model of OPC UA several devices can assume the role of client or server, so that the exchange of data is achieved by sending request and response messages between these parties. OPC UA specifies the services of the object models that a server can make available to a client in its address space or AddressSpace (OPC Foundation, 2017).

Source: OPC Foundation

A Server’s AddressSpace is “a collection of information” that it makes visible to Clients (OPC Foundation, 2017). The data objects that make up AddressSpace can be exposed using different formats, such as: binary structures or XML or JSON documents. These objects can be defined using the information models of standards organizations, suppliers or end users (OPC Foundation, 2017).

OPC UA was created in order to improve the first specifications of the organization that supports it, which are known as OPC Classic. These specifications also allow the exchange of data between software components, but based on Microsoft Windows COM/DCOM technology and offering separate information spaces to access process data, alarms and historical data (OPC Foundation, 2017).

Unlike OPC Classic, OPC UA is not based on the COM / DCOM model but works based on a service-oriented architecture (SOA), which helps it to be implemented in any hardware and software platform. In addition, OPC UA defines an integrated information space that allows to represent process, alarm and historical data in a single component (OPC Foundation, 2017).

The standard OPC UA consists of 14 specifications that define it in broad terms and that are constantly reviewed and improved by the working groups that collaborate with the OPC Foundation. These specifications are (OPC Foundation, 2017):

Part 1 — Overview & Concepts. Presents the concepts and a general scope of OPC UA.

Part 2- Safety Model. It describes the model for secure interactions between OPC UA applications.

Part 3- Address Space Model. It describes the contents and structure of the address space of the server.

Part 4- Services. Specifies the services provided by the servers.

Part 5- Information Model. It specifies the types and their relationships defined by the servers.

Part 6- Service Mappings. It specifies the assignments to transport protocols and data encodings supported by OPC UA.

Part 7- Profiles. It specifies the profiles or characteristics that OPC UA applications must meet in certification processes.

Part 8– Data Access. It specifies the use of OPC UA for access to current data.

Part 9- Alarms & Conditions. It specifies the use of OPC UA to access alarms and conditions.

Part 10- Programs. It specifies the OPC UA support to access the programs.

Part 11– Historical Access. It specifies the use of OPC UA for access to historical data and events.

Part 12- Discovery. It describes how discovery servers work and how clients and servers should operate with them in different scenarios.

Part 13- Aggregates. It specifies how to compute and return aggregates at least, maximum, average, etc. These can be used in both current and historical data.

Part 14- PubSub. It specifies what concerns OPC UA’s PubSub communication model.


Many standardization organizations use OPC UA services as a transport mechanism for their information models, which gives them the advantage of being used in different areas. In regards to the Oil & Gas industry, OPC UA is used currently as a “standard protocol” to transmit quality data and safely between Master Control Systems (MCS) and Distributed Control Systems (DCS) in offshore oil and gas production (OPC Foundation, 2019).


PRODML is a standard that allows the “reliable and automated exchange of data between software packages” that are used in activities related to the management of hydrocarbon production (Energistics, 2016).

The first version of PRODML was developed in 2005 by Energistics (organization that creates data exchange standards), in collaboration with oil companies and companies that provide services in oil fields, such as: BP, Chevron, Exxon Movil, Hallibourton, Schlumberger, among others (Veyber, Kudinov and Markov, 2012). This standard is in a process of constant improvement, so its current version is PRODML v2.0, published in December 2016 (Energistics, 2016).


In order to achieve an efficient data exchange, PRODML allows, in the first instance, to create models of the business objects of any oil and gas production company, using a hierarchical structure made up of three elements: the unit, the network and the model (Veyber, Kudinov and Markov, 2016).

In this sense, the unit represents those components of the object to be modeled that capture or provide information (such as a separator, a pump or a valve). The network, on the other hand, is a set of interconnected units, while the model, representative of the business object, comes to be made up of one or more networks (Veyber, Kudinov and Markov, 2016). All the above elements are described in the XML language (Energistics, 2016).

Importantly, the scope of PRODML covers only the oil and gas production activities that take place from the wellhead to the custody transfer point. These activities include the following (Energistics, 2016):

  • Optimization and monitoring of wells and production assets.
  • Transfer of production reports in standard format, for regulators, partners, and between the departments of the same company.
  • The use of time series for the analysis and modeling of automated data.

Currently, many oil and gas companies around the world actively use the standard PRODML. For example, Saudi Aramco requires all its production providers to use PRODML to achieve more efficient data exchange. Likewise, the Norwegian state company Equinor (formerly Statoil) uses this standard for the transmission of production data to regulators in the Nordic country (Digital Energy Journal, 2017).

PRODML has also been used since its creation by some companies in the realization of pilot projects focused on data analytics. Such is the case of Piooner Natural Resource that worked in the analysis and visualization of hydrocarbon production data using the analytical tool Spotfire, entering the data on this platform in a standard format, instead of using dissimilar formats (Digital Energy Journal, 2017 ).

Energistics offers extensive documentation that promises to help developers and other users in the design, development and testing of software applications based on PRODML. This documentation includes the following (Energistics, 2016):

Business Overview of PRODML. It offers an overview of PRODML from a business point of view, briefly describing its scope, benefits and typical uses.

Technical Overview of PRODML (User Guide). It describes the structure of PRODML and how it should be used.

PRODML Object Usage Guides. It shows how to use each of the PRODML data objects.

PRODML Programmers Guide. It gives a vision to the programmers on how to use the PRODML service specifications.

Data Specifications. It specifies the data covered by PRODML in a schematic way.

Service Specifications. It specifies the web service contracts that are part of PRODML.

Glossary. It defines the terms used in the PRODML documentation.

In addition to the above documents, Energistics makes a software development kit (SDK) available to developers on its website to facilitate the implementation of PRODML and its other known data exchange standards. as WITSML and RESQML (Energistics, 2016).

Key benefits of standardization


The adoption of data exchange standards in the business upstream of the Oil & Gas industry allows companies to reduce costs and increase the efficiency of their operations (Petrolink, 2016). This is achieved in the following way:

  • By reducing delays in work-flows. The use of a standard format allows to automate the exchange of data between software applications, thereby decreasing the delays in carrying out analyzes that would help optimize the drilling and production processes (Morrison and Shields, 2013).
  • By improving the quality of the data. Errors that can occur with manual data management are eliminated with the use of standards for the exchange of information (Morrison and Shields, 2013).
  • By reducing technological dependence. Companies can opt for software packages that are less expensive and that adapt to their real needs, since their data will be transmitted in a standard format and not in a specific format of a provider (Digital Energy Journal, 2017).
  • With the prevention of unwanted events. This prevention starts from the use of standardized historical data and statistical models to anticipate problems that could hinder drilling activities (Petrolink, 2016).


Data exchange standards help hydrocarbon companies automate their work-flows, resulting in lower costs and more efficient processes.

On the other hand, it is necessary to know the scope of the different data exchange standards in order to select the most appropriate for a specific application, since they are usually intended to cover certain domains of the oil industry.

For example, PRODML covers what is related to the optimization of hydrocarbon production, while ISO 15926 focuses on the processes of engineering, construction and operation of oil production facilities. OPC UA, on the other hand, contains a very general data model that allows it to adapt to several areas.


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