While Oil & Gas has been used by mankind in various forms since centuries, the modern petroleum industry’s beginnings can be traced way back to 1959 when Edwin Drake first struck oil in Titusville, Pennsylvania marked by systematic extraction and large-scale drilling.
Since then Exploration, Extraction, Refining and Distribution of Oil and natural gas has been growing in scale, has become far more asset-intensive and novel technologies and methods are continously being deployed to improve output and efficiency in these activities.
The growing complexity has paved the way to the deployment of several modern pieces of equipment, machinery and tooling, each requiring their own maintenance schedules, monitoring and operational management.
Given the large capex requirements in Oil & Gas industries and consolidation of most O&G operations among a few hundred companies globally, any given company makes large and continous deployments of operational assets to ensure best possible operational efficiency and processes are ensured to maximize outcomes and reduce costs.
These operations are generally sequential, meaning one production process is dependent on the successful execution of the preceding steps.
This means that any downtime, delay or mismanagement linked to production activities can have a crippling effect on the entire value chain and fixed assets, equipment and large scale machinery are at the very center of these activities.
Fast forward to the last couple of decades and enterprises are going through a wave of digitization to improve operational efficiency, to generate a digital footprint to track and trace operational tasks and improve their efficiency.
Almost all enterprises with any reasonable sized production and manufacturing operations employ an enterprise asset management (EAM) software with the goal to ensure seamless operations across manufacturing and maintenance operations.
Unfortunately, given the varied requirements and diverse operations in manufacturing and production operations, a one-size fits all approach simply doesn’t work and even large, incumbent Oil & Gas giants struggle with this adoption.
Enterprise Asset Management (EAM) systems are the digital backbone of operational reliability in the Oil & Gas industry.
Whether in upstream exploration and production or downstream refining and distribution, these systems provide a centralized platform to manage the complete lifecycle of critical physical assets – rigs, pipelines, refineries, compressors, and more – ensuring they remain available, safe, compliant, and cost-effective.
A breakdown of some of these activities they perform are detailed below;
At their core, EAM systems manage assets from acquisition through decommissioning. In upstream operations, this could mean tracking offshore platform components or wellheads, while downstream, it includes managing assets like distillation columns, heat exchangers, or storage tanks.
EAM solutions track design specs, commissioning data, modifications, and performance history, ensuring all decisions are based on real-time, asset-specific intelligence.
In upstream environments, maintenance crews are often remote. EAM systems offer mobile access, digitized work orders, and GIS integration to streamline field execution.
Technicians can receive task lists, safety protocols, and part availability info – even in rugged terrains. Similarly, downstream operations benefit from optimized turnarounds and shutdown planning using these tools.
Oil & Gas operations depend on the availability of MRO (Maintenance, Repair, and Operations) inventory.
EAM systems maintain a real-time view of critical spare parts, enabling just-in-time replenishment and avoiding costly stock-outs. In integrated supply chains, EAM also supports vendor-managed inventory and multi-site synchronization.
Unplanned downtime in oilfields or refineries can translate into millions in lost revenue.
EAM systems enable condition-based and predictive maintenance, using IoT sensor data, historical failure patterns, and machine learning to schedule interventions before failures occur.
For example, a compressor station’s vibration data can trigger a work order automatically if thresholds are breached.
Whether it’s OSHA, EPA, or API standards, compliance is non-negotiable. EAM systems automate audit trails, inspection workflows, calibration records, and ensure all maintenance is performed to spec.
They also help enforce Permit-to-Work (PTW) systems, Lockout-Tagout (LOTO) procedures, and safety interlocks – critical in high-risk upstream blowout preventer (BOP) systems or downstream high-pressure pipelines.
Modern EAM systems are no longer standalone—they integrate with APM platforms, ERP systems (like SAP or Oracle), and control systems (like SCADA).
This unification helps operators correlate performance metrics with maintenance data, financials, and production KPIs, driving better investment and replacement decisions.
Despite these modern platforms and some of the best brains building software, several managerial gaps exist, either due to poor adoption or discipline in adopting the technology or a total disconnect between business requirements and technology stacks.
Here are some of these challenges that we know of;
Oil & Gas assets are among the most complex and geographically dispersed in any industry—think subsea infrastructure, desert pipelines, offshore rigs, and refineries.
Managing these assets via an EAM system requires robust connectivity, real-time data acquisition, and remote work capabilities. In many cases, network availability and harsh environments limit the use of mobile-enabled or IoT-based EAM features.
Oil & Gas assets are among the most complex and geographically dispersed in any industry—think subsea infrastructure, desert pipelines, offshore rigs, and refineries.
Managing these assets via an EAM system requires robust connectivity, real-time data acquisition, and remote work capabilities. In many cases, network availability and harsh environments limit the use of mobile-enabled or IoT-based EAM features.
Example: The same pump might be recorded as “Centrifugal Pump,” “Centrif. PMP,” or “CP-1000” in different locations, causing confusion in preventive schedules and spare part planning.
EAM systems don’t work in isolation—they must integrate with ERP systems, SCADA, PLCs, CMMS, and APM tools. This is a significant challenge in Oil & Gas, where legacy platforms, custom-built applications, and siloed operations are the norm. Lack of seamless integration leads to delays in work order execution, visibility gaps, and duplicated effort.
Example: Particularly downstream refineries often face issues integrating real-time control data from DCS (Distributed Control Systems) into the EAM for predictive maintenance triggers.
EAM systems are only as good as the people using them. In Oil & Gas, the field workforce often consists of veteran technicians, contractors, and unionized staff who may resist adopting new digital tools.
Without proper training and change management, paper-based or spreadsheet workflows persist alongside digital systems, defeating the purpose of the EAM implementation.
A common pitfall: Technicians complete tasks but fail to close work orders digitally, leading to discrepancies in asset health records and backlog accumulation.
Like we mentioned earlier, even a short downtime due to mismanaged equipment and assets is a recipe for millions of dollars in losses so manufacturing, digital transformation, operational excellence and data management teams scramble to address some of these challenges mentioned above.
Ironically, while legacy systems do help streamline, analyze, manage and track asset performance and status, it’s success lies in the correct adoption and management by field and managerial teams.
The idea of a Digital Twin in oil & gas production has grown in popularity in recent times precisely so that production workflows and operations can be tracked digitally and monitored for performance to ensure that planning, procurement and maintenance workflows are tackled in a preventive capacity.
While technology and source systems like an EAM system, CMMS platforms, IoT technologies, data management tools and task management applications are at the very center of these processes; people and processes have an equal role to play to ensure success of these initiatives.
In addition to the drawbacks mentioned above, one of the main critiques of these technologies is that they are not tailored to business or industry requirements.
The section below will cover some of the possible solutions that enterprises can explore to make the most of their EAM software, ensure seamless adoption and gun for the highest standards in operational excellence, at least as far as production and maintenance workflows are concerned.
Data is the very beating heart of these EAM systems, and any compromised data quality can lead to serious deficiencies in day-to-day operations. All ERP systems have inbuilt modules for warehousing and managing the quality of data across different data types, some of the data types that are of particular relevance to energy industries are detailed below.
The goal of Master data Management is to maintain a single “clean” and “complete” record at an organizational level
The goal of equipment master data management, for example, is to maintain a complete, clean view of all the equipment and machinery used at the company, with information like plant location, specifications and category duly mapped.
MRO stands for maintenance, repairs and operations, and the goal of MRO master data is simply to maintain a complete, clean view of all the spare parts, tools and consumables used for maintenance operations.
An MRO master contains this data along with product category, Manufacturer name, Manufacturer part number short and long description along with key attributes and unit-of-measure of the given material part.
Complex operations in Oil & Gas pretty much means that companies need to work with several suppliers for a whole plethora of activities that require specialists; from field maintenance, supply of specific parts, raw materials and several others.
The goal of a supplier master is to warehouses this data, ensure its clean maintenance and clearly depict relationships between suppliers to ensure maximum negotiating power.
In addition to master data records, other data types that are critical to asset management are also warehoused and maintained in the ERP system.
A Bill of Material is one of them. Put simply, a Bill of Materials, or B-O-M, is nothing but an exhaustive list of products, spare parts and consumables that is required to repair or maintain a piece of equipment asset.
A work order, on the other hand, is a digital footprint that sequentially details the list of maintenance tasks, activities and replacements performed on a given piece of machinery.
Any given piece of machinery generally has multiple work orders linked to them and these need to be up-to-date in the ERP system for ensuring operational excellence.
Having worked with leading billion $ enterprises globally who are into upstream and mid-stream oil & gas operations, we at Verdantis, have developed deep expertise in building autonomous software solutions that builds operational excellence in Oil & Gas Maintenance operations.
We list some of the most critical challenges and the solution to these problems, that have been purpose built for enterprises in energy, oil & gas.
Despite the best of tooling and EAM solutions, an unreliable MRO master is fairly common at enterprises in energy operations. Some of the commonly known issues are,
1. Poor data governance practices have resulted in multiple master records for the same spart, invariably giving rise to overstocking and escalating inventory costs
2. Missing information like “Manufacturer name” or “Manufacturer Part Number” leads to inaccurate procurement decisions
3. Key details of the product like its “attributes”, “units of measurement” or “category” tend to be missing
4. Multiple taxonomies adopted at any given point, resulting in poorly managed and maintained data.
These data quality concerns can seriously affect operational performance and result in production downtime due to part unavailability, serious overstocking that directly escalates inventory costs and substandard maintenance operations that can affect the longevity of the assets.
To remedy this, Verdantis has rolled out Harmonize© and Integrity©, together these two are the foundations of a rock solid MRO Data Management service through autonomous AI-driven data normalization, enrichment and governance.
A bill of materials (B-O-M), as we mentioned earlier, is simply a dump of all the spare parts and consumables that are required for upkeep of a given piece of equipment or machinery. General best practices dictate that a digital record of B-O-M should be generated and updated in the Enterprise Asset Management system.
Moreover, the best manufacturing companies ensure that;
1. The B-O-M information linked to a given piece of equipment is mapped to the right record in the equipment master
2. Ensures that the spare parts detailed in the B-O-M are synchronized with the Material Master, such that if a new spare part that doesn’t originally exist in Material Material but exists in the BOM is detected, then a new record is autonomously created in the Material Master and if one already exists, the dependency is mapped out in the material master itself
3. BOMs are autonomously created and deduplicated from technical documentations, engineering drawings and supplier databases without any human intervention whatsoever
Along with managing Work Orders, bill of materials management is among the most important aspect in enterprise asset management strategies.
Verdantis’ iBOM solution is one of the first products in the market that leverages purpose-built AI models to autonomously take care of all the 3 pointers we’ve discussed above.
A work order is simply a summary of all maintenance activities carried out for the upkeep of a given piece of machinery. Modern ERP/EAM systems are designed such that an executed work order for a given piece of machinery should be updated in the system so that a digital footprint of the asset is maintained.
However, due to human errors, omissions, lack of organizational controls; it’s very common for these work orders to be updated in a timely manner.
Since this is a periodic maintenance activity, these work orders pile up and these are to be updated sequentially as per the timelines to ensure proper tracking and historical context of a given piece of equipment.
So retrospectively updating these in-bulk was previously a very cumbersome and resource-intensive task.
With specially trained AI-systems, like WorkSync© that we’ve built here at Verdantis, updating historical work orders into the system is far simpler.
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