October 2020


Digital: Enable reliable operations in a volatile oil and gas market

Hydrocarbon processing businesses increase profitability and survivability by optimizing production and/or reducing expenses to maximize profitability—or in the extreme, cash flow.

Covino, L., GE Digital

Hydrocarbon processing businesses increase profitability and survivability by optimizing production and/or reducing expenses to maximize profitability—or in the extreme, cash flow. This is vital today as oil and gas operating conditions are being affected by both the volatility in global prices, the resultant production impacts and the global pandemic. Surviving, if not thriving, in these conditions requires taking advantage of all available resources.

Operators must leverage technology and analytics to understand and uncover risks to their operations. The use of asset data and its application to equipment maintenance and daily operation offer a huge benefit for margin improvement.

Viewing asset performance

One of the chief concerns for operators has been operational and computerized maintenance management system (CMMS)/enterprise asset management (EAM) data quality. A focus on “bad actors,” along with detecting and discerning weak signals pointing to an impending failure of critical assets and systems, is vital to enterprise success. The last thing we need is wasteful spending of precious resources to address a failure that could have been prevented or predicted, allowing a planned intervention, eliminating a catastrophic failure with potentially devastating impacts to employees, communities, customers, license-to-operate and corporate brand.

Today’s digital technology capabilities allow us to benchmark, both internally and externally, like never before. With the ability to view asset performance across plants and businesses, as well as anonymously and legally across companies, we can identify what best-in-class looks like and then target efforts to dramatically improve competitive performance.

Using the latest digital technology, clean data and good engineering practices, we can develop and implement risk-based asset performance management (APM) strategies and associated tasks—such as risk-based inspection (RBI) and reliability-centered maintenance (RCM)—that can create a competitive cost and performance advantage, while minimizing operational risk. We can also use today’s robust technology capabilities to provide risk-based organizational capability to record, track and prioritize the sea of recommendations and action items that have become so routine in our operations.

Data collection and quality

Relative to aging workforce demographics, another huge benefit of today’s digital technology is the ability to capture and codify institutional knowledge and tribal practices that have been, and will continue to be, critical to creating and sustaining competitive advantage.

Data collection has greatly improved with the advent of lower-cost sensors and automated data input opportunities. Regardless, a significant amount of data is still being collected in a non-structured format, and companies struggle with understanding their assets due to a lack of clear, universal standards; inconsistent asset categorization and classification; and non-existent asset risk assessments.

Data quality is problematic for many reasons, not the least of which is that few companies handle asset/equipment data well. Even those that do still have huge challenges with confidence in the data collected, and the time and cost involved with improving it to the point of practical usability. Most will default to using the rudimentary information gleaned from the most readily available and believable data, which is likely to be a small percentage of all the data available.

Harvesting insights

A cost-effective way is needed to allow any company to make use of its data, and to analyze it and reach informed conclusions about acting on that information. Additionally, it would be helpful to know, “How does my asset performance compare to that of my peers/competitors?”

Capturing and harvesting operational data enables discovery of important insights that allow a focus on reliability performance improvement, rather than firefighting. Top-quartile performers have realized and have shared substantial positive results in environment, health and safety (EHS), production and cost performance, as well as employee satisfaction and retention.

How can clean, accurate data provide industrial organizations with valuable insights?

  • Improve the understanding of the plant equipment, systems, operations and people
  • Provide insights to assets that are bad actors but have been previously hidden due to poor data quality
  • Give accurate modeling, estimating and calculating asset utilization for flexible planning
  • Enable an objective, concrete, consistent and repeatable approach to analyzing the data continuously.

Systematically extracting knowledge from description fields is difficult: they are riddled with misspellings, abbreviations and jargon, and much of the meaning is contextual. By utilizing the information from the description fields and fusing it with other data (dates, costs, criticality, service, etc.), operators can identify equipment at risk. This could include:

  • Inconsistently coded data. Preventive maintenance issues (PMs) that are coded as repairs is one example. Mining the description fields can identify this inconsistent data and return insights from the consistently poorly labeled data source.
  • Identifying chronic failures. These can include issues such as a recurring filter plugging coded as PMs, for example.
  • Clarifying trends. It is one thing to know there were 10 seal leaks over the past few years, but it is another to distinguish if most of them occurred in the past 5 mos, or if they all occurred before the last turnaround or with a particular brand of equipment or seal.
  • Maintenance strategy insights. Being able to answer, “Is my current maintenance strategy effective?” through understanding the relationships between risks and mitigating actions from the historical data.


We must continue to be reminded that our greatest vulnerability is in abnormal plant operations that, many times, result from unplanned asset failures. An organizational obsession on eliminating unplanned failures is aspirational, inspirational and empowering, turning emotional energy and capacity into productive activity rooted in data. This includes creating strategies that are based on data and not simply the clock or calendar.

As such, the ability to gain rapid information and insights through clean data is paramount to our ability to make smart decisions. Digital capabilities are incredibly powerful in identifying trends, weak signals, important anomalies, along with potential correlational and causation effects even within unorganized data that can be considered poor quality. It is a challenging yet compelling time to question things as they are, look for solutions outside our existing norms, listen to what our assets are telling us, and then understand and adjust our asset management strategies to align with business strategies.

Another significant opportunity that clean data and this period of uncertainty present is footprint optimization. Proactive companies are taking this opportunity to analyze their data to understand asset utilization vs. production needs and capabilities as a means of optimizing their footprint as they prepare to be stronger when better times come.

CMMS data contains a wealth of information and knowledge that is hidden, because much of it is not machine readable. Advanced analytics exist to tackle these challenges. This is a hybrid approach—combining industry-specific domain knowledge with machine-learning technology.

As the market continues to evolve, it will be important to retain and build capabilities to navigate the changes that today’s world presents. Companies should be looking at what is needed vs. what should be cut. Analytics based on well-organized, quality data can drive decisions that will help operators respond to issues rapidly and effectively, resulting in optimized production and costs. HP

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