Integrated digital twin creation improves gas plant operations, profits

Some Permian basin producers and processors have fared better than than other US operating companies with the coronavirus (COVID-19) pandemic continuing to weigh on global petroleum markets.

July 6, 2020

8 min read

Duncan Micklem
KBC-A Yokogawa Co.
Houston

Some Permian basin producers and processors have fared better than than other US operating companies with the coronavirus (COVID-19) pandemic continuing to weigh on global petroleum markets. Impending production curtailments and expectations for sustained lower oil prices have resulted in major cuts to capital spending. The long-term viability of Permian operators will hinge on their ability to maintain operations at the lowest possible costs in both their drilling as well as production operations.

As the industry now faces a months-long road to recovery, profitability and sustainability of Permian oil and gas activities will depend more than ever on the degree to which operators embrace deeper and broader digitalization initiatives. Capitalizing on operational data already available to them will be key to maintaining competitive advantage.

Ahead of the COVID-19 crisis and its subsequent impact to crude oil prices, a natural gas processor contacted KBC-A Yokogawa Co. to help optimize operations as a means of increasing overall plant profitability. To execute the project, KBC used its Petro-SIM process simulation software to create both a site-wide simulation model for identifying profit-increasing opportunities as well as a digital twin of the plant to monitor future operations.

In addition to establishing a culture and system of data governance to ensure ongoing continuous improvement across plant operations, the digitalization initiative resulted in identification and implementation of no-cost improvement opportunities that enabled the gas processor to generate incremental profits of $7 million/year.

This article examines the impact of lower oil prices on Permian basin operations, outlines guidelines for achieving meaningful digitalization, and presents a lifecycle data management approach for leveraging real-time event infrastructure in existing assets to increase profitability.

Permian price woes

In its May 2020 Short-Term Energy Outlook, the US Energy Information Administration projected that spot prices for benchmark West Texas Intermediate (WTI) crude oil will average $30/bbl in 2020—down from an average of $57/bbl in 2019 and about $60/bbl in early 2020—before averaging $43/bbl in 2021.

Even with various Wall Street bank forecasts in early May predicting an average WTI price of $51/bbl in 2021 offering some optimism, the dilemma for many operators remains that their pre-2020 Permian growth forecasts will not be realized. This will leave much of their production unviable for at least the next 12 months.

With crude prices lingering near their lowest levels in more than 20 years, Permian producers and processors continue to face obstacles despite their relative resilience compared with operators in other US regions.

Surveys of 92 exploration and production companies conducted in mid-March by the Federal Reserve Bank of Dallas show that most of the Permian remains unprofitable at recent crude prices. To profitably drill a new well in the Permian’s Midland or Delaware basins requires WTI breakeven prices in a range of $30-35/bbl (minimum) to $60-70/bbl (maximum), with a mean of $46-52/bbl (mean) (Fig. 1).

To cover operating expenses for existing wells in those same basins requires WTI breakeven prices in a range of $5-9/bbl (minimum) to $50-55/bbl (maximum), with a mean of $26-32/bbl (mean) (Fig. 2).

In June, Wood Mackenzie—which earlier estimated the lowest breakeven prices in the Permian’s high-inventory Wolfcamp formation in a range of $35-38/bbl—said that, while the Permian has long been viewed as the US Lower 48’s growth engine, driving infrastructure investment, E&Ps in the region will now place greater emphasis on cash flow generation than production growth, even as oil prices improve (OGJ Online, June 3, 2020). Wood Mackenzie noted these production cuts will present ongoing difficulties for Permian midstream operators since components of the industry is intertwined in such a way that the relative success, failure, or financial health of one naturally impacts the others.

Given the scale of untapped Permian resources in the context of total US production amid still-reduced demand resulting from COVID-19, the current oversupplied market can be viewed as a battleground between Russia, Saudi Arabia, and Permian operators to see who can continue producing at the lowest cost. To remain relevant in this clash, E&Ps, processors, and other midstream companies operating in the Permian have invested in predictive analytics and digitalization tools to turn available operational data into usable insights for making informed decisions that improve performance.

Readiness is key

Driving down operational costs of any asset can best be achieved through systematic, data-driven approaches.

Any data-driven approach for continuous improvement requires definition, ongoing tracking, and reporting of key performance indicators against targets. Haphazardly providing tools and applications to steward operations conformance against targets and constraints is pointless unless basic methods are first in place to efficiently measure these activities.

All well-planned digitalization initiatives should follow a roadmap (Fig. 3). Readiness, the first step on this map, is critical for reaping productivity and efficiency improvement across the operational asset. From automatic real-time performance tracking and analysis, through web-based applications using—in the case of drilling— wellsite information transfer standard markup language (WITSML) protocol, to automatic real-time asset optimization using integrated process and utilities digital twins, the underlying data and infrastructure management approach is vital (Fig. 4).

Many organizations, however, fall into the trap of reaching for enhanced situational awareness and decision-support tools because they neglect to address readiness first. These companies often invest in more siloed, ad hoc approaches to data management that handle individual asset lifecycle stages in isolation from each other, with little data carried from one stage to the next to enrich the level of overall asset knowledge. Without a deliberate, coordinated approach to holistic operations data management, digitalization initiatives underdeliver on their potential, eroding their return on investment.

Permian operators must treat real-time data as a corporate asset, based off which real-time monitoring and optimization solutions can be developed and implemented.

As the following gas plant case study illustrates, the lifecycle data management approach—which is easily adaptable to production and transportation operations—ensures asset knowledge is captured efficiently, progressively enhanced from one asset lifecycle stage to the next, and leveraged throughout the life of the asset; or equally, from drilling, through completion and production.

Project objectives

The gas processor contacted KBC seeking help to grow profitability of its multi-train natural gas and LPG plant by at least $3 million/year. The operator identified some yield and energy improvements as potential sources of savings. Despite the plant’s already relatively low energy costs, KBC was tasked with finding additional ways to improve plant yields and use less energy.

To develop a corporate culture of continuous improvement, however, the operator needed to improve employees’ skill sets. Although the plant already was using Petro-SIM as its integrated process and utilities modelling and optimization software, its operations team wanted to leverage the software’s ability to process real-time data from the on-site data historian—OSIsoft LLC’s OSIsoft PI—to create a digital twin of the plant. As plant employees gained more detailed and accurate insights into situations as they occurred in real time, their confidence in the model’s integrity grew.

Project execution, results

To identify additional yield-improvement and energy-savings opportunities at the plant, KBC consultants used Petro-SIM software to create a site-wide process and utilities simulation model.

The model, which was used to identify more than 50 improvement opportunities, also helped pinpoint potential gaps as well as test the value associated with each of the recommended improvements. Working with the plant operator, KBC consultants narrowed down the profit-improvement opportunities based on practicality and feasibility. The project team eventually agreed to implement 24 of the identified opportunities that—requiring no capital expenditures—enabled the operator to increase profits by more than $10 million/year.

One of the major profit-improvement opportunities identified by the site-wide process and simulation model was gas turbine generator spinning reserve resulting from too many generators running at low loads. To address the issue, KBC built an online sparing management tool (Fig. 5). The sparing tool assessed the gas turbines’ performance, providing real-time recommendations for switching the turbines on or off to maintain necessary spinning reserve at maximum energy efficiency. This improvement opportunity alone resulted in energy savings of about $3 million/year.

To help meet the operator’s goal of achieving a corporate culture of continuous improvement, KBC placed a site-wide integrated process and utilities model online, allowing it to consume real-time data from the plant’s OSIsoft PI real-time event infrastructure to create an integrated process and utilities digital twin of the plant.

The project team integrated the site-wide Petro-SIM model and OSIsoft PI real-time event infrastructure to ensure constant synchronization (Fig. 6).

In addition to its ability to consume real-time data from the OSIsoft PI system, Petro-SIM continuously wrote all outputs back into the PI system, in real time, to amplify the PI system’s quality of data. Tight integration of Petro-SIM and the PI system enabled continuous synchronization of both systems through automated creation of PI asset framework (PI AF) templates and elements within the PI system from Petro-SIM. Automated updates of the PI AF elements occurred when the Petro-SIM model changed.

Synchronization also entailed automated population of the Petro-SIM model with current PI system data. This allowed the Petro-SIM model to serve as a granular-data enabled digital twin, allowing monitoring and surveillance of molecules and operating conditions across the plant and driving convergence in decision-making regarding its operations.

The author

Duncan Micklem ([email protected]) is executive vice-president of marketing at Yokogawa Corp. of America and KBC-A Yokogawa Co. After starting his career in the engineering industry with AMEC PLC, he moved to KBC as a technical consultant and has since held management roles focused on business development, strategy, restructuring, and planning. Micklem holds a BS both in biology and geography from the University of Exeter, UK, and an MBA from Cass Business School, UK.