CNX Uses InfinityPL from Ambyint to Reduce GHG Emissions by 48%

Natural gas company CNX Resources Corporation (CNX) reduced its greenhouse gas (GHG) emissions by 48 percent and increased the production of its natural gas wells by 4 percent through its collaboration with AWS Partner Ambyint. CNX first engaged Ambyint while looking for a solution to optimize the performance of its wells and streamline internal workflows. In 2021 CNX adopted Ambyint InfinityPL (InfinityPL), a solution that is powered by artificial intelligence (AI) and that runs entirely on Amazon Web Services (AWS). CNX’s deployment of the solution across 120 wells has supported its corporate sustainability goals, streamlined internal workflows, and maximized the production of its wells.

Natural gas company CNX wanted to optimize the performance of its plunger lift systems, which help remove coproduced liquids from its wells, so that it could optimize production, detect equipment issues, and reduce its GHG emissions. Moreover, the company wanted to fulfill these goals without creating additional manual work for its teams or purchasing more hardware for the plunger lift systems.

In 2020, CNX turned to AWS Partner Ambyint, adopting InfinityPL, a software-as-a-service solution that runs entirely on AWS and helps oil and gas companies increase production and reduce operating expenditures. CNX and Ambyint collaborated to set up InfinityPL alongside CNX’s existing supervisory control and data acquisition (SCADA) system, and 6 months after testing this solution, CNX deployed it across 120 wells. As a result, CNX reduced its GHG emissions by 48 percent, increased its natural gas production rates by 4 percent, and supported its corporate sustainability goals.

CNX is a premier natural gas development, production, midstream, and technology company with operations throughout the Appalachian Basin, primarily in the Marcellus Shale and the Utica Shale in Pennsylvania, Ohio, and West Virginia. The company is continuously reducing GHG and other emissions in addition to running a robust methane abatement program.

Prior to its collaboration with Ambyint, CNX had wells in the Marcellus Shale that were prone to liquid loading, a condition that occurs when water or gas condensate accumulate in the well bottom, thereby slowing natural gas production rates. To remediate liquid loading, the CNX team sought to optimize and remediate liquid loading events and streamline internal workflows.

The natural gas company was looking to optimize the performance of these wells, reduce its GHG emissions, and free up its teams from redundant tasks when it turned to Ambyint. The partner provides AI-powered solutions that help oil and gas companies optimize the performance of their wells. The company has over 10 years of experience working on AWS and participates in the AWS Energy Competency Program, which identifies, validates, and promotes AWS Energy Competency Partners with demonstrated AWS technical expertise and proven customer success in building and implementing advanced solutions across the energy industry value chain. Ambyint is also a technology partner for the AWS Energy production optimization solution, which helps upstream operators increase their productivity using data and insights extracted from their production operations. “Our solutions help companies maximize their production rates, improve their operating expenditures, reduce their GHG emissions, and increase the reliability of their systems,” says Chris Robart, chief commercial officer of Ambyint. In collaboration with Ambyint, CNX decided to pilot InfinityPL alongside its existing SCADA system.

CNX and Ambyint configured InfinityPL for a handful of wells, gathering data from CNX’s SCADA system, which uses sensors to stream data about the status of the well equipment remotely. While setting up InfinityPL, CNX did not have to invest in additional hardware or infrastructure to deploy the solution. Rather, CNX benefits from the fact that Ambyint can offer InfinityPL as software as a service because of its scalable backend built on AWS.

InfinityPL runs on Amazon Elastic Kubernetes Service (Amazon EKS), a managed container service that runs and scales Kubernetes applications in the cloud or on premises. Using this service, Ambyint can deploy InfinityPL across both cloud-native and hybrid environments. To maintain high availability, Ambyint also uses Elastic Load Balancing (ELB), which distributes network traffic to improve application scalability. For 6 months, CNX piloted InfinityPL, receiving technical support from Ambyint with the configuration of its SCADA system. “Using InfinityPL, CNX can remotely control and send commands to its well equipment,” says Robart.

Moreover, InfinityPL collects data from CNX’s plunger lift systems to determine their ideal controller set points, helping optimize production and streamline CNX teams’ internal workflows. Ambyint stores the data it collects from InfinityPL on Amazon Simple Storage Service (Amazon S3), an object storage service built to retrieve virtually any amount of data from anywhere. Further, Ambyint keeps the data secure by setting up a highly controlled environment in the cloud using Amazon Virtual Private Cloud (Amazon VPC), which lets organizations define and launch AWS resources in a logically isolated virtual network. Using this data, InfinityPL can also predict potential equipment problems and identify maintenance opportunities, supporting CNX in its efforts to maximize its return on investment.

Once CNX finished piloting the solution, the company decided to move forward with implementing InfinityPL across its plunger lift systems for 120 of its production wells. Since then, CNX has minimized the occurrences of liquid loading, and its teams no longer have to vent wells. As a result, the company reduced its GHG emissions by 48 percent, which represents about 18 metric tons of carbon emissions across each of its wells annually. In turn, CNX can support its corporate sustainability initiatives. Furthermore, the company optimized the performance of its wells, experiencing a 4 percent increase in its natural gas production rates.

Moving forward, CNX will continue to optimize the performance of its natural gas wells using InfinityPL. Ambyint also plans to build more machine learning models to deliver deeper, more intuitive insights to its customers. “We love AWS,” says Robart. “The AWS team is very supportive and provides us with the technical expertise we need to build more products that are relevant to our customers.”