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SCADA-Informed Emissions Management.

Where operational and environmental data meet. 

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The Future of Methane Management Makes Smarter Use of the Data You Already Have

Our AI-driven solution leverages operational data, including SCADA, to enable digital emissions monitoring.

Detection & Duration

of emission events for more accurate reporting and response.

Causation:

Understand the cause behind the event, supporting preventative maintenance & abatement.

Prioritization

of field responses for events such as unlit pilot flares, tank thief hatches, and more.

Prediction:

Gain early detection of major emission events to reduce liability and manage risk.

Applications

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Unlit Flares

Optimize field response, reduce regulatory/reputational risk, mitigate fine exposure, automate reporting.

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Routine Flaring

Lower regulatory risk and emissions, align with corporate commitments, increase resource capture, and improve operational efficiencies while eliminating reliance on operator inputs for reporting.

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Tank Emissions
(e.g., Thief hatch, PRVs)

Optimize field response. Reduce regulatory risk and emissions, decrease investment in hardware through digital continuous monitoring, and limit carbon cost exposure.

 

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Equipment Optimization
(e.g., VRUs, CEMS)

Decrease OpEx, resource capture, lower emissions, and reduce CapEx investment in hardware (e.g., subscriptions, rentals, installations).

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Stationary Combustion
(e.g., Methane Slip, engine efficiency)

Inform power management plans, support engine efficiency, fuel usage, site uptime, reduce regulatory risk, and lower cost per unit power.

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Manual Reporting Events
(e.g., compressor blowdowns)

Automate reporting and eliminate reliance on operator inputs. Improve reporting accuracy and limit carbon cost exposure.

Proven ROI

95 %

Reduction

Reduce events requiring manual review by up to 95%.

90 %

Efficiency

Cut root cause analysis effort by 90% or more.

1 - month

Time to value

Reduce reliance on expensive sensors - leveraging data already collected onsite.

Case Study Improved Flare Management 

A midcap Bakken producer wanted to better understand high-pressure flaring on its sites. Flare event causation, duration, and eventual the ability to predict and proactively manage events was critical to an effective abatement plan. The goal was to ensure compliance with current and future flare rules and to better optimize operations. The project increased production (gas and liquids) by over 150,000 BOEs (25% liquids) over a 12-month period, added over $2 million in additional commodity revenues, and millions in contracted additional revenues. And, among other operational benefits, reduced flare volumes by 80% on the impacted locations.

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 Detection & Causation

Why did the flare event occur? By automating the root cause investigation, they were able to validate whether the event was routine or non-routine, and from there, what actions need to be taken to mitigate future similar events. While the hypothesis was that most flare events were unavoidable, they found that many were manageable with little to no cost, often being an improvement in process, not an investment, that can eliminate some flare events. There was an added benefit of being able to understand unlit flares and Super Emitter risk.

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Duration

Many jurisdictions have reporting requirements that include reporting the reason, length and number of flare events. They were able to leverage SCADA / metered data on location to ensure that they could accurately report all events with ease, which eliminated the need for one full time equivalent role.

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Prediction

The company is able to proactively manage future events by incorporating flare limits and other threshold requirements. They have also successfully been able to predict, with a high level of accuracy, several specific flare situations, which has allowed them to efficiently manage various onsite programs, such as VRU optimization, maintenance programs, and pumper response.

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Learn More Through Our AroIQ Blog

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Get in touch to discuss low-risk pilots that deliver value within 1 month.