Alan Bryant (Oxy and the ISA Chemicals and Petroleum Industries Division - ChemPID) presented on carbon capture and sequestration (CCS) accounting and automation. The oil and gas industry can impact Scope 1 and 2 direct greenhouse emissions that occur from sources associated with fuel combustion in boilers, furnaces, vehicles and from flaring, venting and fugitive emissions. The IEA estimates that eliminating flaring, venting and methane leaks from upstream operations would have the same effect on the global environment as eliminating the emissions from all the world’s road traffic. Achieving net zero will be virtually impossible without CCS. The good news is that potential storage capacity is ‘well in excess of what will be needed’. ‘The world has a vast capacity to store CO2’. Government incentives like tax credits and grants make these initiatives economically attractive. EOR is the biggest and most readily available opportunity for sequestration. To date, EOR typically uses naturally occurring/produced CO2. But capturing CO2 from industrial processes is becoming economically viable with recent incentives. This is where automation comes in to meter sequestered CO2 and back allocate to the different sources. Operators can earn offsets by sequestering more GHG than they produce. Automation can be leveraged to measure the inputs to the credit equation.
Andrew Walsh (Qube Technologies) explained that the EPA recently issued a supplemental proposal* to reduce methane and other harmful pollution from oil and gas operations. To date this has meant voluntary efforts. But from 2023, operators should provide rule-based monitoring and a plan explaining which sites are using alternative continuous monitoring systems. In which context, Qube provides a comprehensive approach to emissions reduction with continuous monitoring, as per the new rules. Qube’s Axon device is a self contained, powered unit that monitors flares, tank and fugitive emissions etc. which are captured to a dashboard for analytics and exploitation by leak detection and repair (LDAR) technicians. Pilots across multiple US basins have demonstrated a ‘65% fall in emissions’ from flaring mitigation, improved VRU system uptime and optimized maintenance. Qube supports auto-calibration for data quality assurance. The EPA regulations make up a ‘trifecta of operator, regulator and certifier’.
* See the EPA Fact Sheet on the new proposal.
Denis Drolet described Vermillion Energy’s use of exception-based operating procedures. Operating by exception means applying AI/ML to ‘minute by minute’ sensor data and photo analytics for leak detection. Such information informs preventive maintenance, operator intervention, chemicals management and also satisfies regulatory requirements for ESG, emissions tracking and more. Data is combined into a VETVision dashboard that aggregates exceptions into a forms/map and workflow-based display. Vermillion is currently working on data clean-up, governance and integration with ERP and cloud-based systems. Another issue is the ‘production vs opex’ battle for resources. Operator/pumper buy-in has been ‘less of an issue than you might think’!
Andrew Pruet (Oxy) presented his AVOID (Audio, Visual, Olfactory Inspection and Detection) hardware for cloud-based fugitive emission detection. Avoid is a small field-deployed hardware units comprising an ESP32 system on a chip microcontroller with integrated Wi-Fi and Bluetooth. Emissions are monitored with a catalytic bead ‘pellistor’ sensor and the unit is programmable in MicroPython. Devices feed over multiple wireless pathways to an Azure IoT hub via the Microsoft device provisioning service) and on to apps (PI Vision, PowerBI; Grafana, Spotfire).
Mark Peavy of Peavy Energy Ventures drilled down into the regulatory perspectives of the inflation reduction act (IRA) with regard to methane emissions. The 2022 IRA includes a charge on methane emissions comparable to the 2021 IRA (HR 5376). Note that this is the first time the federal government has directly imposed a tax on greenhouse gas emissions. The IRA is set to ‘fight inflation, lower energy costs and reduce carbon emissions by 40% by 2030’. A component of the IRA is the methane emissions reduction program (EPA 60113) and the IRA methane emissions charge. This starts at $900 per metric ton of methane, increasing to $1,500 after two years. The regulations call inter-alia for the elimination of high-bleed, natural gas-driven pneumatic devices. The new rules are proving problematical for smaller operators, some stripper well operators may find it hard to achieve compliance. But larger companies are all-in, with ExxonMobil planning to spend some $17 billion over five years on lower emissions initiatives. To finance such initiatives, some companies have issues sustainability-linked securities. Over $3 billion ESG bonds have been issued whose coupon rates climb if certain ESG goals are not met. Peavy concluded by recommending that independents get involved with the EPA on emissions regulations. The winners currently are the multi-nationals which will be leaders in carbon capture and alternative energy sources. But the ‘bell may be tolling’ for the small independent producer!
Richard Xu (Woodside) outlined a ‘fit for purpose, high level, automated data science workflow’. But first, you need a well-defined business problem to solve and to be sure that AI/ML is the best solution for the problem. Also key is an understanding the business process and the data required. Defining what success means is also a prerequisite and how the modeling results will be evaluated. A ‘solid and flexible data platform’ is critical for AI. A spatial capability and meta data catalogue complete the picture. Xu did not say what platform was deployed (we did ask) but Woodside has been a high profile user of IBM Watson as is witnessed by its data science landing page.
Robert Ward presented Kuva Systems’ work on correlating Scada data with time-stamped, colorized methane imagery to pinpoint emissions. 70% of emissions come from 2% of assets and occurrences are very intermittent. The EPA ‘super emitter’ proposal targets emissions of over 100kg/hr with penalties of up to $100k/day. Kuva’s pole-mounted sensors provide multiple views of a facility. These include infra red and visible RGB cameras with an ‘edge compute’ functionality. Use cases include leaking valves, unlit flares, corroded pipes and truck loading. Time-stamped imagery is correlated with Scada data and captured into the Kuva Azure cloud. Data can is also available in the customer’s cloud to integrate with ERP, SAP and other platforms (OGMP2.0, MiQ, Project Canary). The system has been successfully tested at METEC, the Methane Emission Technology Evaluation Center at Colorado State University where ‘Kuva was the only technology with no false alarms and strong detection performance*’
* See: Performance of continuous emission monitoring solutions under single-blind controlled testing protocol on ChemArchiv.org.
Sandro Esposito (Signal Fire)
advocated an emissions monitoring solution that is independent of the
installed Scada network. Operators want to minimize non-control related
data into the control system and to monitor asset health without
penetrating the control IT infrastructure. SignalFire’s ‘Sensor to
cloud’ telemetry leverages MQTT over LTE-M cellular networks, bypassing
the client’s infrastructure. The wireless IoT acts as an ‘air gap’ as
cellular is said to be ‘inherently more secure’ with authentication
from the device all the way to the endpoint. MQTT, the message queuing
transport telemetry is used in satellite-based pipeline monitoring and
to communicate with space probes. New devices broadcast ‘birth message’
of their data capabilities. Facebook Messenger
uses MQTT to minimize battery and bandwidth use. SparkplugB is used to
define a topic namespace, the MQTT payload and state. ‘Overall,
SparkPlugB standardizes an MQTT implementation to realize its benefits
in Scada applications’. Esposito categorized the combination of MQTT,
Sparkplug and LTE-M as a ‘tech trifecta’. A map of Mobile IoT
commercial launches to-date is availability from the GSM Association.
Other presentations of note include: Automated energy management by Dailey Tipton of Ndustrial.io. Goff Daily’s presentation of Techneaux’s Bifrost https://www.bifrostdata.io/ solution for bridging oil and data systems. Kris Palka’s exposé of Akinê’s Raven IIoT controller. More too on Akinê’s 18 month demonstrator project (supported by Alberta Innovates) on the PTAC website.
More from the American Business Conferences Wellsite Automation home page.
© Oil IT Journal - all rights reserved.